Updated on 2025/08/26

写真a

 
JIN, Qun
 
Affiliation
Faculty of Human Sciences, School of Human Sciences
Job title
Professor
Degree
Ph.D
Homepage URL
http://nislab.human.waseda.ac.jp/
Profile

Qun Jin is a professor in the Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Japan. He has been extensively engaged in research works in the fields of computer science, information systems, and human informatics, with a focus on understanding and supporting humans through convergent research. His recent research interests cover behavior and cognitive informatics, health informatics, big data, personal analytics and individual modeling, artificial intelligence and machine learning, LLM and generative AI, Ai agents, blockchain and privacy-preserving computing, metaverse, digital twin, IoT, trustworthy platforms for data federation, sharing, and utilization, cyber-physical-social systems, and applications in healthcare and learning support and for the realization of a carbon-neutral society. He is a foreign fellow of the Engineering Academy of Japan (EAJ).

Research Experience

  • 2003.04
    -
    Now

    Waseda University   Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences   Professor

  • 2018.09
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    2020.09

    Waseda University   Faculty of Human Sciences   Deputy Dean (International Affairs)

  • 2018.09
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    2020.09

    Waseda University   Graduate School of Human Sciences   Dean

  • 2014.09
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    2016.09

    Waseda University   Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences   Chair

  • 1999.04
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    2003.03

    University of Aizu   School of Computer Science and Engineering   Associate Professor

  • 1995.04
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    1999.03

    Tokushima University   Department of Information Science and Intelligent Systems, Faculty of Engineering   Associate Professor

  • 2020.06
    -
    2025.06

    INES Corporation   Outside Board Director

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Professional Memberships

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    ACM

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    IEEE Computer Society

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    IEEE

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    THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE

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    INFORMATION PROCESSING SOCIETY OF JAPAN

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    The Engineering Academy of Japan (EAJ)

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    CCF

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Research Areas

  • Intelligent informatics   Artificial intelligence, Machine learning, Generative AI, AI agents / Database   Big data, Personal data analytics / Web informatics and service informatics   Human informatics, Computing for well-being / Life, health and medical informatics   Smart health, AI-enhanced personalized healthcare / Learning support system   Personalized learning support, Learning analytics / Educational technology   e-learning support / Cognitive science   Behavior and cognitive informatics, Individual modeling

Research Interests

  • behavior and cognitive informatics

  • health informatics

  • artificial intelligence and machine learning

  • LLM and generative AI

  • AI agents

  • big data

  • personal analytics and individual modeling

  • digital twin

  • cyber security

  • blockchain

  • metaverse

  • applications in healthcare and learning support

  • smart energy and behavioral data analytics for carbon neutrality

  • computing for human well-being

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Awards

  • Andrew P. Sage Best Transactions Paper Award 2025 of IEEE Transactions on Computational Social Systems

    2025.07   IEEE SMC   Hierarchical Federated Learning With Social Context Clustering-Based Participant Selection for Internet of Medical Things Applications

    Winner： X. Zhou, X. Ye, K.I. Wang, W. Liang, N.K.C. Nair, S. Shimizu, Z. Yan and Q. Jin

  • ACM Best Student Paper Award（IEA/AIE 2025）

    2025.07   ACM SIGAI   To Earn Praise or to Avoid Denial: Classification of Approval Desires in SNS Posts Based on Sentiment Analysis with Generative AI

    Winner： E. Murata and Q. Jin

  • IEEE Best Student Paper Award（IEEE CyberSciTech 2024）

    2024.11   IEEE   A Two-Stage Depression Recognition Model Based on Improved YOLOv5 and Spatial-Temporal CNN Transformer Network

    Winner： J. Zhao, Q. Jin

  • Best Paper Award 2024, CCF Transactions on Pervasive Computing and Interaction

    2024.08   China Computer Federation (CCF) and Springer   Pre-braking behaviors analysis based on Hilbert–Huang transform

    Winner： B. Wu, Y. Zhu, R. Dong, K. Sato, S. Ikuno, S. Nishimura, Q. Jin

  • IEEE Transactions on Industrial Informatics Best Paper Award

    2023   Technical Committee on Industrail Informatics, IEEE Industrial Electronics Society   Intelligent Small Object Detection Based on Digital Twinning for Smart Manufacturing in Industrial CPS

    Winner： X. Zhou, X. Xu, W. Liang, Z. Zeng, S. Shimizu, L.T. Yang and Q. Jin

  • IEEE Outstanding Leadership Award

    2018   IEEE Computational Intelligence Society and IEEE Computer Society   General Chair of Fourth IEEE International Conference on Internet of People

  • IEEE Outstanding Leadership Award

    2016   IEEE Computer Society   General Chair of First IEEE Cyber Science and Technology Congress

  • IEEE Outstanding Service Award

    2013   IEEE System, Man, and Cybernetics Society   General Co-Chair of International Conference on Awareness Science and Technology and Ubi-Media Computing

  • Best Paper Award

    2011   Fourth IEEE International Conferences on Cyber, Physical and Social Computing  

  • Excellence Award (Operational Practice)

    2005   Japanese Society for Information and Systems in Education and Science Council of Japan   Contest for Excellent Educational Practice Using ICT

  • Best Paper Award

    2016   Seventh International Conference on the Applications of Digital Information and Web Technologies  

  • Best Paper Award

    2014   Sixth International Conference on Information Technology in Medicine and Education  

  • Best Paper Award

    2012   Fifth IET International Conference on Ubi-Media Computing  

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Papers

  • MICCAI 2023 STS Challenge: A retrospective study of semi-supervised approaches for teeth segmentation.

    Yaqi Wang 0002, Yifan Zhang, Xiaodiao Chen, Shuai Wang 0003, Dahong Qian, Fan Ye, Feng Xu, Hongyuan Zhang 0002, Ruilong Dan, Qianni Zhang, Xingru Huang, Zhao Huang, Jun Liu 0027, Zhiwen Zheng, Chengyu Wu, Yunxiang Li, Zhi Li, Zhean Ma, Weiwei Cui 0003, Shan Luo 0003, Chengkai Wang, Yifei Chen, Tianhao Li, Yi Liu, Xiang Feng, Jiaxue Ni, Dongyun Liu, Qixuan Wang, Zhouhao Lin, Wei Song, Yuanlin Li, Bing Wang, Chunshi Wang, Qiupu Chen, Mingqian Li, Huiyu Zhou 0001, Qun Jin

    Pattern Recognit.   170   112049 - 112049  2026  [Refereed]

    Authorship：Last author

    DOI

  • Hilbert-Huang transform based pupil changes analysis for concentration assessment in skilled mowing.

    Bo Wu, Yuan Wu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

    Scientific reports   15 ( 1 ) 21862 - 21862  2025.07  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    In the hilly and mountainous areas of Japan, mowing operations can only be carried out by human labor because of the steep slopes. However, the environment faced by workers when mowing is complex, requiring them to deal with different visual stimuli at the same time. These factors will also be reflected in the data of specific pupil changes, further impacting their concentration while mowing. Therefore, in this study, based on a set of experiments on various terrain (flat land and slope) in Hiroshima, Japan, an analysis method of human pupil changes was proposed based on action decomposition technology Hilbert-Huang Transform (HHT) which can be used to calculate the different frequency patterns (intrinsic mode function, IMF) that represent nonlinearity in pupil changes more effectively than Fourier Transform or Wavelet Transform. Based on the use of our proposed Multiple Comparisons and Filtering framework named MCFID, the IMFs which directly related to specific mowing actions (cutting and lifting) were found though the statistical tools. By monitoring the corresponding IMFs, it is possible to calculate the period of the corresponding pupil movement, and further inversely infer information such as the subject's concentration status. Our approach can also be validated using other pupil movement datasets. The results of the study can provide useful insights for training new lawn mowers, and the relevant data can be used as data accumulation for the development of future fall detection systems.

    DOI PubMed

  • Intelligent games meeting with multi-agent deep reinforcement learning: a comprehensive review.

    Yiqin Wang, Yufeng Wang 0001, Feng Tian, Jianhua Ma 0002, Qun Jin

    Artificial Intelligence Review   58 ( 6 ) 165 - 165  2025.06  [Refereed]

    Authorship：Last author

    DOI

  • Decentralized Federated Graph Learning With Lightweight Zero Trust Architecture for Next-Generation Networking Security

    Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Katsutoshi Yada, Laurence T. Yang, Jianhua Ma, Qun Jin

    IEEE Journal on Selected Areas in Communications   43 ( 6 ) 1908 - 1922  2025.06  [Refereed]

    Authorship：Last author

    DOI

  • Locational False Data Injection Attack Detection in Smart Grid Using Recursive Variational Graph Autoencoder

    Yufeng Wang, Ziyan Lu, Jianhua Ma, Qun Jin

    IEEE Internet of Things Journal   12 ( 10 ) 13697 - 13708  2025.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Information Theoretic Learning-Enhanced Dual-Generative Adversarial Networks With Causal Representation for Robust OOD Generalization

    Xiaokang Zhou, Xuzhe Zheng, Tian Shu, Wei Liang, Kevin I-Kai Wang, Lianyong Qi, Shohei Shimizu, Qun Jin

    IEEE Transactions on Neural Networks and Learning Systems   36 ( 2 ) 2066 - 2079  2025.02  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    Recently, machine/deep learning techniques are achieving remarkable success in a variety of intelligent control and management systems, promising to change the future of artificial intelligence (AI) scenarios. However, they still suffer from some intractable difficulty or limitations for model training, such as the out-of-distribution (OOD) issue, in modern smart manufacturing or intelligent transportation systems (ITSs). In this study, we newly design and introduce a deep generative model framework, which seamlessly incorporates the information theoretic learning (ITL) and causal representation learning (CRL) in a dual-generative adversarial network (Dual-GAN) architecture, aiming to enhance the robust OOD generalization in modern machine learning (ML) paradigms. In particular, an ITL- and CRL-enhanced Dual-GAN (ITCRL-DGAN) model is presented, which includes an autoencoder with CRL (AE-CRL) structure to aid the dual-adversarial training with causality-inspired feature representations and a Dual-GAN structure to improve the data augmentation in both feature and data levels. Following a newly designed feature separation strategy, a causal graph is built and improved based on the information theory, which can enhance the causally related factors among the separated core features and further enrich the feature representation with the counterfactual features via interventions based on the refined causal relationships. The ITL is incorporated to improve the extraction of low-dimensional feature representations and learn the optimized causal representations based on the idea of "information flow." A dual-adversarial training mechanism is then developed, which not only enables the generator to expand the boundary of feature distribution in accordance with the optimized feature representation from AE-CRL, but also allows the discriminator to further verify and improve the quality of the augmented data for OOD generalization. Experiment and evaluation results based on an open-source dataset demonstrate the outstanding learning efficiency and classification performance of our proposed model for robust OOD generalization in modern smart applications compared with three baseline methods.

    DOI PubMed

  • STCA-LLM: Spatial-Temporal Cross-Attention Large Language Model for Wind Speed Forecasting

    Chengjie Zhou, Yufeng Wang, Jianhua Ma, Qun Jin

    IEEE Internet of Things Journal    2025  [Refereed]

    Authorship：Last author

    DOI

  • MFFTD: A Multiscale Feature Fusion Transformer Detector for Electricity Theft Based on Semi-Supervised Learning

    Yufeng Wang, Zhijie Wu, Jianhua Ma, Qun Jin

    IEEE Transactions on Instrumentation and Measurement   74   1 - 10  2025  [Refereed]

    Authorship：Last author

    DOI

  • Adaptive Weighting via Federated Evaluation Mechanism for Domain Adaptation with Edge Devices

    Rui Zhao, Xiao Yang, Peng Zhi, Rui Zhou, Qingguo Zhou, Qun Jin

    ACM Transactions on Sensor Networks    2024.07  [Refereed]

    Authorship：Last author

    DOI

  • Personalized Federated Learning with Model-Contrastive Learning for Multi-Modal User Modeling in Human-Centric Metaverse

    Xiaokang Zhou, Qiuyue Yang, Xuzhe Zheng, Wei Liang, Kevin I.Kai Wang, Jianhua Ma, Yi Pan, Qun Jin

    IEEE Journal on Selected Areas in Communications   42 ( 4 ) 817 - 831  2024.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    83
    Citation
    (Scopus)

  • Group Behavior Prediction and Evolution in Social Networks

    Jingchao Wang, Xinyi Zhang, Weimin Li, Xiao Yu, Fangfang Liu, Qun Jin

    IEEE Intelligent Systems   39 ( 2 ) 62 - 65  2024.03  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
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  • Reconstructed Graph Neural Network With Knowledge Distillation for Lightweight Anomaly Detection

    Xiaokang Zhou, Jiayi Wu, Wei Liang, Kevin I-Kai Wang, Zheng Yan, Laurence T. Yang, Qun Jin

    IEEE Transactions on Neural Networks and Learning Systems   35 ( 9 ) 11817 - 11828  2024  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    The proliferation of Internet-of-Things (IoT) technologies in modern smart society enables massive data exchange for offering intelligent services. It becomes essential to ensure secure communications while exchanging highly sensitive IoT data efficiently, which leads to high demands for lightweight models or algorithms with limited computation capability provided by individual IoT devices. In this study, a graph representation learning model, which seamlessly incorporates graph neural network (GNN) and knowledge distillation (KD) techniques, named reconstructed graph with global-local distillation (RG-GLD), is designed to realize the lightweight anomaly detection across IoT communication networks. In particular, a new graph network reconstruction strategy, which treats data communications as nodes in a directed graph while edges are then connected according to two specifically defined rules, is devised and applied to facilitate the graph representation learning in secure and efficient IoT communications. Both the structural and traffic features are then extracted from the graph data and flow data respectively, based on the graph attention network (GAT) and multilayer perceptron (MLP) techniques. These can benefit the GNN-based KD process in accordance with the more effective feature fusion and representation, considering both structural and data levels across the dynamic IoT networks. Furthermore, a lightweight local subgraph preservation mechanism improved by the graph attention mechanism and downsampling scheme to better utilize the topological information, and a so-called global information alignment defined based on the self-attention mechanism to effectively preserve the global information, are developed and incorporated in a refined graph attention based KD scheme. Compared with four different baseline methods, experiments and evaluations conducted based on two public datasets demonstrate the usefulness and effectiveness of our proposed model in improving the efficiency of knowledge transfer with higher classification accuracy but lower computational load, which can be deployed for lightweight anomaly detection in sustainable IoT computing environments.

    DOI PubMed

    Scopus

    60
    Citation
    (Scopus)

  • LASGRec: A Personalized Recommender Based on Learnable Attribute Sampling and Graph Neural Network

    Yufeng Wang, Xun Huang, Jianhua Ma, Qun Jin

    IEEE Transactions on Computational Social Systems    2024  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • HGCR: A Heterogeneous Graph-Enhanced Interactive Course Recommendation Scheme for Online Learning

    Yufeng Wang, Dehua Ma, Jianhua Ma, Qun Jin

    IEEE Transactions on Learning Technologies    2024  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • TE-TFN: A Text-enhanced Transformer Fusion Network for Multimodal Knowledge Graph Completion

    Jingchao Wang, Xiao Liu, Weimin Li, Fangfang Liu, Xing Wu, Qun Jin

    IEEE Intelligent Systems   39 ( 3 ) 54 - 62  2024  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Guest Editorial: Special Issue on Responsible AI in Social Computing

    Qinghua Lu, Weishan Zhang, Zhen Wang, Qun Jin, Vincenzo Piuri

    IEEE Transactions on Computational Social Systems    2023.12  [Invited]

    DOI

    Scopus

  • Hierarchical Federated Learning With Social Context Clustering-Based Participant Selection for Internet of Medical Things Applications.

    Xiaokang Zhou, Xiaozhou Ye, Kevin I-Kai Wang, Wei Liang 0006, Nirmal-Kumar C. Nair, Shohei Shimizu, Zheng Yan 0002, Qun Jin

    IEEE Transactions on Computational Social Systems   10 ( 4 ) 1742 - 1751  2023.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    150
    Citation
    (Scopus)

  • CDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound.

    Ruilong Dan, Yunxiang Li, Yijie Wang, Xiaodiao Chen, Gangyong Jia, Shuai Wang 0003, Ruiquan Ge, Guiping Qian, Qun Jin, Juan Ye, Yaqi Wang

    IEEE Journal of Biomedical and Health Informatics   27 ( 7 ) 3525 - 3536  2023.07  [Refereed]  [International journal]

    DOI PubMed

    Scopus

    7
    Citation
    (Scopus)

  • Bi-Dueling DQN Enhanced Two-Stage Scheduling for Augmented Surveillance in Smart EMS.

    Wei Liang 0006, Weiquan Xie, Xiaokang Zhou, Kevin I-Kai Wang, Jianhua Ma, Qun Jin

    IEEE Transactions on Industrial Informatics   19 ( 7 ) 8218 - 8228  2023.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • Intelligent Containment Control With Double Constraints for Cloud-Based Collaborative Manufacturing.

    Xiaokang Zhou, Hailiang Hou, Wei Liang 0006, Kevin I-Kai Wang, Qun Jin

    IEEE Transactions on Industrial Informatics   19 ( 6 ) 7541 - 7551  2023.06  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Decentralized P2P Federated Learning for Privacy-Preserving and Resilient Mobile Robotic Systems.

    Xiaokang Zhou, Wei Liang 0006, Kevin I-Kai Wang, Zheng Yan 0002, Laurence T. Yang, Wei Wei 0006, Jianhua Ma, Qun Jin

    IEEE Wireless Communications   30 ( 2 ) 82 - 89  2023.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    102
    Citation
    (Scopus)

  • Edge-Enabled Two-Stage Scheduling Based on Deep Reinforcement Learning for Internet of Everything.

    Xiaokang Zhou, Wei Liang 0006, Ke Yan 0001, Weimin Li, Kevin I-Kai Wang, Jianhua Ma, Qun Jin

    IEEE Internet of Things Journal   10 ( 4 ) 3295 - 3304  2023.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    103
    Citation
    (Scopus)

  • An Efficient Smart Contract Vulnerability Detector Based on Semantic Contract Graphs Using Approximate Graph Matching

    Yingli Zhang, Jiali Ma, Xin Liu, Guodong Ye, Qun Jin, Jianhua Ma, Qingguo Zhou

    IEEE Internet of Things Journal    2023  [Refereed]

    DOI

    Scopus

    10
    Citation
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  • Distribution Bias Aware Collaborative Generative Adversarial Network for Imbalanced Deep Learning in Industrial IoT.

    Xiaokang Zhou, Yiyong Hu, Jiayi Wu, Wei Liang 0006, Jianhua Ma, Qun Jin

    IEEE Transactions on Industrial Informatics   19 ( 1 ) 570 - 580  2023  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    127
    Citation
    (Scopus)

  • A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images

    Zijing Jiang, Linyan Wang, Yaqi Wang, Gangyong Jia, Guodong Zeng, Jun Wang, Yunxiang Li, Dechao Chen, Guiping Qian, Qun Jin

    IEEE/ACM Transactions on Computational Biology and Bioinformatics   21 ( 4 ) 701 - 714  2022  [Refereed]  [International journal]

    Authorship：Last author

    DOI PubMed

    Scopus

    5
    Citation
    (Scopus)

  • PSARE: A RL-Based Online Participant Selection Scheme Incorporating Area Coverage Ratio and Degree in Mobile Crowdsensing.

    Ying Xu, Yufeng Wang 0001, Jianhua Ma, Qun Jin

    IEEE Transactions on Vehicular Technology   71 ( 10 ) 10923 - 10933  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    15
    Citation
    (Scopus)

  • Earning While Learning: An Adversarial Multi-Armed Bandit Based Real-Time Bidding Scheme in Deregulated Electricity Market.

    Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

    IEEE Transactions on Network Science and Engineering   9 ( 6 ) 3991 - 4000  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.

    Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qun Jin, Lingling Sun, Qianni Zhang, Qisi Lian, Guiping Qian, Neng Xia, Ruizi Peng, Kai Tang, Shuai Wang, Yaqi Wang

    IEEE Journal of Biomedical and Health Informatics   26 ( 4 ) 1684 - 1695  2022  [Refereed]  [International journal]

    DOI PubMed

    Scopus

    29
    Citation
    (Scopus)

  • Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems.

    Xiaokang Zhou, Xuesong Xu, Wei Liang, Zhi Zeng, Shohei Shimizu, Laurence T. Yang, Qun Jin

    IEEE Transactions on Industrial Informatics   18 ( 2 ) 1377 - 1386  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    236
    Citation
    (Scopus)

  • Siamese Neural Network Based Few-Shot Learning for Anomaly Detection in Industrial Cyber-Physical Systems

    Xiaokang Zhou, Wei Liang, Shohei Shimizu, Jianhua Ma, Qun Jin

    IEEE Transactions on Industrial Informatics   17 ( 8 ) 5790 - 5798  2021.08  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    With the increasing population of Industry 4.0, both AI and smart techniques have been applied and become hotly discussed topics in industrial cyber-physical systems (CPS). Intelligent anomaly detection for identifying cyber-physical attacks to guarantee the work efficiency and safety is still a challenging issue, especially when dealing with few labeled data for cyber-physical security protection. In this article, we propose a few-shot learning model with Siamese convolutional neural network (FSL-SCNN), to alleviate the over-fitting issue and enhance the accuracy for intelligent anomaly detection in industrial CPS. A Siamese CNN encoding network is constructed to measure distances of input samples based on their optimized feature representations. A robust cost function design including three specific losses is then proposed to enhance the efficiency of training process. An intelligent anomaly detection algorithm is developed finally. Experiment results based on a fully labeled public dataset and a few labeled dataset demonstrate that our proposed FSL-SCNN can significantly improve false alarm rate (FAR) and F1 scores when detecting intrusion signals for industrial CPS security protection.

    DOI

  • Variational LSTM Enhanced Anomaly Detection for Industrial Big Data

    Xiaokang Zhou, Yiyong Hu, Wei Liang, Jianhua Ma, Qun Jin

    IEEE Transactions on Industrial Informatics   17 ( 5 ) 3469 - 3477  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    With the increasing population of Industry 4.0, industrial big data (IBD) has become a hotly discussed topic in digital and intelligent industry field. The security problem existing in the signal processing on large scale of data stream is still a challenge issue in industrial internet of things, especially when dealing with the high-dimensional anomaly detection for intelligent industrial application. In this article, to mitigate the inconsistency between dimensionality reduction and feature retention in imbalanced IBD, we propose a variational long short-term memory (VLSTM) learning model for intelligent anomaly detection based on reconstructed feature representation. An encoder-decoder neural network associated with a variational reparameterization scheme is designed to learn the low-dimensional feature representation from high-dimensional raw data. Three loss functions are defined and quantified to constrain the reconstructed hidden variable into a more explicit and meaningful form. A lightweight estimation network is then fed with the refined feature representation to identify anomalies in IBD. Experiments using a public IBD dataset named UNSW-NB15 demonstrate that the proposed VLSTM model can efficiently cope with imbalance and high-dimensional issues, and significantly improve the accuracy and reduce the false rate in anomaly detection for IBD according to F1, area under curve (AUC), and false alarm rate (FAR).

    DOI

  • Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN

    Yaqi Wang, Lingling Sun, Qun Jin

    IEEE/ACM Transactions on Computational Biology and Bioinformatics   18 ( 3 ) 951 - 962  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this disease. Computer-aided diagnosis of pneumothorax on chest X-ray, as a prerequisite for a timely cure, has been widely studied, but it is still not satisfactory to achieve highly accurate results. In this paper, an image classification algorithm based on the deep convolutional neural network (DCNN) is proposed for high-resolution medical image analysis of pneumothorax X-rays, which features a Network In Network (NIN) for cleaning the data, random histogram equalization data augmentation processing, and a DCNN. The experimental results indicate that the proposed method can effectively increase the correct diagnosis rate of pneumothorax, and the Area under Curve (AUC) of the test verified in the experiment is 0.9844 on ZJU-2 test data and 0.9906 on the ChestX-ray14, respectively. In addition, a large number of atmospheric pleura samples are visualized and analyzed based on the experimental results and in-depth learning characteristics of the algorithm. The analysis results verify the validity of feature extraction for the network. Combined with the results of these two aspects, the proposed X-ray image processing algorithm can effectively improve the classification accuracy of pneumothorax photographs.

    DOI PubMed

  • CCFS: A Confidence-Based Cost-Effective Feature Selection Scheme for Healthcare Data Classification

    Yiyuan Chen, Yufeng Wang, Liang Cao, Qun Jin

    IEEE/ACM Transactions on Computational Biology and Bioinformatics   18 ( 3 ) 902 - 911  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Feature selection (FS) is one of the fundamental data processing techniques in various machine learning algorithms, especially for classification of healthcare data. However, it is a challenging issue due to the large search space. Binary Particle Swarm Optimization (BPSO) is an efficient evolutionary computation technique, and has been widely used in FS. In this paper, we proposed a Confidence-based and Cost-effective feature selection (CCFS) method using BPSO to improve the performance of healthcare data classification. Specifically, first, CCFS improves search effectiveness by developing a new updating mechanism that designs the feature confidence to explicitly take into account the fine-grained impact of each dimension in the particle on the classification performance. The feature confidence is composed of two measurements: the correlation between feature and categories, and historically selected frequency of each feature. Second, considering the fact that the acquisition costs of different features are naturally different, especially for medical data, and should be fully taken into account in practical applications, besides the classification performance, the feature cost and the feature reduction ratio are comprehensively incorporated into the design of fitness function. The proposed method has been verified in various UCI public datasets and compared with various benchmark schemes. The thoroughly experimental results show the effectiveness of the proposed method, in terms of accuracy and feature selection cost.

    DOI PubMed

  • Guest Editorial: Special Issue on Hybrid Human-Artificial Intelligence for Social Computing.

    Weishan Zhang, Huansheng Ning, Lu Liu 0001, Qun Jin, Vincenzo Piuri

    IEEE Transactions on Computational Social Systems   8 ( 1 ) 118 - 121  2021  [Invited]

    DOI

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    10
    Citation
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  • Guest Editorial: Machine Learning for AI-Enhanced Healthcare and Medical Services: New Development and Promising Solution.

    Ke Yan 0001, Zhiwei Ji, Qun Jin, Qing-Guo Wang

    IEEE/ACM Transactions on Computational Biology and Bioinformatics   18 ( 3 ) 850 - 851  2021

    DOI

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    10
    Citation
    (Scopus)

  • Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-ray Images

    Jingxiong Li, Yaqi Wang, Shuai Wang, Jun Wang, Jun Liu, Qun Jin, Lingling Sun

    IEEE Journal of Biomedical and Health Informatics   25 ( 5 ) 1336 - 1346  2021  [Refereed]  [International journal]  [International coauthorship]

    DOI PubMed

  • Research and Implementation of Chinese Couplet Generation System With Attention Based Transformer Mechanism

    Yufeng Wang, Jiang Zhang, Bo Zhang, Qun Jin

    IEEE Transactions on Computational Social Systems   9 ( 4 ) 1 - 9  2021  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Couplet is a unique art form in Chinese traditional culture. The development of deep neural network (DNN) technology makes it possible for computers to automatically generate couplets. Especially, Transformer is a DNN-based 'Encoder-Decoder' framework, and widely used in natural language processing (NLP). However, the existed Transformer mechanism cannot fully exploit the essential linguistic knowledge in Chinese, including the special format and requirements of Chinese couplets. Therefore, this article adapts the Transformer mechanism to generate meaningful Chinese couplets. Specifically, the contributions of our work are threefold. First, considering the fact that the words in the corresponding positions of the antecedent clause and the subsequent clause in a Chinese couplet always have same part-of-speech (pos, i.e., word class), pos information is intentionally added into the Transformer to improve the accuracy of the conceived couplet. Second, to deal with the large number of unregistered and low-frequency words in Chinese couplet, a specific unregistered/low-frequency word processing mechanism (UWP) is designed and combined with the Transformer model. Third, to further improve the coherence of couplets, we incorporate the polish mechanisms (PMs) into Transformer model. In terms of three evaluation criteria including bilingual evaluation understudy (BLEU), perplexity, and human evaluation, the experimental results demonstrate the effectiveness of our designed Chinese couplet generation system.

    DOI

  • Intelligent Small Object Detection Based on Digital Twinning for Smart Manufacturing in Industrial CPS

    Xiaokang Zhou, Xuesong Xu, Wei Liang, Zhi Zeng, Shohei Shimizu, Laurence T. Yang, Qun Jin

    IEEE Transactions on Industrial Informatics     1 - 1  2021  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    DOI

  • KFRNN: An Effective False Data Injection Attack Detection in Smart Grid Based on Kalman Filter and Recurrent Neural Network

    Yufeng Wang, Zhihao Zhang, Jianhua Ma, Qun Jin

    IEEE Internet of Things Journal   9 ( 9 ) 1 - 1  2021  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    The smart grid is now increasingly dependent on smart devices to operate, which leaves space for cyber attacks. Especially, the intentionally designed false data injection attack (FDIA) can successfully bypass the traditional measurement residual-based bad data detection scheme. Considering that the smart grid data naturally contain linear and nonlinear components, inspired by parallel ensemble learning, especially by the stacking method, this article presents an effective two-level learner-based FDIA detection scheme using the Kalman filter and recurrent neural network (KFRNN). The first level includes two base learners, in which the Kalman filter is used for state prediction to fit linear data, and the recurrent neural network is used to fit the nonlinear data feature. The second-level learner uses the fully connected layer and backpropagation (BP) module to adaptively combine the results of two base learners. Then, through fitting Weibull distribution of the sum of square errors (SSEs) between the observed measurements and the predicted measurements, the dynamic threshold is obtained to judge whether FDIA occurs or not. Comprehensive simulation results show that our scheme has better performance than other neural network-based and ensemble learning-based FDIA detection schemes.

    DOI

  • Academic Influence Aware and Multidimensional Network Analysis for Research Collaboration Navigation Based on Scholarly Big Data

    Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Runhe Huang, Qun Jin

    IEEE Transactions on Emerging Topics in Computing   9 ( 1 ) 246 - 257  2021.01  [Refereed]  [International journal]

    Authorship：Last author, Corresponding author

    DOI

  • Guest Editorial: AI and Machine Learning Solution Cyber Intelligence Technologies: New Methodologies and Applications

    Ke Yan, Lu Liu, Yong Xiang, Qun Jin

    IEEE Transactions on Industrial Informatics   16 ( 10 ) 6626 - 6631  2020.10  [Invited]  [International journal]  [International coauthorship]

    Authorship：Last author

    DOI

  • An Intelligent Dynamic Offloading From Cloud to Edge for Smart IoT Systems With Big Data

    Tian Wang, Yuzhu Liang, Yilin Zhang, Xi Zheng, Muhammad Arif, Jin Wang, Qun Jin

    IEEE Transactions on Network Science and Engineering   7 ( 4 ) 2598 - 2607  2020.10  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author, Corresponding author

    　View Summary

    Intelligent networking and big data analytics are two important pillars for the operation of systems. Edge computing is frequently used in smart IoT systems, particularly in those which cannot be served efficiently through cloud computing due to the limitations in bandwidth, latency and Internet connectivity. However, applications always generate a large amount of data, which are pre-programmed and predefined to run on the cloud or edge platform and can't be changed at run time. The applications may gain better performance if they synergistically run on the cloud and edge platform. In this study, a novel algorithm called Dynamic Switching Algorithm is proposed to ensure intelligent dynamics where all tasks are either offloaded on cloud or edge according to the system's real-time conditions. We further divide applications into four types based on their real-time requirements. Each type of application is set to a reasonable latency to make sure the system to have less processing time. The results demonstrate that our method outperforms two state-of-the-art methods, decreasing both the average delay and energy consumption of offloading by 8.17%~66.90% and 3.76%~78.60% respectively. The experimental evaluations show that the performance of the proposed method could effectively offload tasks in smart IoT systems.

    DOI

  • BciNet: A Biased Contest-Based Crowdsourcing Incentive Mechanism Through Exploiting Social Networks

    Yufeng Wang, Wei Dai, Qun Jin, Jianhua Ma

    IEEE Transactions on Systems, Man, and Cybernetics: Systems   50 ( 8 ) 2926 - 2937  2020.08  [Refereed]  [International journal]  [International coauthorship]

    　View Summary

    Crowdsourcing has proved to be a splendid tool to aggregate the knowledge from a pool of individuals in order to perform abundant microtasks efficiently. Recently, with the explosive growth of online social network, Word of Mouth (WoM)-based crowdsourcing systems have emerged, in which besides conducting the tasks by themselves, participants simultaneously recruit other individuals through exploiting their social networks to help solve crowdsourced tasks. This crowdsourcing paradigm can greatly facilitate to grow the pool of crowdworkers. However, there exist two conflicting challenges in designing an effective WoM-based incentive mechanism: 1) sybil attack and 2) heterogeneous effect of participants. That is, intuitively, incentivizing (usually compensating for) common-ability individuals will inevitably stimulate the behavior of sybil attack (i.e., some individuals create multiple sybils, and split the total efforts into those sybils to expect more compensation). This paper proposes a novel biased contest-based crowdsourcing incentive mechanism through exploiting social networks (BciNet), aiming to balance those two conflicting objectives. BciNet is composed of two phases. First, based on spreading activation model, an enhanced geometric virtual point dissemination mechanism is able to provide sybil-proof property and accommodate the realistic social network structure. Second, based on participants' virtual points, a biased contest gives more reward to less able participants. Through carefully calibrating the bias factor, simulation results based on the real dataset show that BciNet can greatly improve the amount of participants' effort levels, and actually be robust against the sybil attack. In brief, for a practical incentive mechanism, the methodology to address conflicting goals is to put rational individuals into dilemma: to be sybil or not to be, it is the problem, i.e., the potential gain from the sybils in the second phase may be offset by the loss in the first phase.

    DOI

  • Deep-Learning-Enhanced Human Activity Recognition for Internet of Healthcare Things

    Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Hao Wang, Laurence T. Yang, Qun Jin

    IEEE Internet of Things Journal   7 ( 7 ) 6429 - 6438  2020.07  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Along with the advancement of several emerging computing paradigms and technologies, such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of Things (IoT) technologies have been applied in a variety of fields. In particular, the Internet of Healthcare Things (IoHT) is becoming increasingly important in human activity recognition (HAR) due to the rapid development of wearable and mobile devices. In this article, we focus on the deep-learning-enhanced HAR in IoHT environments. A semisupervised deep learning framework is designed and built for more accurate HAR, which efficiently uses and analyzes the weakly labeled sensor data to train the classifier learning model. To better solve the problem of the inadequately labeled sample, an intelligent autolabeling scheme based on deep Q-network (DQN) is developed with a newly designed distance-based reward rule which can improve the learning efficiency in IoT environments. A multisensor based data fusion mechanism is then developed to seamlessly integrate the on-body sensor data, context sensor data, and personal profile data together, and a long short-term memory (LSTM)-based classification method is proposed to identify fine-grained patterns according to the high-level features contextually extracted from the sequential motion data. Finally, experiments and evaluations are conducted to demonstrate the usefulness and effectiveness of the proposed method using real-world data.

    DOI

  • BTR: A Feature-Based Bayesian Task Recommendation Scheme for Crowdsourcing System

    Wei Dai, Yufeng Wang, Jianhua Ma, Qun Jin

    IEEE Transactions on Computational Social Systems   7 ( 3 ) 780 - 789  2020.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    The crowdsourcing system is a distributed problem-solving platform, in which tasks are delivered to the crowd (i.e., crowdworkers) in the form of an open call. Usually, large-scale crowdsourcing systems contain abundant microtasks, and the overhead of a crowdworker spending on searching the appropriate task may be comparable to the cost of completing the task. Therefore, task recommendation is necessary. However, existing work ignores the dynamics in crowdsourcing system, i.e., new tasks continually arrive, which leads to the issues of task cold-start. To overcome the challenge of the new coming task recommendation, this article proposes a feature-based Bayesian task recommendation (BTR) scheme. The key idea to deal with the dynamics of the crowdsourcing system lies in that the BTR learns the latent factor of the task through the task features instead of task ID and then learns the user's preference according to their historical behaviors. Specifically, based on task features and the user's historical behavior records, BTR can not only timely provide crowdworkers with personalized task recommendations but also solve the task cold-start problem. The simulations based on the real crowdsourced data set demonstrate that BTR performs better than other typical schemes that target at recommending the newly arrived tasks to crowdworkers.

    DOI

  • Cyber-Enabled Well-Being Oriented Daily Living Support Based on Personal Data Analysis

    Seiji Kasuya, Xiaokang Zhou, Kiichi Tago, Shoji Nishimura, Qun Jin

    IEEE Transactions on Emerging Topics in Computing   8 ( 2 ) 493 - 502  2020.04  [Refereed]  [International journal]

    Authorship：Last author, Corresponding author

    　View Summary

    We are living in a cyber-physical-social environment with a variety of lifestyles and values. Living support has become important in such a diverse society. Owing to the ability to collect a large amount of personal data or life logs in the cyber-physical-social environment, it is now possible for us to provide living support based on personal data analysis. Moreover, analyzing such data can facilitate a deep understanding of an individual. In this study, we focus on the provision of cyber-enabled well-being oriented daily living support for an individual based on personal data analysis. Three categories of personal data are identified from an individual's daily life data. In this paper, we discuss the basic concept, model, and framework for well-being oriented personal data analysis in order to offer suggestions and advices to improve the living quality of an individual. Finally, we report a feasibility study with an application scenario by using personal and environmental data.

    DOI

  • DNN-DP: Differential privacy enabled deep neural network learning framework for sensitive crowdsourcing data

    Y. Wang, M. Gu, J. Ma, Q. Jin

    IEEE Transactions on Computational Social Systems   7 ( 1 ) 215 - 224  2020.02  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Deep neural network (DNN) learning has witnessed significant applications in various fields, especially for prediction and classification. Frequently, the data used for training are provided by crowdsourcing workers, and the training process may violate their privacy. A qualified prediction model should protect the data privacy in training and classification/prediction phases. To address this issue, we develop a differential privacy (DP)-enabled DNN learning framework, DNN-DP, that intentionally injects noise to the affine transformation of the input data features and provides DP protection for the crowdsourced sensitive training data. Specifically, we correspondingly estimate the importance of each feature related to target categories and follow the principle that less noise is injected into the more important feature to ensure the data utility of the model. Moreover, we design an adaptive coefficient for the added noise to accommodate the heterogeneous feature value ranges. Theoretical analysis proves that DNN-DP preserves ${\varepsilon }$ -differentially private in the computation. Moreover, the simulation based on the US Census data set demonstrates the superiority of our method in predictive accuracy compared with other existing privacy-aware machine learning methods.

    DOI

    Scopus

    31
    Citation
    (Scopus)

  • A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing

    Tian Wang, Guangxue Zhang, Anfeng Liu, Md Zakirul Alam Bhuiyan, Qun Jin

    IEEE Internet of Things Journal   6 ( 3 ) 4831 - 4843  2019.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author, Corresponding author

    　View Summary

    The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT's capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.

    DOI

  • DP3: A Differential Privacy-based Privacy-Preserving Indoor Localization Mechanism

    Y. Wang, M. Huang, Q. Jin, J. Ma

    IEEE Communications Letters   22 ( 12 ) 2547 - 2550  2018.12  [Refereed]  [International journal]  [International coauthorship]

    DOI

    Scopus

    38
    Citation
    (Scopus)

  • Analysis of User Network and Correlation for Community Discovery Based on Topic-Aware Similarity and Behavioral Influence

    Xiaokang Zhou, Bo Wu, Qun Jin

    IEEE Transactions on Human-Machine Systems   48 ( 6 ) 559 - 571  2018.12  [Refereed]  [International journal]

    Authorship：Last author, Corresponding author

    DOI

  • PPRank: Economically Selecting Initial Users for Influence Maximization in Social Networks

    Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

    IEEE SYSTEMS JOURNAL   11 ( 4 ) 2279 - 2290  2017.12  [Refereed]

    　View Summary

    This paper focuses on seeking a new heuristic scheme for an influence maximization problem in social networks: how to economically select a subset of individuals (so-called seeds) to trigger a large cascade of further adoptions of a new behavior based on a contagion process. Most existing works on selection of seeds assumed that the constant number k seeds could be selected, irrespective of the intrinsic property of each individual's different susceptibility of being influenced (e.g., it may be costly to persuade some seeds to adopt a new behavior). In this paper, a price-performance-ratio inspired heuristic scheme, PPRank, is proposed, which investigates how to economically select seeds within a given budget and meanwhile try to maximize the diffusion process. Our paper's contributions are threefold. First, we explicitly characterize each user with two distinct factors: the susceptibility of being influenced (SI) and influential power (IP) representing the ability to actively influence others and formulate users' SIs and IPs according to their social relations, and then, a convex price-demand curve-based model is utilized to properly convert each user's SI into persuasion cost (PC) representing the cost used to successfully make the individual adopt a new behavior. Furthermore, a novel cost-effective selection scheme is proposed, which adopts both the price performance ratio (PC-IP ratio) and user's IP as an integrated selection criterion and meanwhile explicitly takes into account the overlapping effect; finally, simulations using both artificially generated and real-trace network data illustrate that, under the same budgets, PPRank can achieve larger diffusion range than other heuristic and brute-force greedy schemes without taking users' persuasion costs into account.

    DOI

  • Cybersecurity for Cyber-Enabled Multimedia Applications

    Qun Jin, Yong Xiang, Guozi Sun, Yao Liu, Chin-Chen Chang

    IEEE MULTIMEDIA   24 ( 4 ) 10 - 13  2017.10  [Invited]

    Authorship：Lead author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Analyzing Social Roles Based on a Hierarchical Model and Data Mining for Collective Decision-Making Support

    Bo Wu, Xiaokang Zhou, Qun Jin, Fuhua Lin, Henry Leung

    IEEE SYSTEMS JOURNAL   11 ( 1 ) 356 - 365  2017.03  [Refereed]

    Authorship：Corresponding author

    DOI

    Scopus

    21
    Citation
    (Scopus)

  • Enabling the Social Internet of Things and Social Cloud Introduction

    Weishan Zhang, Qun Jin, Didier El Baz

    IEEE CLOUD COMPUTING   2 ( 6 ) 6 - 9  2015.11  [Invited]

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Discovery of Action Patterns and User Correlations in Task-Oriented Processes for Goal-Driven Learning Recommendation

    Xiaokang Zhou, Jian Chen, Bo Wu, Qun Jin

    IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES   7 ( 3 ) 231 - 245  2014.07  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    42
    Citation
    (Scopus)

  • LONET: An Interactive Search Network for Intelligent Lecture Path Generation

    Neil Y. Yen, Timothy K. Shih, Qun Jin

    ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY   4 ( 2 ) 1 - 27  2013.03  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    17
    Citation
    (Scopus)

  • Ranking Metrics and Search Guidance for Learning Object Repository

    Neil Y. Yen, Timothy K. Shih, Louis R. Chao, Qun Jin

    IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES   3 ( 3 ) 250 - 264  2010.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    59
    Citation
    (Scopus)

  • Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI

    Erina Murata, Qun Jin

    IEA/AIE (1)     161 - 172  2026  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

  • Ego-centric multiple-correlation and temporal graph neural networks based residential load forecasting

    Yufeng Wang, Tianxu Han, Lingxiao Rui, Jianhua Ma, Qun jin

    Engineering Applications of Artificial Intelligence    2025.11  [Refereed]

    Authorship：Last author

    DOI

  • TF-MVGNN: an accurate traffic forecasting framework based on spatial-temporal graph neural network through exploiting multiple-view graph construction and learning.

    Haoyuan Cheng, Yufeng Wang 0001, Jianhua Ma 0002, Qun Jin

    Neural Comput. Appl.   37 ( 20 ) 14657 - 14671  2025.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Integrating Acupuncture and Herbal Medicine into Assisted Reproductive Technology: A Systematic Review and Meta-Analysis of East Asian Traditional Medicine

    Xiangping Peng, Bo Wu, Siyu Zhou, Yinghan Xu, Atsushi Ogihara, Shoji Nishimura, Qun Jin, Gerhard Litscher

    Healthcare   13 ( 11 )  2025.06  [Refereed]  [International journal]

    　View Summary

    BACKGROUND: Assisted reproductive technologies (ARTs) are essential in treating infertility but often face limited success due to low implantation and live birth rates. East Asian traditional medicine (EATM), including acupuncture and herbal medicine (HM), may enhance physiological responses during ART cycles. This study evaluated the effectiveness and safety of EATM in improving clinical pregnancy and live birth outcomes in women undergoing ART. METHODS: This review, registered in PROSPERO (CRD42023411712), systematically searched 11 databases up to 31 March 2023. We included randomized controlled trials (RCTs) comparing EATM interventions to control groups. Data extraction and quality assessment were performed independently by two authors. Meta-analysis used the inverse-variance method in Stata 12.0. A total of 37 RCTs involving 10,776 women (aged 29-38) were analyzed. Studies addressed infertility causes including polycystic ovary syndrome, tubal blockage, diminished ovarian reserve, and unexplained infertility. Acupuncture therapies included body, electro-, laser, and auricular acupuncture. Herbal treatments were administered as powders, pills, granules, decoctions, and ointments based on traditional Chinese formulas. RESULTS: EATM interventions were associated with significant improvements in clinical pregnancy and live birth rates. Acupuncture increased clinical pregnancy rates (CPR: RR 1.316, 95% CI 1.171-1.480) and live birth rates (LBR: RR 1.287, 95% CI 1.081-1.533). HM also enhanced CPRs (RR 1.184) and LBRs (RR 1.147). Subgroup analysis showed true acupuncture and HM were more effective than sham or placebo. No significant differences in adverse events were found. CONCLUSIONS: EATM, particularly acupuncture and HM, appears to be a safe and effective complementary therapy that can be used to improve ART outcomes. Future research should focus on developing standardized acupuncture and herbal protocols to optimize integration with ART.

    DOI PubMed

  • Financial risk assessment of imbalanced data based on nonlinear causal time-series network

    Xiaoyang Li, Weimin Li, Xiao Yu, Zhongming Han, Qun Jin

    Information Processing & Management   62 ( 3 ) 104025 - 104025  2025.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Improving Multimodal Sentiment Analysis with Unimodal Pseudo-label Generation

    Jianing Zhao, Ou Deng, Qun Jin

    Lecture Notes in Computer Science     165 - 179  2025.03  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

  • 原発性卵巣機能不全患者に対する鍼治療を用いた体外受精成功の症例報告—Acupuncture-Assisted In Vitro Fertilization in a Patient with Primary Ovarian Insufficiency : A Case Study

    彭 湘萍, 徐 桜晗, 金 群, 西村 昭治, 扇原 淳

    中医臨床 = Clinical journal of traditional Chinese medicine : 使える中医学の総合情報誌   46 ( 1 ) 114 - 119  2025.03  [Refereed]

  • Research on predicting the sleep status of orthopedic pain patients based on machine learning

    Yikang Yu, Yuxi Li, Saboor Saeed, Atsushi Ogihara, Shoji Nishimura, Chao Xu, Guiyuan Lv, Qun Jin

    Clinical Traditional Medicine and Pharmacology    2025.03  [Refereed]

    Authorship：Last author

    DOI

  • Meta-Data-Guided Robust Deep Neural Network Classification with Noisy Label

    Jie Lu, Yufeng Wang, Aiju Shi, Jianhua Ma, Qun Jin

    Applied Sciences    2025.02  [Refereed]

    Authorship：Last author

    DOI

  • Analysis of combined impact of information and emotional content on user engagement based on social media data

    Zhenzhen Xu, Ruichen Cong, Qun Jin

    HCII 2025, Proceedings. Lecture Notes in Computer Science, Springer 2025    2025  [Refereed]

    Authorship：Last author

  • Dynamic Dominate-Modal-aware Model for Multimodal Sentiment Analysis

    Jianing Zhao, Qun Jin

    HCII 2025, Proceedings. Lecture Notes in Computer Science, Springer 2025    2025  [Refereed]

    Authorship：Last author

  • A systematic review and meta-analysis of deep learning and radiomics in predicting MGMT promoter methylation status in glioblastoma: Efficacy, reliability, and clinical implications.

    Yu Chen, Yuehui Liao, Panfei Li, Wei Jin, Jingwan Fang, Junwei Huang, Yaning Feng, Changxiong Xie, Ruipeng Li, Qun Jin, Xiaobo Lai

    Displays   89   103072 - 103072  2025  [Refereed]

    DOI

  • Exploratory and Interpretable Approach to Estimating Latent Health Risk Factors Without Using Domain Knowledge.

    Ruichen Cong, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    Big Data Min. Anal.   8 ( 2 ) 447 - 457  2025  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

  • Exploring multi-granularity contextual semantics for fully inductive knowledge graph completion

    Jingchao Wang, Weimin Li, Alex Munyole Luvembe, Xiao Yu, Xinyi Zhang, Fangyu Liu, Fangfang Liu, Hao Wang, Zhenhai Wang, Qun Jin

    Expert Systems with Applications   260   125407 - 125407  2025.01  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Analyzing Lifestyle and Behavior with Causal Discovery in Health Data from Wearable Devices and Self-Assessments

    Jing Zhang, Ruichen Cong, Ou Deng, Yuxi Li, Keishin Lam, Qun Jin

    2024 IEEE International Conference on E-health Networking, Application & Services (HealthCom)     1 - 6  2024.11  [Refereed]

    Authorship：Last author

    DOI

  • Species-specific model based on sequence and structural information for ubiquitination sites prediction.

    Weimin Li, Nan Chen, Jie Wang, Yin Luo, Huazhong Liu, Jihong Ding, Qun Jin

    Journal of molecular biology   436 ( 22 ) 168781 - 168781  2024.11  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    Ubiquitination is a common post-translational modification of proteins in eukaryotic cells, and it is also a significant method of regulating protein biological function. Computational methods for predicting ubiquitination sites can serve as a cost-effective and time-saving alternative to experimental methods. Existing computational methods often build classifiers based on protein sequence information, physical and chemical properties of amino acids, evolutionary information, and structural parameters. However, structural information about most proteins cannot be found in existing databases directly. The features of proteins differ among species, and some species have small amounts of ubiquitinated proteins. Therefore, it is necessary to develop species-specific models that can be applied to datasets with small sample sizes. To solve these problems, we propose a species-specific model (SSUbi) based on a capsule network, which integrates proteins' sequence and structural information. In this model, the feature extraction module is composed of two sub-modules that extract multi-dimensional features from sequence and structural information respectively. In the submodule, the convolution operation is used to extract encoding dimension features, and the channel attention mechanism is used to extract feature map dimension features. After integrating the multi-dimensional features from both types of information, the species-specific capsule network further converts the features into capsule vectors and classifies species-specific ubiquitination sites. The experimental results show that SSUbi can effectively improve the prediction performance of species with small sample sizes and outperform other models.

    DOI PubMed

    Scopus

    1
    Citation
    (Scopus)

  • Multiple feature selection based on an optimization strategy for causal analysis of health data

    Ruichen Cong, Ou Deng, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    Health Information Science and Systems   12 ( 1 ) 52 - 52  2024.11  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Challenges and Emerging Issues for Generative AI and Hyper Intelligence

    Jianhua Ma, Qun Jin, Hui-Huang Hsu, John Paul C. Vergara, Antonio Guerrieri, Claudio Miceli, Ao Guo

    2024 IEEE Cyber Science and Technology Congress (CyberSciTech)     258 - 265  2024.11  [Refereed]

    DOI

  • Assessing ChatG PT -Generated Comments for Video Content Viewing in Online Learning

    Jiaqi Wang, Jian Chen, Qun Jin

    2024 IEEE Cyber Science and Technology Congress (CyberSciTech)     230 - 237  2024.11  [Refereed]

    Authorship：Last author

    DOI

  • A Two-Stage Depression Recognition Model Based on Improved YOLOv5 and Spatial-Temporal CNN-Transformer Network

    Jianing ZHAO, Qun JIN

    2024 IEEE Cyber Science and Technology Congress (CyberSciTech)     329 - 334  2024.11  [Refereed]

    Authorship：Last author

    DOI

  • Decoupling representation contrastive learning for carbon emission prediction and analysis based on time series

    Xiao Liu, Qunpeng Hu, Jinsong Li, Weimin Li, Tong Liu, Mingjun Xin, Qun Jin

    Applied Energy    2024.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Blinding and blurring the multi-object tracker with adversarial perturbations

    Haibo Pang, Rongqi Ma, Jie Su, Chengming Liu, Yufei Gao, Qun Jin

    Neural Networks   176   106331 - 106331  2024.08  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    Adversarial attack reveals a potential imperfection in deep models that they are susceptible to being tricked by imperceptible perturbations added to images. Recent deep multi-object trackers combine the functionalities of detection and association, rendering attacks on either the detector or the association component an effective means of deception. Existing attacks focus on increasing the frequency of ID switching, which greatly damages tracking stability, but is not enough to make the tracker completely ineffective. To fully explore the potential of adversarial attacks, we propose Blind-Blur Attack (BBA), a novel attack method based on spatio-temporal motion information to fool multi-object trackers. Specifically, a simple but efficient perturbation generator is trained with the blind-blur loss, simultaneously making the target invisible to the tracker and letting the background be regarded as moving targets. We take TraDeS as our main research tracker, and verify our attack method on other excellent algorithms (i.e., CenterTrack, FairMOT, and ByteTrack) on MOT-Challenge benchmark datasets (i.e., MOT16, MOT17, and MOT20). BBA attack reduced the MOTA of TraDeS and ByteTrack from 69.1 and 80.3 to -238.1 and -357.0, respectively, indicating that it is an efficient method with a high degrees of transferability.

    DOI PubMed

    Scopus

    1
    Citation
    (Scopus)

  • ConeE: Global and local context-enhanced embedding for inductive knowledge graph completion

    Jingchao Wang, Weimin Li, Fangfang Liu, Zhenhai Wang, Alex Munyole Luvembe, Qun Jin, Quanke Pan, Fangyu Liu

    Expert Systems with Applications   246   123116 - 123116  2024.07  [Refereed]

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • ECPAS: A Blockchain-based E-Commerce Price Auditing System

    Toshiki Takakubo, Ruidong Li, Haihan Nan, Qun Jin, Zhou Su, Huaming Wu

    ICC 2024 - IEEE International Conference on Communications     1334 - 1339  2024.06  [Refereed]

    DOI

  • Heterogeneous network influence maximization algorithm based on multi-scale propagation strength and repulsive force of propagation field

    Chang Guo, Weimin Li, Jingchao Wang, Xiao Yu, Xiao Liu, Alex Munyole Luvembe, Can Wang, Qun Jin

    Knowledge-Based Systems   291  2024.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    15
    Citation
    (Scopus)

  • LFAS: An electricity load forecasting framework assisted by cooperative multi-task learning-based spike occurrence prediction

    Wei Shi, Yufeng Wang, Jianhua Ma, Qun Jin

    2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)     212 - 217  2024.05  [Refereed]

    Authorship：Last author

    DOI

  • Spatial–Temporal Federated Transfer Learning with multi-sensor data fusion for cooperative positioning

    Xiaokang Zhou, Qiuyue Yang, Qiang Liu, Wei Liang, Kevin Wang, Zhi Liu, Jianhua Ma, Qun Jin

    Information Fusion   105   102182 - 102182  2024.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    78
    Citation
    (Scopus)

  • Preface of special issue on heterogeneous information network embedding and applications.

    Weimin Li 0001, Lu Liu, Kevin I-Kai Wang, Qun Jin

    Future Generation Computer Systems   152   331 - 332  2024.03  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Design of TAM-based framework for credibility and trend analysis in sharing economy: Behavioral intention and user experience on Airbnb as an instance.

    Yenjou Wang, Jason C. Hung, Chun-Hong Huang, Sadiq Hussain, Neil Y. Yen, Qun Jin

    Computer Science and Information Systems   21 ( 2 ) 547 - 568  2024  [Refereed]

    Authorship：Last author

    DOI

  • A locational false data injection attack detection method in smart grid based on adversarial variational autoencoders [Formula presented]

    Yufeng Wang, Yangming Zhou, Jianhua Ma, Qun jin

    Applied Soft Computing   151   111169 - 111169  2024.01  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Influence maximization algorithm based on group trust and local topology structure.

    Chang Guo, Weimin Li, Fangfang Liu, Kexin Zhong, Xing Wu 0001, Yougang Zhao, Qun Jin

    Neurocomputing   564   126936 - 126936  2024.01  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    19
    Citation
    (Scopus)

  • AffinityVAE: A multi-objective model for protein-ligand affinity prediction and drug design.

    Mengying Wang, Weimin Li, Xiao Yu, Yin Luo, Ke Han, Can Wang, Qun Jin

    Computational biology and chemistry   107   107971 - 107971  2023.12  [Refereed]  [International journal]

    Authorship：Last author

    　View Summary

    In the prediction of protein-ligand affinity, the traditional methods require a large amount of computing resources, and have certain limitations in predicting and simulating the structural changes. Although employing data-driven approaches can yield favorable outcomes in deep learning, it entails a lack of interpretability. Some methods may require additional structural information or domain knowledge to support the interpretation, which may limit their applicability. This paper proposes an affinity variational autoencoder (AffinityVAE) using interaction feature mapping and a variational autoencoder, which consists of a multi-objective model capable of end-to-end affinity prediction and drug discovery. In this study, the limitations of affinity prediction in terms of interpretability are tackled by proposing the concept of a protein-ligand interaction feature map. This increases the diversity and quantity of protein-ligand binding data by designing an adaptive autoencoder of target chemical properties to generate new ligands similar to known ligands and adding them to the original training set. AffinityVAE is then retrained using this extended training set to further validate the protein-ligand binding affinity prediction. Comparisons were conducted between the AffinityVAE and recent methods to demonstrate the high efficiency of the proposed model. The experimental results show that AffinityVAE has very high prediction performance, and it has the potential to enhance the diversity and the amount of protein-ligand binding data, which promotes the drug development.

    DOI PubMed

    Scopus

    14
    Citation
    (Scopus)

  • GOMPS: Global Attention-based Ophthalmic Image Measurement and Postoperative Appearance Prediction System.

    Xingru Huang, Zhi Li, Lixia Lou, Ruilong Dan, Lingxiao Chen, Guodong Zeng, Gangyong Jia, Xiaodiao Chen, Qun Jin, Juan Ye, Yaqi Wang

    Expert Syst. Appl.   232   120812 - 120812  2023.12  [Refereed]

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Determining Important Features in Multidimensional Health Data for Individualized Precision Healthcare

    Ruichen Cong, Jianlun Wu, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)     0077 - 0083  2023.11  [Refereed]

    Authorship：Last author

    DOI

  • Dynamic Multi-view Group Preference Learning for group behavior prediction in social networks.

    Weimin Li, Cai Zhang, Xiaokang Zhou, Qun Jin

    Expert Syst. Appl.   231   120553 - 120553  2023.11  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    11
    Citation
    (Scopus)

  • Enabling inductive knowledge graph completion via structure-aware attention network.

    Jingchao Wang, Weimin Li, Wei Liu, Can Wang 0004, Qun Jin

    Applied Intelligence   53 ( 21 ) 25003 - 25027  2023.11  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Hic-KGQA: Improving multi-hop question answering over knowledge graph via hypergraph and inference chain.

    Jingchao Wang, Weimin Li, Fangfang Liu, Bin Sheng, Wei Liu, Qun Jin

    Knowl. Based Syst.   277   110810 - 110810  2023.10  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • A short-term residential load forecasting scheme based on the multiple correlation-temporal graph neural networks.

    Yufeng Wang 0001, Lingxiao Rui, Jianhua Ma, Qun Jin

    Appl. Soft Comput.   146   110629 - 110629  2023.10  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    25
    Citation
    (Scopus)

  • SGNR: A Social Graph Neural Network Based Interactive Recommendation Scheme for E-Commerce

    Dehua Ma, Yufeng Wang, Jianhua Ma, Qun Jin

    Tsinghua Science and Technology   28 ( 4 ) 786 - 798  2023.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    40
    Citation
    (Scopus)

  • A Trustworthy Decentralized System for Health Data Integration and Sharing: Design and Experimental Validation

    Ruichen Cong, Yaping Ye, Jianlun Wu, Yuxi Li, Yuerong Chen, Yishan Bian, Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    Lecture Notes in Computer Science     125 - 134  2023.07  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Rumor source localization in social networks based on infection potential energy.

    Weimin Li, Chang Guo, Yanxia Liu, Xiaokang Zhou, Qun Jin, Mingjun Xin

    Information Sciences   634   172 - 188  2023.07  [Refereed]

    DOI

    Scopus

    32
    Citation
    (Scopus)

  • ADCB: Adaptive Dynamic Clustering of Bandits for Online Recommendation System.

    Yufeng Wang 0001, Weidong Zhang, Jianhua Ma, Qun Jin

    Neural Processing Letters   55 ( 2 ) 1155 - 1172  2023.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks.

    Pasquale De Meo, Qun Jin, Jianguo Yao, Michael Sheng 0001

    CAAI Trans. Intell. Technol.   8 ( 1 ) 1 - 2  2023.03  [Invited]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Behavioral Analysis of Mowing Workers Based on Hilbert–Huang Transform: An Auxiliary Movement Analysis of Manual Mowing on the Slopes of Terraced Rice Fields

    Bo Wu, Yuan Wu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

    Agriculture (Switzerland)   13 ( 2 )  2023.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Message from the DIKW 2023 Chairs: HPCC/DSS/SmartCity/DependSys 2023

    Qun Jin, Yucong Duan, Muhammad Usman Khan, Xiaolong Xu

    Proceedings - 2023 IEEE International Conference on High Performance Computing and Communications, Data Science and Systems, Smart City and Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2023     xxxi  2023

    Authorship：Lead author

    DOI

    Scopus

  • Causal Discovery of Health Features from Wearable Device and Traditional Chinese Medicine Diagnosis Data

    Yuxi Li, Ou Deng, Atsushi Ogihara, Shoji Nishimura, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14055 LNCS   556 - 569  2023  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • FOSA: Full Information Maximum Likelihood (FIML) Optimized Self-Attention Imputation for Missing Data.

    Ou Deng, Qun Jin

    CoRR   abs/2308.12388  2023

    Authorship：Last author

    DOI

  • Policy-Based Reinforcement Learning for Assortative Matching in Human Behavior Modeling.

    Ou Deng, Qun Jin

    HCI (19)   14029 LNCS   378 - 391  2023  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Investigating the Factors to Improve Discrimination of the Desire for Approval in Tweets by Incorporating Dependency Analysis.

    Erina Murata, Kiichi Tago, Qun Jin

    HCI (50)     316 - 325  2023  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Experimental Design and Validation of i-Comments for Online Learning Support.

    Jiaqi Wang, Jian Chen, Qun Jin

    HCI (30)   14040 LNCS   201 - 213  2023  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Multidimensional Data Integration and Analysis for Youth Health Care During the Covid-19 Pandemic.

    Jianlun Wu, Yaping Ye, Yuxi Li, Ruichen Cong, Yishan Bian, Yuerong Chen, Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    HCI (19)   14029 LNCS   154 - 168  2023  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Coevolution modeling of group behavior and opinion based on public opinion perception.

    Weimin Li, Chang Guo, Zhibin Deng, Fangfang Liu, Jianjia Wang, Ruiqiang Guo, Can Wang 0004, Qun Jin

    Knowledge-Based Systems   270   110547 - 110547  2023  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • Artificial intelligence of things (AIoT) data acquisition based on graph neural networks: A systematical review.

    Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

    Concurrency and Computation:Practice and Experience   35 ( 23 )  2023  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • LDP-Fed+: A robust and privacy-preserving federated learning based classification framework enabled by local differential privacy.

    Yufeng Wang 0001, Xu Zhang, Jianhua Ma, Qun Jin

    Concurrency and Computation:Practice and Experience   35 ( 19 )  2023  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Multi-ledger Coordinating Mechanism by Smart Contract for Individual-Initiated Trustworthy Data Sharing.

    Yenjou Wang, Ruichen Cong, Yixiao Liu, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

    HCI (35)     232 - 243  2023  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Effectiveness, Policy, and User Acceptance of COVID-19 Contact-Tracing Apps in the Post–COVID-19 Pandemic Era: Experience and Comparative Study

    Ming Xin Liu, Si Yu Zhou, Qun Jin, Shoji Nishimura, Atsushi Ogihara

    JMIR Public Health and Surveillance   8 ( 10 ) e40233  2022.10  [Refereed]  [International journal]

    DOI PubMed

    Scopus

    8
    Citation
    (Scopus)

  • i-Comments: On-screen Individualized Comments for Online Learning Support

    Jiaqi Wang, Jian Chen, Qun Jin

    2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)     1 - 5  2022.09  [Refereed]

    Authorship：Last author

    DOI

  • Design of a Vision Blind Spot Detection System Based on Depth Camera

    Zijun Wang, Qun Jin, Bo Wu

    2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)     1 - 5  2022.09  [Refereed]

    DOI

  • Preface

    Qun Jin, Chin Chen Chang

    ACM International Conference Proceeding Series     V - VI  2022.07  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • Analysis on the Subdivision of Skilled Mowing Movements on Slopes

    Bo Wu, Yuan Wu, Shoji Nishimura, Qun Jin

    Sensors   22 ( 4 ) 1372 - 1372  2022.02  [Refereed]  [International journal]

    Authorship：Last author

    DOI PubMed

    Scopus

    9
    Citation
    (Scopus)

  • CAN: Effective cross features by global attention mechanism and neural network for ad click prediction

    Wenjie Cai, Yufeng Wang, Jianhua Ma, Qun Jin

    Tsinghua Science and Technology   27 ( 1 ) 186 - 195  2022.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    21
    Citation
    (Scopus)

  • Message from the General Chairs: ITME 2022

    Xiaobo You, Qun Jin, Hong Liu, Xiansheng Liu

    Proceedings - 2022 12th International Conference on Information Technology in Medicine and Education, ITME 2022     XXIII  2022  [Invited]

    DOI

    Scopus

  • Policy-Based Reinforcement Learning for Assortative Matching in Human Behavior Modeling.

    Ou Deng, Qun Jin

    CoRR   abs/2211.03936  2022

    Authorship：Last author

    DOI

  • CDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound.

    Ruilong Dan, Yunxiang Li, Yijie Wang, Gangyong Jia, Ruiquan Ge, Juan Ye, Qun Jin, Yaqi Wang

    CoRR   abs/2206.08524  2022

    　View Summary

    Precise and rapid categorization of images in the B-scan ultrasound modality
    is vital for diagnosing ocular diseases. Nevertheless, distinguishing various
    diseases in ultrasound still challenges experienced ophthalmologists. Thus a
    novel contrastive disentangled network (CDNet) is developed in this work,
    aiming to tackle the fine-grained image categorization (FGIC) challenges of
    ocular abnormalities in ultrasound images, including intraocular tumor (IOT),
    retinal detachment (RD), posterior scleral staphyloma (PSS), and vitreous
    hemorrhage (VH). Three essential components of CDNet are the weakly-supervised
    lesion localization module (WSLL), contrastive multi-zoom (CMZ) strategy, and
    hyperspherical contrastive disentangled loss (HCD-Loss), respectively. These
    components facilitate feature disentanglement for fine-grained recognition in
    both the input and output aspects. The proposed CDNet is validated on our ZJU
    Ocular Ultrasound Dataset (ZJUOUSD), consisting of 5213 samples. Furthermore,
    the generalization ability of CDNet is validated on two public and widely-used
    chest X-ray FGIC benchmarks. Quantitative and qualitative results demonstrate
    the efficacy of our proposed CDNet, which achieves state-of-the-art performance
    in the FGIC task. Code is available at:
    https://github.com/ZeroOneGame/CDNet-for-OUS-FGIC .

    DOI

  • An effective model-free Gaussian Process based online social media recommendation.

    Jiawei Xu, Yufeng Wang 0001, Jianhua Ma, Qun Jin

    2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)(iThings/GreenCom/CPSCom/SmartData/Cybermatics)     374 - 378  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • MARV: Multi-task learning and Attention based Rumor Verification scheme for Social Media.

    Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

    IEEE/CIC International Conference on Communications in China(ICCC)     94 - 98  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • An Extendable Sentiment Monitoring Model for SNS Considering Environmental Factors.

    Yenjou Wang, Neil Y. Yen, Qun Jin

    Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference   13315 LNCS   408 - 421  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Linguistic and Contextual Analysis of SNS Posts for Approval Desire.

    Erina Murata, Kiichi Tago, Qun Jin

    Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference   13315 LNCS   332 - 344  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Analyzing Change on Emotion Scores of Tweets Before and After Machine Translation.

    Karin Fukuda, Qun Jin

    Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference   13315 LNCS   294 - 308  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Analysis on the Effect of Living Habits and Environment to Concentration.

    Yukai Gu, Qun Jin

    HCI International 2022 Posters - 24th International Conference on Human-Computer Interaction   1581 CCIS   129 - 136  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Improving Emotional Confusions in SNS Sentiment Analysis by Partial Redistribution of BERT Discrimination Results.

    Yenjou Wang, Qun Jin

    Big Data Analytics in Astronomy, Science, and Engineering - 10th International Conference on Big Data Analytics   13830 LNCS   199 - 210  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Measurement and verification of cognitive load in multimedia presentation using an eye tracker.

    Ruichen Cong, Kiichi Tago, Qun Jin

    Multimedia Tools and Applications   81 ( 19 ) 26821 - 26835  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • QAPP: A quality-aware and privacy-preserving medical image release scheme.

    Xu Zhang, Yufeng Wang 0001, Jianhua Ma, Qun Jin

    Information Fusion   88   281 - 295  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • SSPA: an effective semi-supervised peer assessment method for large scale MOOCs.

    Yufeng Wang 0001, Hui Fang, Qun Jin, Jianhua Ma

    Interactive Learning Environments   30 ( 1 ) 158 - 176  2022  [Refereed]

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • F-SWIR: Rumor Fick-spreading model considering fusion information decay in social networks.

    Weimin Li, Dingmei Wei, Xiaokang Zhou, Shaohua Li, Qun Jin

    Concurrency and Computation: Practice and Experience   34 ( 22 )  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    11
    Citation
    (Scopus)

  • Modeling social network behavior spread based on group cohesion under uncertain environment.

    Weimin Li, Zhibin Deng, Xiaokang Zhou, Qun Jin, Bin Sheng

    Concurrency and Computation: Practice and Experience   34 ( 21 )  2022  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Secure Interoperation of Blockchain and IPFS Through Client Application Enabled by CP-ABE.

    Ruichen Cong, Yixiao Liu, Yenjou Wang, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

    HCI (32)   13333 LNCS   30 - 41  2022  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Pre-braking behaviors analysis based on hilbert–huang transform

    Bo Wu, Yishui Zhu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

    CCF Transactions on Pervasive Computing and Interaction   5 ( 2 ) 157 - 182  2022  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Measurement and quantification of an individual's feelings for a place in personal data analysis

    Seiji Kasuya, Kiichi Tago, Qun Jin

    Human Behavior and Emerging Technologies   3 ( 5 ) 739 - 749  2021.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Analysis on Falling Risk of Elderly Workers when Mowing on a Slope via Motion Capture

    Bo Wu, Yuan Wu, Shoji Nishimura, Qun Jin

    2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)     890 - 895  2021.10  [Refereed]

    Authorship：Last author

    DOI

  • An Short-Term Residential Load Forecasting Scheme Using Multi-Task Learning

    Yu Feng Wang, Can Bin Xiao, Yan Chen, Qun Jin

    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications   44 ( 3 ) 47 - 52  2021.06  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Individual-Initiated Auditable Access Control for Privacy-Preserved IoT Data Sharing with Blockchain

    Ruichen Cong, Yixiao Liu, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

    2021 IEEE International Conference on Communications Workshops (ICC Workshops)     1 - 6  2021.06  [Refereed]

    Authorship：Last author

    DOI

  • Evolutionary community discovery in dynamic social networks via resistance distance

    Weimin Li, Heng Zhu, Shaohua Li, Hao Wang, Hongning Dai, Can Wang, Qun Jin

    Expert Systems with Applications   171   114536 - 114536  2021.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author, Corresponding author

    　View Summary

    Traditional social community discovery methods concentrate mainly on static social networks, but the analysis of dynamic networks is a prerequisite for real-time and personalized social services. Through the study of community changes, the community structure in a dynamic network can be tracked over time, which helps in the mining of dynamic network information. In this paper, we propose a method of tracking dynamic community evolution that is based on resistance distance. Specifically, we model the time-varying features of dynamic networks using the convergence of a resistance-based distance. In our model, the heterogeneity of neighboring nodes can be obtained in the local topology of nodes by analyzing the resistance distance between nodes. We design a community discovery algorithm that essentially discovers community structures on dynamic networks by identifying the so-called core node. During the process of community evolution analysis, both the dynamic contribution of ordinary nodes and core nodes in each community are considered. In addition, to avoid the inclusion of spurious communities in the community structure, we define the notion of noise community and account for it in our algorithm. Experimental results show that the method proposed in this paper can yield better accuracy than other existing methods.

    DOI

    Scopus

    27
    Citation
    (Scopus)

  • Improving Diagnosis Estimation by Considering the Periodic Span of the Life Cycle Based on Personal Health Data

    Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

    Big Data Research   23   100176 - 100176  2021.02  [Refereed]  [International journal]

    Authorship：Last author, Corresponding author

    　View Summary

    With the surge in popularity of wearable devices, collection of personal health data has become quite easy. Many studies have been conducted using health data to estimate the onset and progression of illness. However, life habits may vary among individuals. By analyzing the life cycle from health-related data, conventional studies may be improved. This study proposes a new approach to improving diagnosis estimation by considering the life cycle analyzed from health-related data. The periodic span of the life cycle is estimated via autocorrelation analysis. In the range of the periodic span, dimension reduction for health data is performed by principal component analysis, and health features are extracted and used for diagnosis estimation. In our experiment, we used personal health data and pulse diagnosis data collected by a traditional Chinese medicine doctor. Using six multi-label classification methods, we verified that a combination of pulse and health features could improve the accuracy of diagnosis estimation compared with that using only pulse features.

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Analysis of the Conversations on Twitter regarding HPV Vaccine

    Daisuke Suzuki, Shoji Nishimura, Qun Jin, Atsushi Ogihara

    Journal of Consumer Health on the Internet   25 ( 4 ) 397 - 406  2021  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Dispensed Transformer Network for Unsupervised Domain Adaptation.

    Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou 0001, Qun Jin, Li Wang, Yaqi Wang

    CoRR   abs/2110.14944  2021

    　View Summary

    Accurate segmentation is a crucial step in medical image analysis and
    applying supervised machine learning to segment the organs or lesions has been
    substantiated effective. However, it is costly to perform data annotation that
    provides ground truth labels for training the supervised algorithms, and the
    high variance of data that comes from different domains tends to severely
    degrade system performance over cross-site or cross-modality datasets. To
    mitigate this problem, a novel unsupervised domain adaptation (UDA) method
    named dispensed Transformer network (DTNet) is introduced in this paper. Our
    novel DTNet contains three modules. First, a dispensed residual transformer
    block is designed, which realizes global attention by dispensed interleaving
    operation and deals with the excessive computational cost and GPU memory usage
    of the Transformer. Second, a multi-scale consistency regularization is
    proposed to alleviate the loss of details in the low-resolution output for
    better feature alignment. Finally, a feature ranking discriminator is
    introduced to automatically assign different weights to domain-gap features to
    lessen the feature distribution distance, reducing the performance shift of two
    domains. The proposed method is evaluated on large fluorescein angiography (FA)
    retinal nonperfusion (RNP) cross-site dataset with 676 images and a wide used
    cross-modality dataset from the MM-WHS challenge. Extensive results demonstrate
    that our proposed network achieves the best performance in comparison with
    several state-of-the-art techniques.

  • GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation.

    Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

    CoRR   abs/2109.14813  2021

  • Anatomy-Guided Parallel Bottleneck Transformer Network for Automated Evaluation of Root Canal Therapy.

    Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qianni Zhang, Qun Jin, Lingling Sun, Qisi Lian, Neng Xia, Ruizi Peng, Kai Tang, Yaqi Wang, Shuai Wang

    CoRR   abs/2105.00381  2021

  • An Extended Epidemic Model on Interconnected Networks for COVID-19 to Explore the Epidemic Dynamics.

    Ou Deng, Kiichi Tago, Qun Jin

    CoRR   abs/2104.04695  2021

    Authorship：Last author

    　View Summary

    COVID-19 has resulted in a public health global crisis. The pandemic control
    necessitates epidemic models that capture the trends and impacts on infectious
    individuals. Many exciting models can implement this but they lack practical
    interpretability. This study combines the epidemiological and network theories
    and proposes a framework with causal interpretability in response to this
    issue. This framework consists of an extended epidemic model in interconnected
    networks and a dynamic structure that has major human mobility. The networked
    causal analysis focuses on the stochastic processing mechanism. It highlights
    the social infectivity as the intervention estimator between the observable
    effect (the number of daily new cases) and unobservable causes (the number of
    infectious persons). According to an experiment on the dataset for Tokyo
    metropolitan areas, the computational results indicate the propagation features
    of the symptomatic and asymptomatic infectious persons. These new
    spatiotemporal findings can be beneficial for policy decision making.

  • DAST: An aggregation scheme for crowdsensed indoor data exploiting sequential long-tail features.

    Yawen Zhong, Yichen Guo, Yufeng Wang 0001, Qun Jin

    IEEE Wireless Communications and Networking Conference Workshops     1 - 6  2021  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation.

    Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

    Machine Learning in Medical Imaging - 12th International Workshop(MLMI@MICCAI)   12966 LNCS   386 - 395  2021  [Refereed]

    DOI

    Scopus

    60
    Citation
    (Scopus)

  • VFAT: A Personalized HAR Scheme Through Exploiting Virtual Feature Adaptation Based on Transfer Learning.

    Xiao Li 0014, Yufeng Wang 0001, Jianhua Ma, Qun Jin

    19th IEEE International Conference on Embedded and Ubiquitous Computing(EUC)     1 - 8  2021  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Front-End Framework Selection Assistance System with Customizable Quantification Indicators Based on Analysis of Repository and Community Data.

    Koichi Kiyokawa, Qun Jin

    Big-Data-Analytics in Astronomy, Science, and Engineering - 9th International Conference on Big Data Analytics   13167 LNCS   41 - 55  2021  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • A Position and Area Localization Algorithm for Obstacles in the Environment of Sparsely-Deployed Sensors.

    Zhigang Gao, Xiaowei Yang, Bo Wu 0007, Huijuan Lu, Jianhui Zhang, Wenjie Diao, Qun Jin

    IEEE Access   9   39884 - 39896  2021  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Analyzing eye-movements of drivers with different experiences when making a turn

    Bo Wu, Shoji Nishimura, Qun Jin, Yishui Zhu

    Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020     502 - 507  2020.12  [Refereed]

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • The effect of eye movements and cultural factors on product color selection

    Bo Wu, Yishui Zhu, Keping Yu, Shoji Nishimura, Qun Jin

    Human-centric Computing and Information Sciences   10 ( 1 )  2020.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    18
    Citation
    (Scopus)

  • RV-ML: An Effective Rumor Verification Scheme Based on Multi-Task Learning Model

    Qian Lv, Yufeng Wang, Bo Zhang, Qun Jin

    IEEE Communications Letters   24 ( 11 ) 2527 - 2531  2020.11  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Analyzing Pre-braking Behaviors of Drivers with Varying Experience

    Bo Wu, Shoji Nishimura, Qun Jin, Yishui Zhu

    Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020     284 - 289  2020.08  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Personalized real-time movie recommendation system: Practical prototype and evaluation

    Jiang Zhang, Yufeng Wang, Zhiyuan Yuan, Qun Jin

    Tsinghua Science and Technology   25 ( 2 ) 180 - 191  2020.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    78
    Citation
    (Scopus)

  • Three-hop velocity attenuation propagation model for influence maximization in social networks

    Weimin Li, Yuting Fan, Jun Mo, Wei Liu, Can Wang, Minjun Xin, Qun Jin

    World Wide Web   23 ( 2 ) 1261 - 1273  2020.03  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    21
    Citation
    (Scopus)

  • Improved Cascade R-CNN for Medical Images of Pulmonary Nodules Detection Combining Dilated HRNet

    Shihuai Xu, Huijuan Lu, Minchao Ye, Ke Yan, Wenjie Zhu, Qun Jin

    ACM International Conference Proceeding Series     283 - 288  2020.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Modified Hybrid Task Cascade for Lung Nodules Segmentation in CT Images with Guided Anchoring

    Shihuai Xu, Huijuan Lu, Minchao Ye, Ke Yan, Wenjie Zhu, Qun Jin

    ACM International Conference Proceeding Series     433 - 438  2020.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Applying of Adaptive Threshold Non-maximum Suppression to Pneumonia Detection

    Hao Teng, Huijuan Lu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

    Communications in Computer and Information Science   1160 CCIS   518 - 528  2020  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • IEEE access special section editorial: Proximity service (prose) challenges and applications

    Yufeng Wang, Qun Jin, Jianhua Ma, Klimis Ntalianis, M. D. Zakirul Alam Bhuiyan, Michele Luvisotto

    IEEE Access   8   169106 - 169109  2020  [Invited]

    DOI

    Scopus

  • Analyzing the Effects of Driving Experience on Prebraking Behaviors Based on Data Collected by Motion Capture Devices

    Bo Wu, Yishui Zhu, Shoji Nishimura, Qun Jin

    IEEE Access   8   197337 - 197351  2020  [Refereed]

    Authorship：Last author

    DOI

  • Detection of Health Abnormality Considering Latent Factors Inducing a Disease

    Kiichi Tago, Kosuke Takagi, Qun Jin

    IEEE Access   8   139433 - 139443  2020  [Refereed]  [International journal]

    Authorship：Last author, Corresponding author

    　View Summary

    Underlying latent factors may cause a person to feel unwell. As the influence of the latent factors increases, the person will become sick. It is difficult to directly measure the influence of latent factors on risk degrees. However, early symptoms of a disease may affect vital signs such as body temperature and blood pressure, which may be a result of the influence of the latent factors. Deep learning is often used to predict the onset of a disease owing to its high accuracy. However, the reliability of this method is limited because of its characteristics of a black-box model. In this study, we propose a new approach to detect health abnormality. We regard the degree of influence of latent factors as the risk of disease and detect health abnormality before the onset of the disease. In our approach, we used a combination of Structural Equation Modeling (SEM) and Hidden Markov Model (HMM). First, in SEM, a domain model was created, and the factor score was estimated based on the relationship between latent factors and the explicit variables influenced by the factors. Thereafter, risk degrees were quantified with HMM using the estimated factor scores, and abnormality was identified in terms of risk degree. Finally, our proposed method was compared with three baselines: PCA (principal component analysis)-based approach, deep learning, and no-degree estimation methods. The average recall of our method was 98.75%, almost the same as the baselines, and false positive rate (FPR) was 0.186%, lower than the baselines. In the five-fold cross-validation comparing with no-degree estimation method, the average accuracy and recall of our method were 99.7% and 98.3% respectively, and FPR was 0.045%, all much better than the baseline. Moreover, our approach can make the process of obtaining the result visible and help detect abnormality sensitively by setting the threshold according to the risk degree, which can contribute to early detection of a disease and improve the reliability of abnormality detection as well.

    DOI

  • Learning misclassification costs for imbalanced classification on gene expression data

    Huijuan Lu, Yige Xu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

    BMC Bioinformatics   20 ( Suppl 25 ) 681 - 681  2019.12  [Refereed]  [International journal]

    Authorship：Last author

    DOI PubMed

    Scopus

    33
    Citation
    (Scopus)

  • Classification of TCM pulse diagnoses based on pulse and periodic features from personal health data

    K. Tago, H. Wang, Q. Jin

    Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM)    2019.12  [Refereed]

    Authorship：Last author, Corresponding author

    　View Summary

    (accepted)

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • Guest Editorial: Special Issue on Human-Centric Cyber Social Computing

    Qun Jin, Weimin Li, Song Guo, Sethuraman Panchanathan

    IEEE Transactions on Computational Social Systems   6 ( 5 ) 1038 - 1040  2019.10  [Invited]

    Authorship：Lead author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Visualization design based on personal health data and persona analysis

    Zhi Li, Qun Jin

    Proceedings - IEEE 17th International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, DASC-PiCom-CBDCom-CyberSciTech 2019     201 - 206  2019.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Improved mask R-CNN for lung nodule segmentation

    Huanlan Yan, Huijuan Lu, Minchao Ye, Ke Yan, Yige Xu, Qun Jin

    Proceedings - 10th International Conference on Information Technology in Medicine and Education, ITME 2019     137 - 141  2019.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    18
    Citation
    (Scopus)

  • Culture-based Color Influence Paths Analysis by Using Eye-tracking Devices

    B. Wu, S. Nishimura, Y. Zhu, Q. Jin

    Proc.CyberSciTech2019 (IEEE Cyber Science and Technology), Fukuoka, Japan     66 - 71  2019.08  [Refereed]  [International coauthorship]

    Authorship：Last author

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Polarity classification of tweets considering the poster's emotional change by a combination of Naive Bayes and LSTM

    K. Tago, K.Takagi, Q. Jin

    Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science   11619   579 - 588  2019.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • An efficient location recommendation scheme based on clustering and data fusion

    W. Cai, Y. Wang, R. Lv, Q. Jin

    Computers & Electrical Engineering (Elsevier)   77 ( 2019 ) 289 - 299  2019.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • User role identification based on social behavior and networking analysis for information dissemination

    X. Zhou, B. Wu, Q. Jin

    Future Generation Computer Systems (Elsevier)   96   639 - 648  2019.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    28
    Citation
    (Scopus)

  • BRIM: An accurate electricity spot price prediction scheme-based bidirectional recurrent neural network and integrated market

    Yiyuan Chen, Yufeng Wang, Jianhua Ma, Qun Jin

    Energies   12 ( 11 ) 2241 - 2241  2019.06  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    30
    Citation
    (Scopus)

  • A Distributed Intelligent Hungarian Algorithm for Workload Balance in Sensor-Cloud Systems Based on Urban Fog Computing

    J. Jiang, Y. Long, Y. Mei, T. Wang, Q. Jin

    IEEE Access   7   77649 - 77658  2019.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author, Corresponding author

    　View Summary

    With the help of fog computing, urban computing and intelligence novel systems can be created to improve the urban environment and the quality of human life. Sensor-cloud systems based on urban fog computing (SCS-UFC) are new intelligent network systems, which combine a cloud platform with wireless sensor networks (WSNs) as well as fog nodes to provide functions such as sensing, computation, and storage of large-scale data. Since the sensor nodes in WSNs only have limited transmission capacity, they cannot transmit their data to the cloud platform directly. Therefore, fog nodes with stronger transmission capacity are deployed to relay the data from WSNs to the cloud platform. However, different fog nodes may be burdened with different workloads (i.e., amounts of data): usually, the fog nodes with heavier workloads mean longer transmission delay and more energy consumption. If a fog node exhausts its energy, it will die and then make the network cease to work. Therefore, it is necessary to balance the workload of all fog nodes so as to reduce transmission delay and energy consumption of the sensors. However, addressing the problem is challenging because each fog node only knows local information of its neighbors, and thus it is difficult to get a global optimization result by itself. In this paper, a distributed intelligent algorithm based on the Hungarian method is proposed. First, each fog node collects the information connected with its neighboring fog nodes that are located within its transmission range. Then, a new genetic algorithm is designed to find an approximate optimization solution. Finally, each fog node decides if it should forward parts of its workload to other fog nodes so that the workloads of all fog nodes are balanced. Simulation results show that our algorithm can achieve shorter delay and less energy consumption than existing works.

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • An accurate false data detection in smart grid based on residual recurrent neural network and adaptive threshold

    Yufeng Wang, Wanjiao Shi, Qun Jin, Jianhua Ma

    Proceedings - IEEE International Conference on Energy Internet, ICEI 2019     499 - 504  2019.05  [Refereed]

    DOI

    Scopus

    20
    Citation
    (Scopus)

  • Human–computer cooperation for future computing

    Byeong Seok Shin, Houcine Hassan, Qun Jin

    Journal of Supercomputing   75 ( 4 ) 1747 - 1750  2019.04  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • Experiment Design and Analysis of Cross-cultural Variation in Color Preferences Using Eye-tracking

    B. Wu, S. Nishimura, Y. Zhu, Q. Jin

    Proc.MUE2019 (The 13th International Conference on Multimedia and Ubiquitous Engineering), Xi’an, China   590   44 - 49  2019.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Analysis of health changes and the association of health indicators in the elderly using TCM pulse diagnosis assisted with ICT devices: a time series study

    S. Zhou, S. Nishimura, A. Ogihara, Q. Jin

    European Journal of Integrative Medicine (Elsevier)   27   105 - 113  2019.04  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • An improved SSO algorithm for cyber-enabled tumor risk analysis based on gene selection

    C. Ye, J. Pan, Q. Jin

    Future Generation Computer Systems (Elsevier)   89   407 - 418  2019.03  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Design of a computational model for social learning support and analytics

    N.Y. Yen, J.C. Hung, C.C. Chen, Q. Jin

    Computers in Human Behavior (Elsevier)   92   547 - 561  2019.03  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Conventional online learning typically allows an instructor to deliver instruction to students via a predefined curriculum and within a fixed knowledge structure (i.e., explaining the instructional subject). With the dramatic growth of social media technology and correlated data aggregation, some sort of instant knowledge is obtained by daily users. An emerging type of knowledge (i.e., social knowledge) has been identified and may lead to self-paced learning from social networks, which is simply defined as social learning. This article points out three important issues for social learning, namely, knowledge retrieval via temporal social factors, and the connection between social network and the knowledge domain. Two significant automation mechanisms, lecture generation for self-regulated learning and influencing domain computation for opportunity finding, are suggested to facilitate the process of social learning. A prototype system based on Elgg was implemented, sourced by a federated repository that has stored and shared more than 1.5 millions transactions (e.g., content, interactions, etc.). We conclude that timely social knowledge (or crowdsourcing results) can be widely applied in the next era of online learning environment. Findings through the statistical analysis are prospective to support understanding of phenomenon of social learning and design of future learning platform for followup researchers.

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Self-Adaptive Process Mining Algorithm Based on Information Entropy to Deal with Uncertain Data

    Weimin Li, Yuting Fan, Wei Liu, Minjun Xin, Hao Wang, Qun Jin

    IEEE Access   7   131681 - 131691  2019  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Random convolutional neural network based on distributed computing with decentralized architecture

    Yige Xu, Huijuan Lu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   11956 LNCS   504 - 510  2019  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Personalization Recommendation Algorithm Based on Trust Correlation Degree and Matrix Factorization

    Weimin Li, Xiaokang Zhou, Shohei Shimizu, Mingjun Xin, Jiulei Jiang, Honghao Gao, Qun Jin

    IEEE Access   7   45451 - 45459  2019  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author, Corresponding author

    　View Summary

    The rapid development of the Internet of Things (IoT) and e-commerce has brought a lot of convenience to people's lives. IoT applications generate a large number of services and user data. It is necessary to design a personalized recommendation technology suitable for the users of IoT services and improve the user experience. In this paper, a recommendation algorithm with trusted relevance combined with matrix factorization is proposed. By establishing an effective trust metric model, the user's social information is integrated into the recommendation algorithm. First, the social network concentric hierarchical model is used to consider the direct or indirect trust relationship, and more trust information is integrated for the matrix factorization recommendation algorithm. Then, we design the trust relevance, comprehensively considering the trust factors and interest similar factors. Our experiments were performed on the Dianping datasets. The recommendation algorithm using matrix factorization and trusted relevance degree has higher prediction accuracy than the basic matrix decomposition and social matrix factorization in terms of accuracy and stability.

    DOI

  • Emerging Privacy Issues and Solutions in Cyber-Enabled Sharing Services: From Multiple Perspectives

    K. Yan, W. Shen, Q. Jin, H. Lu

    IEEE Access   7   26031 - 26059  2019  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Corresponding author

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • Message from the ITME 2018 General Chairs

    Qun Jin, Ning Jin, Enrico Haemmerle

    Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018     xxviii  2018.12  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • An Effective Feature Selection Scheme for Healthcare Data Classification Using Binary Particle Swarm Optimization

    Yiyuan Chen, Yufeng Wang, Liang Cao, Qun Jin

    Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018     703 - 707  2018.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    18
    Citation
    (Scopus)

  • Correlation Analysis of Health and Traditional Chinese Medicine (TCM) Pulse Diagnosis for the Elderly Using Wearable Devices

    Siyu Zhou, Atsushi Ogihara, Shoji Nishimura, Qun Jin

    Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018     745 - 749  2018.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • An undergraduate curriculum model for intelligence science and technology

    Jingde Cheng, Runhe Huang, Qun Jin, Jianhua Ma, Yi Pan

    Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018     234 - 239  2018.12  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Welcome message from the IEEE IoP 2018 general chairs

    Guojun Wang, Hakim Mabed, Qun Jin, Bin Guo, Fuhua Oscar Lin

    Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018     xciii  2018.12  [Invited]

    DOI

    Scopus

  • TNERec: Topic-aware network embedding for scientific collaborator recommendation

    Xiangjie Kong, Mengyi Mao, Jiaying Liu, Bo Xu, Ruihe Huang, Qun Jin

    Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018     1007 - 1014  2018.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    15
    Citation
    (Scopus)

  • DNN-Based image classification for software GUI testing

    Huijuan Lu, Li Wang, Minchao Ye, Ke Yan, Qun Jin

    Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018     1818 - 1823  2018.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Vote Parallel SVM: An extension of parallel support vector machine

    Yan Song, Qun Jin, Ke Yan, Huijuan Lu, Julong Pan

    Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018     1942 - 1947  2018.12  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Modeling of cross-disciplinary collaboration for potential field discovery and recommendation based on scholarly big data

    Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Xuesong Xu, Qun Jin

    Future Generation Computer Systems   87   591 - 600  2018.10  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    43
    Citation
    (Scopus)

  • An Anti-Noise Process Mining Algorithm Based on Minimum Spanning Tree Clustering

    Li Weimin, Zhu Heng, Liu Wei, Chen Dehua, Jiang Jiulei, Jin Qun

    IEEE ACCESS   6   48756 - 48764  2018.10  [Refereed]  [International journal]  [International coauthorship]

    Authorship：Last author

    　View Summary

    Many human-centric systems have begun to use business process management technology in production. With the operation of business process management systems, more and more business process logs and human-centric data have been accumulated. However, the effective utilization and analysis of these event logs are challenges that people need to solve urgently. Process mining technology is a branch of business process management technology. It can extract process knowledge from event logs and build process models, which helps to detect and improve business processes. The current process mining algorithms are inadequate in dealing with log noise. The family of alpha-algorithms ignores the impact of noise, which is unrealistic in real-life logs. Most of the process mining algorithms that can handle noise also lack reasonable denoising thresholds. In this paper, a new assumption on noise is given. Furthermore, an anti-noise process mining algorithm that can deal with noise is proposed. The decision rules of the selective, parallel, and non-free choice structures are also given. The proposed algorithm framework discovers the process model and transforms it into a Petri network representation. We calculate the distance between traces to build the minimum spanning tree on which clusters are generated. The traces of the non-largest clusters are treated as noise, and the largest cluster is mined. Finally, the algorithm can discover the regular routing structure and solve the problem of noise. The experimental results show the correctness of the algorithm when compared with the α ++ algorithm.

    DOI

    Scopus

    18
    Citation
    (Scopus)

  • Special Issue on Trends and Research Issues of Emerging Technologies to Enhance Learning

    Yin Chengjiu, Yen Neil, Jin Qun

    INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES   16 ( 4 )  2018.10  [Invited]

    Authorship：Last author

  • Experiment and Analysis on Visual Field and Fixation when Going Upstairs and Downstairs

    B. Wu, S. Nishimura, Q. Jin

    Proc. ITME2018 (9th International Conference on Information Technology in Medicine and Education)     163 - 167  2018.10  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • GCHAR: An efficient Group-based Context—aware human activity recognition on smartphone

    Liang Cao, Yufeng Wang, Bo Zhang, Qun Jin, Athanasios V. Vasilakos

    Journal of Parallel and Distributed Computing   118   67 - 80  2018.08  [Refereed]

    　View Summary

    With smartphones increasingly becoming ubiquitous and being equipped with various sensors, nowadays, there is a trend towards implementing HAR (Human Activity Recognition) algorithms and applications on smartphones, including health monitoring, self-managing system and fitness tracking. However, one of the main issues of the existing HAR schemes is that the classification accuracy is relatively low, and in order to improve the accuracy, high computation overhead is needed. In this paper, an efficient Group-based Context-aware classification method for human activity recognition on smartphones, GCHAR is proposed, which exploits hierarchical group-based scheme to improve the classification efficiency, and reduces the classification error through context awareness rather than the intensive computation. Specifically, GCHAR designs the two-level hierarchical classification structure, i.e., inter-group and inner-group, and utilizes the previous state and transition logic (so-called context awareness) to detect the transitions among activity groups. In comparison with other popular classifiers such as RandomTree, Bagging, J48, BayesNet, KNN and Decision Table, thorough experiments on the realistic dataset (UCI HAR repository) demonstrate that GCHAR achieves the best classification accuracy, reaching 94.1636%, and time consumption in training stage of GCHAR is four times shorter than the simple Decision Table and is decreased by 72.21% in classification stage in comparison with BayesNet.

    DOI

    Scopus

    134
    Citation
    (Scopus)

  • An Optimized trust model integrated with linear features for cyber-enabled recommendation services

    Weimin Li, Jun Mo, Minjun Xin, Qun Jin

    Journal of Parallel and Distributed Computing   118   81 - 88  2018.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    11
    Citation
    (Scopus)

  • A Novel Personalized Recommendation Algorithm Based on Trust Relevancy Degree

    W. Li, H. Zhu, X. Zhou, S. Shimizu, M. Xin, Q. Jin

    Proc. CyberSciTech 2018 (2018 IEEE Cyber Science and Technology Congress)     418 - 422  2018.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • TSP: Truthful Grading-Based Strategyproof Peer Selection for MOOCs

    Yufeng Wang, Hui Fang, Chonghu Cheng, Qun Jin

    Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018     679 - 684  2018.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • PDL: An Efficient Prediction-Based False Data Injection Attack Detection and Location in Smart Grid

    Wanjiao Shi, Yufeng Wang, Qun Jin, Jianhua Ma

    Proceedings - International Computer Software and Applications Conference   2   676 - 681  2018.06  [Refereed]

    DOI

    Scopus

    23
    Citation
    (Scopus)

  • BLE Mesh: A Practical Mesh Networking Development Framework for Public Safety Communications

    Zhang Bo, Wang Yufeng, Wei Li, Jin Qun, Vasilakos Athanasios V

    TSINGHUA SCIENCE AND TECHNOLOGY   23 ( 3 ) 333 - 346  2018.06  [Refereed]

    　View Summary

    Owing to advanced storage and communication capabilities today, smart devices have become the basic interface between individuals and their surrounding environment. In particular, massive devices connect to one other directly in a proximity area, thereby enabling abundant Proximity Services (ProSe), which can be classified into two categories: public safety communication and social discovery. However, two challenges impede the quick development and deployment of ProSe applications. From the viewpoint of networking, no multi-hop connectivity functionality component can be directly operated on commercially off-the-shelf devices, and from the programming viewpoint, an easily reusable development framework is lacking for developers with minimal knowledge of the underlying communication technologies and connectivity. Considering these two issues, this paper makes a twofold contribution. First, a multi-hop mesh networking based on Bluetooth Low Energy (BLE) is implemented, in which a proactive routing mechanism with link-quality (i.e., received signal strength indication) assistance is designed. Second, a ProSe development framework called BLE Mesh is designed and implemented, which can provide significant benefits for application developers, framework maintenance professionals, and end users. Rich application programming interfaces can help developers to build ProSe apps easily and quickly. Dependency inversion principle and template method pattern allow modules in BLE Mesh to be loosely coupled and easy to maintain and update. Callback mechanism enables modules to work smoothly together and automation processes such as registration, node discovery, and messaging are employed to offer nearly zero-configuration for end users. Finally, based on the designed ProSe development kit, a public safety communications app called QuoteSendApp is built to distribute emergency information in close area without Internet access. The process illustrates the easy usability of BLE Mesh to develop ProSe apps.

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • Analyzing influence of emotional tweets on user relationships using Naive Bayes and dependency parsing

    Kiichi Tago, Kosuke Takagi, Seiji Kasuya, Qun Jin

    World Wide Web   22 ( 3 ) 1 - 16  2018.05  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    13
    Citation
    (Scopus)

  • Special issue on communication and computation cooperation (3C): Principles, algorithms and systems

    Kezhi Wang, Qun Jin, Hamid Sharif

    International Journal of Communication Systems   31 ( 7 )  2018.05  [Invited]

    DOI

    Scopus

  • Analyzing the changes of health condition and social capital of elderly people using wearable devices

    Zhou Siyu, Ogihara Atsushi, Nishimura Shoji, Jin Qun

    HEALTH INFORMATION SCIENCE AND SYSTEMS   6 ( 1 ) 4 - 4  2018.04  [Refereed]  [International journal]

    Authorship：Last author

    DOI PubMed

    Scopus

    27
    Citation
    (Scopus)

  • Special issue on "Advances in human-like intelligence towards next-generation web"

    Yen Neil, Hsu Ching-Hsien, Jin Qun, Kao Odej

    NEUROCOMPUTING   279   1 - 2  2018.03  [Invited]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Optimization modeling and analysis of trustworthiness determination strategies for service discovery of MSNP

    Xixi Ma, Qun Jin, Julong Pan, Yufeng Wang

    Journal of Supercomputing   75 ( 4 ) 1 - 17  2018.02  [Refereed]

    Authorship：Corresponding author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Geo-QTI: A quality aware truthful incentive mechanism for cyber–physical enabled Geographic crowdsensing

    Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

    Future Generation Computer Systems   79   447 - 459  2018.02  [Refereed]

    　View Summary

    Nowadays, the cyber, social and physical worlds are increasingly integrating and merging. Especially, combining the strengths of humans and machines helps tackle increasing hard tasks that neither can be done alone. Following this trend, this paper designs a Quality aware Truthful Incentive mechanism for cyber–physical enabled Geographic crowdsensing called Geo-QTI. Different from existing work, Geo-QTI appropriately accommodates the utilities of various stakeholders: requesters, participants and the crowdsourcing platform, and explicitly takes the requesters’ quality requirements, and participants’ quality provision into account. Geo-QTI explicitly includes four components: requester selection, participant selection, pricing and allocation. Requester selection with feasible analysis removes the requesters whose job cannot be completed by all participants or suffers from the monopoly participant (without the participant's contribution, others cannot cover requesters’ requirement), obtains winning requesters set and determines actual payments. In participant selection phase, the platform aggregates the requested tasks (submitted by all winning requesters) in the sensed geographic area, and chooses the appropriate participants satisfying the winning requesters’ quality requirements with total cost as low as possible. Pricing phase determines the payments to winning participants. The phase of allocation assigns the specific participants to minimally cover the quality requirements of those winning requesters. Rigid theoretical analysis demonstrates Geo-QTI can achieve both requesters’ and participants’ individual rationality and truthfulness, computational efficiency and budget balance for the platform. Furthermore, the extensive simulations confirm our theoretical analysis, and illustrate that Geo-QTI can reduce requesters’ expenses greatly and ensure the fairness of allocation.

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Overlap community detection using spectral algorithm based on node convergence degree

    Weimin Li, Shu Jiang, Qun Jin

    Future Generation Computer Systems   79   408 - 416  2018.02  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    30
    Citation
    (Scopus)

  • Influence analysis of emotional behaviors and user relationships based on Twitter data

    Kiichi Tago, Qun Jin

    Tsinghua Science and Technology   23 ( 1 ) 104 - 113  2018.02  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    34
    Citation
    (Scopus)

  • RankwithTA: A robust and accurate peer grading mechanism for MOOCs

    Hui Fang, Yufeng Wang, Qun Jin, Jianhua Ma

    Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017   2018-   497 - 502  2018.01  [Refereed]

    　View Summary

    Massive Online Open Courses (MOOCs) have the potential to revolutionize higher education with their wide outreach and accessibility. One of key challenges in MOOCs is the student evaluation: The large number of students makes it infeasible for instructors or teaching assistants (TAs) to grade all assignments. Peer grading-having students assess each other-is a promising approach to tackling the problem of evaluation at scale. The user evaluations are then used directly, or aggregated into a consensus value. However, lacking an incentive scheme, users have no motive in making effort in completing the evaluations, providing inaccurate answers instead. To address the above issues, we propose and implement a peer grading scheme, RankwithTA. Specifically, considering that the quality of a student determines both her performance in the assignment and her grading ability, RankwithTA makes the grade each student received depend on both the quality of the solution they submitted, and on the quality of their review and grading work to incentivize students' correct grading, Furthermore, the ground truth is incorporated, which utilizes external calibration by having some students graded by instructors or TAs to provide a basis for accuracy. The simulation results illustrate that RankwithTA performs better than the existing schemes.

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Learning misclassification costs for imbalanced datasets, application in gene expression data classification

    Huijuan Lu, Yige Xu, Minchao Ye, Ke Yan, Qun Jin, Zhigang Gao

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   10954 LNCS   513 - 519  2018  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Analysis of pulse diagnosis data from a TCM doctor and a device by Random Forest

    K. Tago, A. Ogihara, S. Nishimura, Q. Jin

    Kojima K., Sakamoto M., Mineshima K., Satoh K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer Science, Springer   11717   74 - 80  2018  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Detection of Anomaly Health Data by Specifying Latent Factors with SEM and Estimating Hidden States with HMM

    K. Tago, Q. Jin

    Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education     137 - 141  2018  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • i-Blockchain: A Blockchain-Empowered Individual-Centric Framework for Privacy-Preserved Use of Personal Health Data

    K. Ito, K. Tago, Q. Jin

    Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education     829 - 833  2018  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    30
    Citation
    (Scopus)

  • Extraction of Factors Related to Transportations and Destinations by Decision Trees for Personal Whereabouts Modeling

    S. Kasuya, K. Tago, Q. Jin

    Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education     808 - 812  2018  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Comparison of measurements by the betweenness centrality and subjective experiment on the word priority of Tweets

    K. Takagi, K. Tago, K. Ito, Q. Jin

    Proceedings of the 4th IEEE International Conference on Internet of People     1936 - 1941  2018  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Specifying Latent Factors with a Domain Model for Personal Data Analysis

    K. Tago, K. Takagi, K. Ito, Q. Jin

    Proceedings of the 3rd IEEE Cyber Science and Technology Congress (CyberSciTech)     1 - 6  2018  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Analysis of Health and Physiological Index Based on Sleep and Walking Steps by Wearable Devices for the Elderly

    Siyu Zhou, Atsushi Ogihara, Shoji Nishimura, Qun Jin

    Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017   2017-   245 - 250  2017.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Trust-Aware Recommendation for E-Commerce Associated with Social Networks

    Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

    Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017   2017-   211 - 216  2017.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Analyzing Influence of Emotional Tweets on User Relationships by Naive Bayes Classification and Statistical Tests

    Kiichi Tago, Qun Jin

    Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017   2017-   217 - 222  2017.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A data intensive heuristic approach to the two-stage streaming scheduling problem

    Wei Liang, Chunhua Hu, Min Wu, Qun Jin

    JOURNAL OF COMPUTER AND SYSTEM SCIENCES   89   64 - 79  2017.11  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Highly-skilled heath care workers exhibit tacit knowledge and advanced skills for preventing disordered swallowing and aspiration pneumonia in their patients

    Nao Ueda, Manabu Yamaji, Moyuan Li, Kohei Matsushita, Qun Jin, Shoji Nishimura, Atsushi Ogihara

    INTERNATIONAL JOURNAL OF ANTIMICROBIAL AGENTS   50   S159 - S159  2017.11  [Refereed]

  • ActiRecognizer: Design and Implementation of a Real-Time Human Activity Recognition System

    Liang Cao, Yufeng Wang, Qun Jin, Jianhua Ma

    2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)   2018-January   266 - 271  2017.10  [Refereed]  [International coauthorship]

    　View Summary

    In our society, inadequate physical activity is one of severe problems issues for human health, which may increase the health risks of many diseases. Nowadays, smartphones are ubiquitous and widely used around the world, in which multi-functional sensors and wireless interfaces are embedded. Therefore, smartphone is viewed as an appropriate platform for real-time activity recognition to address these healthy problems by monitoring and detecting user's everyday activities. In this paper, unlike other wearable devices based applications (e.g., watches, bands, or clip-on devices), ActiRecognizer, a smartphone-based prototype of a real-time human activity recognition (HAR) is designed and implemented, in which a detailed activity report of individuals (i.e. a pie chart containing the proportion and duration of each activity) can be correspondingly generated based on the detected real-time activities. Specifically, ActiRecognizer adopts client/server (C/S) architecture. At client side, smartphone associated with each individual periodically uploads the accelerometer and gyroscope sensing data to server for activity recognition and monitoring. At serve side, HAR is composed of offline training phase and online activity recognition phase: In training phase, sensing data are collected to extract the desired features that can appropriately characterize behaviors, classification model is generated utilizing these features, and then the trained classification model is used to classify user activity in real time. Finally, detailed activity reports and statistics are available to the user via a secure web interface.

    DOI

  • Recommendation for Cross-Disciplinary Collaboration Based on Potential Research Field Discovery

    Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

    Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017     349 - 354  2017.09  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • ABT: An Effective Ability-Balanced Team Based Incentive Mechanism in Crowdsourcing System

    Yufeng Wang, Jie Huang, Qun Jin, Jianhua Ma

    Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017     220 - 225  2017.09  [Refereed]

    　View Summary

    Crowdsourcing systems which rely on a great deal of crowdworkers to perform large quantities of microtasks, have been leveraged in a variety of applications. There are two factors affecting the productive output of each crowdworker. One is skill level, which is private information to each crowdworker, and another is her variable expended effort. In this paper, we construct and analyze a total-Ability-balanced team based incentive mechanism ABT, which can stimulate the strategic crowdworkers to truthfully report their ability levels, and according to crowdworkers' ability levels, form the competing teams. Specifically, a crowdworker with a certain skill level, is askedto choose a specificskill level (i.e., denoted as an ability threshold), and a basic payment scheme is designed to incentivize the crowdworker to truthfully report her ability level. Then, according to the chosen ability thresholds, crowdworkers are organized into total ability balanced teams to earn extra team bonus, which can further motivate crowdworkers to exert more efforts. Compared to team formation process where workers are randomly assigned to the same-scale teams and the pay per task model, our scheme ABT can improve the work efficiency.

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Device-to-Device based mobile social networking in proximity (MSNP) on smartphones: Framework, challenges and prototype

    Yufeng Wang, Li Wei, Athanasios V. Vasilakos, Qun Jin

    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE   74   241 - 253  2017.09  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    32
    Citation
    (Scopus)

  • A hybrid feature selection algorithm for gene expression data classification

    Huijuan Lu, Junying Chen, Ke Yan, Qun Jin, Yu Xue, Zhigang Gao

    NEUROCOMPUTING   256   56 - 62  2017.09  [Refereed]

    　View Summary

    In the DNA microarray research field, the increasing sample size and feature dimension of the gene expression data prompt the development of an efficient and robust feature selection algorithm for gene expression data classification. In this study, we propose a hybrid feature selection algorithm that combines the mutual information maximization (MIM) and the adaptive genetic algorithm (AGA). Experimental results show that the proposing MIMAGA-Selection method significantly reduces the dimension of gene expression data and removes the redundancies for classification. The reduced gene expression dataset provides highest classification accuracy compared to conventional feature selection algorithms. We also apply four different classifiers to the reduced dataset to demonstrate the robustness of the proposed MIMAGA-Selection algorithm. (C) 2017 Elsevier B.V. All rights reserved.

    DOI

    Scopus

    330
    Citation
    (Scopus)

  • Health concerns: Self-disclosure and online behavior analysis

    Ting Wang, Guangyu Piao, Julong Pan, Qun Jin

    Proceedings - 2016 8th International Conference on Information Technology in Medicine and Education, ITME 2016     182 - 186  2017.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Message from the GreenCom-2017 General Chair

    Rubem Pereira, Geyong Min, Qun Jin

    Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017   2018-January   xxvii  2017.07  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • Preface

    Juhong Christie Liu, Shoji Nishimura, Hai Zhang, Qun Jin

    Proceedings - 6th International Conference of Educational Innovation Through Technology, EITT 2017   2018-March   xiii  2017.07  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • Social recommendation based on trust and influence in SNS environments

    Weimin Li, Zhengbo Ye, Minjun Xin, Qun Jin

    MULTIMEDIA TOOLS AND APPLICATIONS   76 ( 9 ) 11585 - 11602  2017.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • A heuristic approach to discovering user correlations from organized social stream data

    Xiaokang Zhou, Qun Jin

    MULTIMEDIA TOOLS AND APPLICATIONS   76 ( 9 ) 11487 - 11507  2017.05  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    35
    Citation
    (Scopus)

  • ELR-DC: An Efficient Recommendation Scheme for Location Based Social Networks

    Ruheng Lv, Yufeng Wang, Qun Jin, Jianhua Ma

    Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016     567 - 572  2017.05  [Refereed]

    　View Summary

    Location-based social networks (LBSNs) have recently attracted millions of mobile users to share their locations and location-related contents. With the increasing use of LBSNs, an efficient personalized recommendation service is required to recommend appropriate point of interests (POIs) to users. Traditional collaborative filtering (CF) based recommendation algorithms need go through all users in LBSN to recommend locations to the target user. Due to the fact that many users are irrelevant to the target user, these approaches perform poorly in accuracy and scalability. In this paper, we propose an Efficient Location Recommendation scheme based on Discrete particle swarm optimization (DPSO) and Collaborative filtering, called ELR-DC. This scheme efficiently detects communities with close internal ties and then conducts location recommendation in each community. Specifically, a similarity network among users is firstly constructed based on their check-in activities, which explicitly takes into account users' similarities of interest and active regions. Then, an improved merging DPSO algorithm (IMDPSO) is proposed to detect communities through utilizing the formed similarity network. Then, in each community, CF algorithm is applied to recommend Top-N locations to each user. Finally, we conduct a comprehensive performance evaluation on a large-scale datasets collected from Gowalla. Experimental results show that the proposed scheme have the superiority of the precision and efficiency over the existed CF algorithms.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • SmartFDS: Design and Implementation of Falling Detection System on Smartphones

    Xiao Li, Yufeng Wang, Qicai Zhou, Qun Jin

    Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016     402 - 405  2017.05  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Message from the CIT 2016 program chairs

    Jiannong Cao, Qun Jin, Xiaodong Lin, Vincenzo Piuri

    Proceedings - 2016 16th IEEE International Conference on Computer and Information Technology, CIT 2016, 2016 6th International Symposium on Cloud and Service Computing, IEEE SC2 2016 and 2016 International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2016     xv - xix  2017.03  [Invited]

    DOI

    Scopus

  • Mobile crowdsourcing: framework, challenges, and solutions

    Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE   29 ( 3 )  2017.02  [Refereed]

    　View Summary

    Crowdsourcing is the generalized act of outsourcing tasks, traditionally performed by an employee or contractor, to a large group of Internet population through an open call. With the great development of smartphones with rich built-in sensors and multiple ratio interfaces, mixing smartphone-based mobile technologies and crowdsourcing offers significant flexibilities and leads to a new paradigm called mobile crowdsourcing (MCS), which can be fully explored for real-time and location-sensitive crowdsourced tasks. In this paper, we present a taxonomy for the MCS applications, which are explicitly divided as using human as sensors, and exploiting the wisdom of crowd (i.e., human intelligence). Moreover, two paradigms for mobilizing users in MCS are outlined: direct mode and word of mouth mode. A comprehensive MCS framework and typical workflow of MCS applications are proposed, which consist of nine functional modules, pertaining to three stakeholders in MCS: crowdsourcer, crowdworkers, and crowdsourcing platform. Then, we elaborate the MCS challenges including task management, incentives, security and privacy, and quality control, and summarize the corresponding solutions. Especially, from the viewpoints of various stakeholders, we propose the desired properties that an ideal MCS system should satisfy. The primary goal of this paper is to comprehensively classify and provide a summary on MCS framework, challenges, and possible solutions to highlight the MCS related research topics and facilitate to develop and deploy interesting MCS applications. Copyright (C) 2016 John Wiley & Sons, Ltd.

    DOI

    Scopus

    56
    Citation
    (Scopus)

  • Analyzing of research patterns based on a temporal tracking and assessing model

    Wei Liang, Qun Jin, Zixian Lu, Min Wu, Chunhua Hu

    PERSONAL AND UBIQUITOUS COMPUTING   20 ( 6 ) 933 - 946  2016.11  [Refereed]

    　View Summary

    Scientific research works conducted by researchers spread all over the world in every research field, which are hard to be tracked and quantified. Although there are many research works focused on scientific community discovery and researcher profiling, it is still a big challenge to track the research patterns and assess the research development for an individual researcher or a research group over time. In this study, we seek to model researchers' scientific activities and quantify their outcome during their research career. A temporal tracking and assessing model is introduced to represent the research development and quantify the scientific outcome for both an individual and a group along the time. Based on our model, a research topic analyzing approach is developed to extract the topics covered by a research group for the research pattern analysis. Furthermore, a latent research pattern discovering approach is proposed to depict how a research group's research works contributed by its members are discovered and visualized. The effectiveness of our approach is evaluated based on a real academic dataset.

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • QuaCentive: a quality-aware incentive mechanism in mobile crowdsourced sensing (MCS)

    Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

    JOURNAL OF SUPERCOMPUTING   72 ( 8 ) 2924 - 2941  2016.08  [Refereed]

    　View Summary

    Today's smartphones with a rich set of cheap powerful embedded sensors can offer a variety of novel and efficient ways to opportunistically collect data, and enable numerous mobile crowdsourced sensing (MCS) applications. Basically, incentive is one of fundamental issues in MCS. Through appropriately integrating three popular incentive methods: reverse auction, reputation and gamification, this paper proposes a quality-aware incentive framework for MCS, QuaCentive, which, pertaining to all components in MCS, can motivate crowd to provide high-quality sensed contents, stimulate crowdsourcers to give truthful feedback about quality of sensed contents, and make platform profitable. Specifically, first, we utilize the reverse auction and reputation mechanisms to incentivize crowd to truthfully bid for sensing tasks, and then provide high-quality sensed contents. Second, in to encourage crowdsourcers to provide truthful feedbacks about quality of sensed data, in QuaCentive, the verification of those feedbacks are crowdsourced in gamification way. Finally, we theoretically illustrate that QuaCentive satisfies the following properties: individual rationality, cost-truthfulness for crowd, feedback-truthfulness for crowdsourcers, platform profitability.

    DOI

    Scopus

    37
    Citation
    (Scopus)

  • Message from the IoP 2015 leading chairs

    Qun Jin, Lu Liu, Jianxin Li

    Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015     xl  2016.07  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • Modeling and analyzing of Research topic evolution associated with social networks of researchers

    Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

    International Journal of Distributed Systems and Technologies   7 ( 3 ) 42 - 62  2016.07  [Refereed]

    　View Summary

    Research trends keep evolving along the time with certain trackable patterns. Mining academic literature and discovering the latent research trends evolution is an interesting and important problem. Few of previous studies focusing on academic topic evolution modeling have addressed the temporal topic evolution patterns. In addition, researchers' profile and their social networks are valuable complementary to the research trends tracking. In this study, to analyze the underlying research trends evolution along with the scientific collaborations of researchers, a novel temporal research trends evolution model associated with researchers' social networks is proposed and built. Specifically, the detected research topics are classified into different clusters in each timeslot, and the evolution patterns are deduced among these topic clusters. The effectiveness of our approach is evaluated based on a real academic dataset. The experimental results can help users to discover the major research trends for specific fields. Besides, the tracked statuses of the corresponding scientific groups are helpful for searching research trends or finding collaboration opportunities according to researchers' different requirements.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Energy-efficient localization and tracking on smartphones: Design principle and solutions

    Yufeng Wang, Yuanting Bu, Qun Jin, Athanasios V. Vasilakos

    ACM International Conference Proceeding Series   15-17-   29 - 35  2016.06  [Refereed]

    　View Summary

    In recent years, various location based services (LBS) have witnessed great development and are being prevalently used in our life. However, as the foundation of various LBS applications, localization consumes large energy of resource-constraint mobile terminals, especially on smartphones. This paper explicitly proposes three technical principles, substitution, adaption and collaboration to guide energy-efficient localization and tracking schemes on smartphones. Then several typical schemes in indoor or outdoor environments are respectively summarized and compared under the umbrella of those three principles. Moreover, the context-Assisting techniques are also discussed to design energy-efficient LBS applications. Finally, the quantitative metrics to measure the tradeoff between energy and localization performance are summarized. The primary goal of this paper is to comprehensively classify and provide a summary on the sporadic localization schemes (with energy-efficiency as main concern), possible solutions and tradeoffs, and facilitate to develop and deploy the energy-efficient LBS applications.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • An Integrated Incentive Framework for Mobile Crowdsourced Sensing

    Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

    TSINGHUA SCIENCE AND TECHNOLOGY   21 ( 2 ) 146 - 156  2016.04  [Refereed]

    　View Summary

    Currently, mobile devices (e.g., smartphones) are equipped with multiple wireless interfaces and rich built-in functional sensors that possess powerful computation and communication capabilities, and enable numerous Mobile Crowdsourced Sensing (MCS) applications. Generally, an MCS system is composed of three components: a publisher of sensing tasks, crowd participants who complete the crowdsourced tasks for some kinds of rewards, and the crowdsourcing platform that facilitates the interaction between publishers and crowd participants. Incentives are a fundamental issue in MCS. This paper proposes an integrated incentive framework for MCS, which appropriately utilizes three widely used incentive methods: reverse auction, gamification, and reputation updating. Firstly, a reverse-auction-based two-round participant selection mechanism is proposed to incentivize crowds to actively participate and provide high-quality sensing data. Secondly, in order to avoid untruthful publisher feedback about sensing-data quality, a gamification-based verification mechanism is designed to evaluate the truthfulness of the publisher's feedback. Finally, the platform updates the reputation of both participants and publishers based on their corresponding behaviors. This integrated incentive mechanism can motivate participants to provide high-quality sensed contents, stimulate publishers to give truthful feedback, and make the platform profitable.

    DOI

    Scopus

    26
    Citation
    (Scopus)

  • Special Issue on Mobile Social Networking and computing in Proximity (MSNP)

    Yufeng Wang, Qun Jin, Athanasios V. Vasilakos

    JOURNAL OF COMPUTER AND SYSTEM SCIENCES   82 ( 1 ) 91 - 92  2016.02  [Invited]

    DOI

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    2
    Citation
    (Scopus)

  • Gradually adaptive recommendation based on semantic mapping of users′ interest correlations

    Jian Chen, Xiaokang Zhou, Qun Jin

    International Journal of Communication Systems   29 ( 2 ) 341 - 361  2016.01  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Security and Privacy Mechanisms for Sensor Middleware and Application in Internet of Things (IoT)

    Namje Park, Hongxin Hu, Qun Jin

    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS   2016 ( 1 ) 2965438 - 2965438  2016  [Invited]

    Authorship：Last author

    DOI

    Scopus

    23
    Citation
    (Scopus)

  • A Framework of Personal Data Analytics for Well-Being Oriented Life Support

    Seiji Kasuya, Xiaokang Zhou, Shoji Nishimura, Qun Jin

    ADVANCED MULTIMEDIA AND UBIQUITOUS ENGINEERING: FUTURE INFORMATION TECHNOLOGY, VOL 2   354   443 - 449  2016  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Perspectives on Cyber Science and Technology for Cyberization and Cyber-enabled Worlds

    Jianhua Ma, Kim-Kwang Raymond Choo, Hui-Huang Hsu, Qun Jin, William Liu, Kevin Wang, Yufeng Wang, Xiaokang Zhou

    2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC     1 - 9  2016  [Refereed]

    　View Summary

    Cyberization, as a new big trend following computerization and informatization, is the process of forming a new cyberworld and transforming our current physical, social and mental worlds into novel cyber-combined worlds. Cyber science, responding to the cyberization trend, aims to create a new collection of knowledge about these cyber-enabled worlds, and provide a way of discovering what is in the cyber-enabled worlds and how they work. Cyber science is concerned with the study of phenomena caused or generated by the cyberworld and cyberphysical, cyber-social and cyber-mental worlds, as well as the complex intertwined integration of cyber physical, social and mental worlds. It fuels advances in cyber technology, beyond the existing cyber related technologies. In this paper, after discussing the cyberization background and process, and explaining cyber science and technology, we present our visions and perspectives on new opportunities, essential issues and major challenges for cyber science and technology. We further describe cyber related technologies and closely related existing research areas, and envision future research directions, in terms of cyber physical, cyber social, cyber life, cyber intelligence and cyber security, which are five basic dimensions of cyber science and technology.

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • Personal Data Analytics to Facilitate Cyber Individual Modeling

    Xiaokang Zhou, Bo Wu, Qun Jin, Jianhua Ma, Weimin Li, Neil Y. Yen

    2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC     39 - 46  2016  [Refereed]

    　View Summary

    The high development of emerging computing paradigms, such as Ubiquitous Computing, Mobile Computing, and Social Computing, has brought us a big change from all walks of our work, life, learning and entertainment. Especially, with the high accessibility of social networking services along with the increasingly pervasive use of portable wireless mobile computing devices, more and more populations have been engaged into this kind of integration of real physical world and cyber digital space, which can be called the hyper world. To help people live better in the highly developed information society, the so-called cyber-individual (Cyber-I), which is far beyond a user model or a software agent to assist a user, has been proposed to provide the most comprehensive digital entities for its corresponding Real-I in terms of the individual's experience, behavior, and thinking as well as his or her birth, growth, and death. In this study, we concentrate on the personal data analytics to facilitate the cyber individual modeling. Organic Stream is introduced to systematically organize and refine the personal stream data, which can help improve the data processing and management in the CI-Spine tier and CI-Pivot tier of Cyber-I. The DSUN (Dynamically Socialized User Networking) model is employed to better utilize the collective intelligence from a group of users, which can help improve the CI-Mind tier to make Cyber-I to become more robust. Based on these, we discuss the functional modules for the facilitation of cyber individual modeling. Finally, a scenario is given, and the experimental results are presented to demonstrate that the valuable outcomes from the personal analysis can be utilized to enrich the Cyber-I, and provide users with more suitable services.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Message forwarding strategies in Device-to-Device based mobile social networking in proximity (MSNP)

    Yufeng Wang, Jiabing Chen, Qun Jin, Jianhua Ma

    2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC     69 - 74  2016  [Refereed]

    　View Summary

    Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones. Message forwarding/data routing in MSNP relies on the movement of individuals and their encounter opportunities to relay data to the destination, so-called store-carry-forward (SCF) mode. Due to lacking continuous network connectivity and must handle dynamic topology, message forwarding mechanism in MSNP is challenging. In recent years, exploiting MSNP users' social behaviours to forward message, have drawn tremendous interests. In this paper, we provide the taxonomy of social behaviour-based forwarding strategies, comprehensively summarize and compare various schemes, including location-based and encounter-based (further divided into social property based and community-based) strategies. Location-based strategies forward data to the individuals geographically closer to the destination, while encounter-based strategies forward data to the users more socially active through considering human interactions. Then, we present open issues in MSNP forwarding strategies and their potential solutions. The goal of this work is to provide deep understanding on SCF based message forwarding in MSNP which properly incorporate the individual's social characteristics, and bring new visions to MSNP research and applications.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Overlap Community Detection Based On Node Convergence Degree

    Weimin Li, Shu Jiang, HuaiKou Miao, Xiaokang Zhou, Qun Jin

    2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC     163 - 167  2016  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Personal Data Analytics for Well-Being Oriented Life Support: Experiment and Feasibility Study

    Seiji Kasuya, Xiaokang Zhou, Shoji Nishimura, Qun Jin

    ADVANCES IN DIGITAL TECHNOLOGIES   282   172 - 179  2016  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Ubi-Liven: A Human-Centric Safe and Secure Framework of Ubiquitous Living Environments for the Elderly

    Qun Jin, Bo Wu, Shoji Nishimura, Atsushi Ogihara

    2016 FOURTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD 2016)     304 - 309  2016  [Refereed]

    Authorship：Lead author

    DOI

  • A Privacy-Preserving Incentive Scheme for Advertisement Dissemination in Vehicular Social Networks

    Peipei Xiao, Yufeng Wang, Qun Jin, Jianhua Ma

    2016 IEEE TRUSTCOM/BIGDATASE/ISPA     1741 - 1746  2016  [Refereed]

    　View Summary

    Recent years has witnessed a great progress in Vehicular Social Networks (VSNs), which is a particular class of vehicular ad hoc networks, characterized by social aspects and features, including human mobility and rational behaviors. Among various VSN applications, one of the most promising applications is the dissemination of commercial advertisement via car-to-RSU (rode side unit) and car-to-car communication. However, due to non-cooperative behavior of selfish nodes or malicious ones in the real-world scenario, such vehicular advertisement system can't be realized unless proper security and incentive mechanisms are taken into account. In this paper, the privacy concern is addressed by leveraging a PKI (Public Key Infrastructure) to provide secure incentives for cooperative nodes. The selfishness issue is solved through adopting Topology dependent Reward Mechanisms (TDRM). Preliminary theoretical and simulation results show that, besides incentivizing individuals' participation, the proposed scheme can increase participants' reward through their active contribution and solicitation, and moreover, is robust against users' misbehaviors, especially Sybil-attack.

    DOI

  • Dynamic Community Mining and Tracking Based on Temporal Social Network Analysis

    Xiaokang Zhou, Wei Liang, Bo Wu, Zixian Lu, Shoji Nishimura, Takashi Shinomiya, Qun Jin

    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT)     177 - 182  2016  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Energy-Efficient Architecture and Technologies for Device to Device (D2D) Based Proximity Service

    Zhang Bo, Wang Yufeng, Jin Qun, Ma Jianhua

    CHINA COMMUNICATIONS   12 ( 12 ) 32 - 42  2015.12  [Refereed]

    　View Summary

    Considering that modern mobile terminals possess the capability to detect users' proximity, and offer means to directly communicate and share content with the people in close area, Device-to-Device (D2D) based Proximity Services (Pro Se) have recently witnessed great development, which enable users to seek for and utilize relevant value in their physical proximity, and are capable to create numerous new mobile service opportunities. However, without a breakthrough in battery technology, the energy will be the biggest limitation for ProSe. Through incorporating the features of ProSe (D2D communication technologies, abundant built-in sensors, localization-dependent, and context-aware, etc.), this paper thoroughly investigates the energy-efficient architecture and technologies for ProSe from the following four aspects: underlying networking technology, localization, application and architecture features, context-aware and user interactions. Besides exploring specific energy-efficient schemes pertaining to each aspect, this paper offers a perspective for research and applications. In brief, through classifying, summarizing and optimizing the multiple efforts on studying, modeling and reducing energy consumption for ProSe on mobile devices, the paper would provide guide for developers to build energy-efficient ProSe.

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • A Pagerank-Inspired Heuristic Scheme for Influence Maximization in Social Networks

    Bo Zhang, Yufeng Wang, Qun Jin, Jianhua Ma

    INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH   12 ( 4 ) 48 - 62  2015.10  [Refereed]

    　View Summary

    This article focused on seeking a new heuristic algorithm for the influence maximization problem in complex social networks, in which a small subset of individuals are intentionally selected as seeds to trigger a large cascade of further adoptions of a new behavior under certain influence cascade models. In literature, degree and other centrality-based heuristics are commonly used to estimate the influential power of individuals in social networks. The major issues with degree-based heuristics are twofold. First, those results are only derived for the uniform IC model, in which propagation probabilities on all social links are set as same, which is rarely the case in reality; Second, intuitively, an individual's influence power depends not only on the number of direct friends, but also relates to kinds of those friends, that is, the neighbors' influence should also be taken into account when measuring one's influential power. Based on the general weighted cascade model (WC), this article proposes Pagerank-inspired heuristic scheme, PRDiscount, which explicitly discounts the influence power of those individuals who have social relationships with chosen seeds, to alleviate the "overlapping effect" occurred in behavior diffusion. Then, the authors use both the artificially constructed social network graphs (with the features of power-law degree distribution and small-world characteristics) and the real-data traces of social networks to verify the performance of their proposal. Simulations illustrate that PRDiscount can advantage over the existing degree-based discount algorithm, Degree Discount, and achieve the comparable performance as greedy algorithm.

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • HIC 2015 Chairs' welcome

    Neil Y. Yen, Qun Jin

    HIC 2015 - Proceedings of the 2015 International Workshop on Human-centric Independent Computing, co-located with HT 2015     iii  2015.09  [Invited]

    Authorship：Last author

  • Social Recommendation Algorithm Dynamically Adaptable to User Profiling for SNS

    Weimin Li, Yikai Ni, Minye Wu, Zhengbo Ye, Qun Jin

    Proceedings - 2014 2nd International Conference on Advanced Cloud and Big Data, CBD 2014     261 - 266  2015.08  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Multi-dimensional attributes and measures for dynamical user profiling in social networking environments

    Xiaokang Zhou, Wei Wang, Qun Jin

    MULTIMEDIA TOOLS AND APPLICATIONS   74 ( 14 ) 5015 - 5028  2015.07  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    40
    Citation
    (Scopus)

  • Participatory information search and recommendation based on social roles and networks

    Bo Wu, Xiaokang Zhou, Qun Jin

    MULTIMEDIA TOOLS AND APPLICATIONS   74 ( 14 ) 5173 - 5188  2015.07  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Personalized fitting recommendation based on support vector regression

    Weimin Li, Xunfeng Li, Mengke Yao, Jiulei Jiang, Qun Jin

    HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES   5 ( 1 )  2015.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • Special Issue on "Massive Open Online Courses (MOOCs)" PREFACE

    Hung Jason C, Shih Timothy K, Jin Qun

    INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES   13 ( 3 ) IV - VI  2015.07  [Invited]

    Authorship：Last author

  • Intelligent state machine for social ad hoc data management and reuse

    Neil Y. Yen, Qun Jin, Joseph C. Tsai, James J. Park

    MULTIMEDIA TOOLS AND APPLICATIONS   74 ( 10 ) 3521 - 3541  2015.05  [Refereed]

    　View Summary

    Recent advances in information technology have turned out World Wide Web to be the main platform for interactions where participants-users and corresponding events-are triggered. Although the participants vary in accordance with scenarios, a considerable size of data will be generated. This phenomenon indeed causes the complexity in information retrieval, management, and resuse, and meanwhile, turns down the value of this data. In this research, we attempt to achieve efficient management of user-generated data and its derivative contexts (i.e., social ad hoc data) for human supports. The correlations among data, contexts, and their hybridization are specifically concentrated. An intelligent state machine is proposed to outline the relations of data and contexts, and applied to further identify their usage scenarios. The performance and feasibility can be revealed by the experiments that were conducted on the data collected from open social networks (e.g., Facebook, Twitter, etc.) in the past few years with size around 500 users and 8,000,000 shared contents from them.

    DOI

    Scopus

  • Privacy protection for lbs in mobile environments: Progresses, issues and challenges

    Julong Pan, Zhengwei Zuo, Zhanyi Xu, Qun Jin

    International Journal of Security and its Applications   9 ( 1 ) 249 - 258  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • LIP3: A Lightweighted Fine-Grained Privacy-Preserving Profile Matching Mechanism for Mobile Social Networks in Proximity

    Yufeng Wang, Xiaohong Chen, Qun Jin, Jianhua Ma

    ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, ICA3PP 2015   9532   166 - 176  2015  [Refereed]

    　View Summary

    Recently, Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones, which enable actively/passively and continuously seek for relevant value in one's physical proximity, through direct communicating with other individuals within the communication range, without the support of centralized networking infrastructure. Specially, a user would like to find out and interact with some strangers with similar interest in vicinity through profile matching. However, in matching process, individuals always have to reveal their personal and private profiles to strangers, which conflicts with users' growing privacy concerns. To achieve privacy preserving profile matching (i.e., friend discovery), many schemes are proposed based on homomorphic and commutative encryption, which bring tremendous computation and communication overheads, and are not practical for the resource limited mobile devices in MSNP. In this paper we adapt Confusion Matrix Transformation (CMT) method to design a Lightweighted fIne-grained Privacy-Preserving Profile matching mechanism, LIP3, which can not only efficiently realize privacy-preserving profile matching, but obtain the strict measurement of cosine similarity between individuals, while other existing CMT-based schemes can only roughly estimate the matching value.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Personalized Micro-Learning Support Based on Process Mining

    Jian Chen, Yueqin Zhang, Jingyu Sun, Yongle Chen, Fuping Lin, Qun Jin

    2015 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN MEDICINE AND EDUCATION (ITME)     511 - 515  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    14
    Citation
    (Scopus)

  • Service Discovery Based on Trustworthiness in MSNP: Major Issues, Potential Solutions, and Feasible Strategies

    Xixi Ma, Qun Jin, Julong Pan, Yufeng Wang

    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY)     315 - 320  2015  [Refereed]

    　View Summary

    With the popularity of mobile Internet, smart phones and location-based services, Mobile Social Network in Proximity (MSNP) has attracted more and more attentions, for which trustworthy service discovery and its associated latency are two important issues. In this paper, after overviewing MSNP and trustworthiness for service discovery in MSNP, we discuss the major issues and potential solutions of trustworthy service discovery. We present trustworthiness determination strategies based on service provider candidates' past experience and current profile analysis to reduce the latency caused by trustworthiness computation for trustworthy service discovery in MSNP.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • HYChat: A hybrid interactive chat system for mobile social networking in proximity

    Jinhang Zuo, Yufeng Wang, Qun Jin, Jianhua Ma

    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY)     471 - 477  2015  [Refereed]

    　View Summary

    Recently, mobile social networks in proximity (MSNP) has gained tremendous attentions, which explicitly explores the physical proximity of individuals, and greatly facilitates their face-to-face interactions through direct communications. Generally, Proximity awareness can be enabled with two methodologies: Over-The-Top (OTT), in which the centralized server determines the proximity based on users' location updates and interests, and intermediate the interactions between proximal users; Device-to-Device (D2D), which allows two devices in radio range to discovery and communicate directly. This paper designs and implements a novel hybrid interactive chatting system, HYChat, which integrates the merits of both methodologies: simultaneously support direct interaction through WiFi Direct when individuals are within each other's radio range; when detecting two devices are out of range of WiFi Direct (e.g., due to individual's movement), it will switch to online OTT mode automatically to continue the interactive chat. Specifically, two key challenges in HYChat are preliminarily solved in this paper: profile matching prior to establishing connection among devices (i.e., layer 2 profile matching), and the smooth switching between D2D and OTT modes. The prototype of HYChat on Android phones illustrates its effectiveness. In brief, the hybrid system HYChat could greatly facilitate individuals' social interaction in physical proximity.

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • A Temporal Model of Research Work Tracking and Assessing for an Individual and a Group

    Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY)     440 - 445  2015  [Refereed]

    　View Summary

    Although there are many research works focused on scientific community discovery and researcher profiling, it is still a challenge to track and assess the research development for an individual researcher or a research group over time. In this study, we seek to model and quantify an individual's research work outcome during his/her research career. A temporal tracking model is introduced to represent research development for both an individual and a group along the time. Furthermore, assessing measures are proposed to depict how to quantify a research group's outcomes by its members' contribution. Based on our model, a research topic analyzing approach is proposed to extract the topics covered by a group and discover the group's research pattern. The analyzed output is helpful for a researcher to pursue his/her scientific life or find collaboration opportunities.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Open Learning Platform Based on Personal and Social Analytics for Individualized Learning Support

    Xiaokang Zhou, Bo Wu, Qun Jin

    IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS     1741 - 1745  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Modeling of research topic evolution associated with social networks of researchers

    Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

    IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS     1169 - 1174  2015  [Refereed]

    　View Summary

    Understanding research topic evolution in a specific field is important to learn the temporal structure and latent research trends. Although research works in terms of topic analysis have been developed for many years, it is still difficult to well understand the topic evolution due to the limitation of the bibliographical data which does not consider the researchers' profiles and their social networks. In this study, to analyze the underlying research topic evolution and facilitate the scientific collaborations for researchers, a novel topic evolution model based on the analysis of researchers' social networks is built. Specifically, the researchers' co-authorships associated with their latent social networks are analyzed. A research topic tracking method is then developed to track the topic evolutions and analyze the research lifecycle for the latent scientific teams. The derived results can help users to discover the major research trends for specific fields. And the tracked statuses of the corresponding scientific groups are illustrated in different lifecycle stages, which is useful for the search of research trends or finding of collaboration opportunity according to researchers' different requirements.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • BWMesh: a multi-hop connectivity framework on Android for proximity service

    Yufeng Wang, Jing Tang, Qun Jin, Jianhua Ma

    IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS     278 - 283  2015  [Refereed]

    　View Summary

    Considering the inherent properties of privacy protection and battery efficiency, Device-to-Device (D2D) based proximity service (ProSe) has recently witnessed great development, which enable user to continuously and passively search for and utilize relevant value in one's physical proximity, and is capable to create numerous new mobile service opportunities. However, most of existing ProSe enabled frameworks and applications only provide single-hop Peer-to-Peer connection, lack of easily supporting simultaneous and multi-hop connection on commercially available smartphones to broaden ProSe coverage in static scenario. To solve this issue, this paper proposes a multi-hop connectivity framework BWMesh, through combining Bluetooth and WiFi Direct technologies. BWMesh possesses two special features: exploit users' heterogeneous network and enable smooth interaction among devices with different wireless technologies; provide an easy-to-deploy multi-hop networking framework on currently commercial available smartphones. Specifically, we identify several key issues in multi-hop connectivity framework, design and implement corresponding components to deal with those issues. Then, a prototype MultiChat, is developed based on BWMesh framework, which enables real-time chat among users in proximity, in multi-hop way, without accessing to Internet.

    DOI

    Scopus

    15
    Citation
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  • Mobile crowdsourcing: architecture, applications, and challenges

    Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

    IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS     1127 - 1132  2015  [Refereed]

    　View Summary

    Crowdsourcing is the generalized act of outsourcing tasks, traditionally performed by employees or contractors, to a large group of Internet population (the wise crowd) by means of an open call. With the great development of smartphones with rich built-in sensors and ratio interfaces, mixing smartphone-based mobile technologies and crowdsourcing offers vast computing resources, and leads to a new paradigm called Mobile Crowdsourcing (MCS). In this paper, we presents a taxonomy for the MCS applications, which are explicitly divided as using human as sensors, and exploiting the wisdom of crowd, and typical applications are summarized and compared. Then, a generic MCS framework is proposed, which consists of multiple functional modules. Finally, we elaborate the challenges in MCS applications (i.e., quality control, task management, incentives, as well as security and privacy), and summarize potential solutions. Our main contribution is to classify and provide a summary MCS framework, challenges and possible solutions to facilitate to develop and deploy various MCS applications.

    DOI

    Scopus

    11
    Citation
    (Scopus)

  • Associative Recommendation of Learning Contents Aided by Eye-Tracking in a Social Media Enhanced Environment

    Guangyu Piao, Xiaokang Zhou, Qun Jin

    UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR   331   493 - 501  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • A Heuristic Scheduling Approach to Hybrid Makepsan Problem for Data Intensive Computing

    Wei Liang, Yonghua Xiong, Min Wu, Qun Jin

    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY)     932 - 937  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Strategic management advanced service for sustainable computing environment

    Sang Soo Yeo, Qun Jin, Vincenzo Loia, Hangbae Chang

    Scientific World Journal   2015   1 - 2  2015  [Invited]

    DOI

    Scopus

  • Organic streams a unified framework for personal big data integration and organization towards social sharing and individualized sustainable use

    Xiaokang Zhou, Qun Jin

    Big Data: Algorithms, Analytics, and Applications     241 - 255  2015.01  [Refereed]

    Authorship：Last author, Corresponding author

  • Message from SocialCom 2015 general chairs

    Qun Jin, Timothy K. Shih

    Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015     xxx  2015  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • Social network recommendation based on hybrid suffix tree clustering

    Jianhao Zhang, Xun Ma, Weimin Li, Qun Jin

    Lecture Notes in Electrical Engineering   330   47 - 53  2015  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Message from the FiSTA 2014 workshop organizers

    Bernady O. Apduhan, Rafael Santos, Jianhua Ma, Qun Jin

    Proceedings - 14th International Conference on Computational Science and Its Applications, ICCSA 2014     xxii  2014.12  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • On studying business models in mobile social networks based on two-sided market (TSM)

    Yufeng Wang, Jing Tang, Qun Jin, Jianhua Ma

    JOURNAL OF SUPERCOMPUTING   70 ( 3 ) 1297 - 1317  2014.12  [Refereed]

    　View Summary

    In contrast to the huge popularity of Mobile Social Network (MSN) services, not sufficient attention has been reserved to the dynamics of revenue streams and business models in MSN. In this paper, we investigate how a two-sided market (TSM) formulation can be used to provide insight for the problem above from the perspective of MSN platform. Intuitively, MSN service platform could be described as a two-sided market, in which the critical feature is indirect value flow (indirect network externality): one/both sides of the market benefit from increasing adoption and/or consumption of the other side. For instance, participants, like consumers and the third service providers (or advertisers), are the "two sides" of MSN platform. In this paper, our contributions are threefold. First, we thoroughly characterize the economic features of MSN as TSM, including mobility, network externalities and herd effect, as well as long tail property. Second, we provide the various revenue streams within the framework of TSM, including advertising, subscription, and transactions, and characterize the basic components of general business model in MSN. Finally, the free plus premium (Freemium) business model in MSN is formally analyzed. Specifically, we quantitatively characterize the relationship of participation levels among free and premium users as well as service providers, and illustrate the mutual enhancement among those participants. And moreover, Freemium is theoretically compared with the traditional business model with no free users (NF model). The numerical results show that, in Freemium, the participation levels of premium users and service providers, as well as the profit of MSN platform always exceed the corresponding terms in NF model.

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Recommendation of location-based services based on composite measures of trust degree

    Weimin Li, Mengke Yao, Xiaokang Zhou, Shoji Nishimura, Qun Jin

    JOURNAL OF SUPERCOMPUTING   69 ( 3 ) 1154 - 1165  2014.09  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Survey on mobile social networking in proximity (MSNP): approaches, challenges and architecture

    Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

    WIRELESS NETWORKS   20 ( 6 ) 1295 - 1311  2014.08  [Refereed]

    　View Summary

    Recently, mobile social networks (MSN) have gained tremendous attention, which free users from face-to-monitor life, while still can share information and stay in touch with their friends on the go. However most MSN applications regard mobile terminals just as entry points to existing social networks, in which centralized servers (for storage and processing of all application/context data) and continual Internet connectivity are prerequisites for mobile users to exploit MSN services, even though they are within proximity area (like campus, event spot, and community, etc.), and can directly exchange data through various wireless technologies (e.g., Bluetooth, WiFi Direct, etc.). In this paper, we focus on mobile social networking in proximity (MSNP), which is explicitly defined in our paper as: MSNP is wireless peer-to-peer (P2P) network of spontaneously and opportunistically connected nodes, and uses geo-proximity as the primary filter in determining who is discoverable on the social network. In this paper, first, primary support approaches related to MSNP available in literature, are summarized and compared, including MSN, mobile P2P and opportunistic networks. And then, we offer the special characteristics of MSNP, open issues and potential solutions. A networking technologies and platform independent architecture is proposed for developing MSNP applications, and proof-of-concept implementation of WiFi direct based MSNP application is also provided. Our primary goal is to identify the characteristics, technical challenges and potential solutions for future MSNP applications, capable to flexibly adapt to different application domains and deployment requirements.

    DOI

    Scopus

    67
    Citation
    (Scopus)

  • Special Issue on "Hybrid intelligence for growing internet and its applications" Preface

    Neil Y. Yen, Qun Jin, Ching-Hsien Hsu, Qiangfu Zhao

    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE   37   401 - 403  2014.07  [Invited]

    DOI

    Scopus

  • Probability Modeling and Functional Validation of Dynamic Service Composition for Location Based Services with Uncertain Factors

    Weimin Li, Zhengbo Ye, Xiaohua Zhao, Jiulei Jiang, Qun Jin

    JOURNAL OF INTERNET TECHNOLOGY   15 ( 4 ) 635 - 643  2014.07  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Process-Focused Social Learning Analytics Based on Personal Big Data for Cross-MOOCs Open Environments

    Q. Jin, X. Zhou, B. Wu, J. Chen, J. Pan, W. Zheng

    (Poster) Intel‐CSU Transparent Computing and Big Data Summit    2014.07  [Invited]

    Authorship：Lead author

  • Special section on human-centric computing Preface

    Qun Jin, Sethuraman Panchanathan, Changhoon Lee

    INFORMATION SCIENCES   257   229 - 230  2014.02  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • A human-centric framework for context-aware flowable services in cloud computing environments

    Yishui Zhu, Roman Y. Shtykh, Qun Jin

    INFORMATION SCIENCES   257   231 - 247  2014.02  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    13
    Citation
    (Scopus)

  • A malicious behavior analysis based Cyber-I birth

    Jie Wen, Jianhua Ma, Runhe Huang, Qun Jin, Jian Chen, Benxiong Huang, Ning Zhong

    JOURNAL OF INTELLIGENT MANUFACTURING   25 ( 1 ) 147 - 155  2014.02  [Refereed]

    　View Summary

    Cyber-Individual (Cyber-I) is the digital counterpart of an individual in the real world, which aims at systematically studying and developing comprehensive individual human modeling and its associated applications. The ultimate goal of this research is to create a digital clone for each individual and to provide active desirable services. We present a part of our research work focusing on examining the basic system architecture and the birth process of Cyber-I from a security perspective. In this study, a customized honeypot is used to record multidimensional data Cyber-I is constructed for a corresponding invader. Further, assembling a Cyber-I with associated CI-Applications enables aninvader having more behaviors in the honeypot and provides a possible chance to prolong activities of the invader, which complements a loop mechanism to feed Cyber-I for its growth. The preliminary result in this paper reveals that appropriate authorization and controls are extremely necessary to prevent Cyber-I from being maliciously used and to ensure privacy of its real individual in building an open Cyber-I platform.

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • User Attribute Analysis for Dynamical User Profiling in Social Networking Environments

    X. Zhou, Q. Jin

    Proc. AIM2014 (The 4th FTRA International Conference on Advanced IT, Engineering and Management)    2014.02  [Refereed]

    Authorship：Last author

  • Personalized Fitting with Deviation Adjustment Based on Support Vector Regression for Recommendation

    Weimin Li, Mengke Yao, Qun Jin

    MULTIMEDIA AND UBIQUITOUS ENGINEERING   308   173 - 178  2014  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Hierarchical Modeling and Analysis of Social Roles for Collective Decision-Making Support

    Bo Wu, Xiaokang Zhou, Qun Jin, Fuhua Lin, Henry Leung

    2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT)     490 - 495  2014  [Refereed]

    　View Summary

    With the popularity of Social Network Service (SNS) and the increasing of users, individuals' social roles in a social network have become more and more important in recommendation of the personalized services, and in a collective decision-making process as well. In an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may be multifarious. In this study, we consider users' social roles as an important element to support the collective decision-making process. After introducing the social choice theories and collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way, and utilize it to support the collective decision-making process. A case study for COD (Course-Offering Determination) with an application scenario is demonstrated to show the process of how users' social roles are utilized to support the collective decision-making.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A Wi-Fi Direct based P2P application prototype for mobile social networking in proximity (MSNP)

    Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

    2014 IEEE 12TH INTERNATIONAL CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING (DASC)/2014 IEEE 12TH INTERNATIONAL CONFERENCE ON EMBEDDED COMPUTING (EMBEDDEDCOM)/2014 IEEE 12TH INTERNATIONAL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING (PICOM)     283 - +  2014  [Refereed]

    　View Summary

    Nowadays, most popular social networking services adopt centralized architecture, in which continual Internet connectivity is prerequisite for each user to exploit those services, and centralized servers are used for storage and processing of all application/context data, even though mobile users are within proximity area (like campus, event spot, and community), and can directly exchange media through various wireless technologies (e.g., Bluetooth, Wi-Fi Direct, etc.). On one hand, the omniscient centralized server may cause serious privacy concern, due to the fact that it collects and stores all users' data (messages, profiles, location, relations, etc.); On the other hand, transmitting a large amount of media generated by users in proximity through Internet, would not only bring a lot of pressure to the network infrastructure and service provider, but incur heavy data traffic cost to users. In this paper, our contributions are twofold. First, we propose a Wi-Fi Direct based P2P social networking framework, which enables direct data exchange among users without using infrastructure network when users are located in proximity, and provide solutions to two core problems in this framework, i.e., discoverability and privacy. Second, the prototype of this framework is preliminarily implemented in Android, which is composed of the following functions: localization based on Google Geocoding, Chat, and file-sharing component supporting intermittent transmission.

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • A Management System for Cyber Individuals and Heterogeneous Data

    Jun Ren, Jianhua Ma, Runhe Huang, Qun Jin, Zhigang Chen

    2014 IEEE 11TH INTL CONF ON UBIQUITOUS INTELLIGENCE AND COMPUTING AND 2014 IEEE 11TH INTL CONF ON AUTONOMIC AND TRUSTED COMPUTING AND 2014 IEEE 14TH INTL CONF ON SCALABLE COMPUTING AND COMMUNICATIONS AND ITS ASSOCIATED WORKSHOPS     88 - 95  2014  [Refereed]

    　View Summary

    The progressive development of information and communication technologies has led us to a new world called hyper world that is composed by the cyber world and the physical world, which, at the same time, brings us the digital explosions of data and connectivity as well as all kinds of smart services. Based on these, Cyber-I was proposed, which aims at creating a unique, digital, comprehensive description for every real person so that the possibility for the person being in the cyber world to get lost in the digital explosions will be reduced. However, the ultimate goal of realizing such Cyber-I needs an endless research process, which will cover multiple areas and disciplines. In order to merge efforts on the study of Cyber-I together as well as provide people with better services utilizing Cyber-I, this paper presents our research and development on a Cyber-I oriented management system where (1) the life cycle of Cyber-I including its birth, growth and death is simulated, (2) with the NO-SQL properties supported by Mongo DB, heterogeneous personal data coming from disparate sources with different formats through varied media can be managed in a scalable way, and (3) apps connected with the Cyber-I can not only fetch personal data but also provide personalized services, while the collected personal data can be used to generate user models from different aspects.

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • Alljoyn based direct proximity service development: overview and prototype

    Yufeng Wang, Li Wei, Qun Jin, Jianhua Ma

    2014 IEEE 17th International Conference on Computational Science and Engineering (CSE)     634 - 641  2014  [Refereed]

    　View Summary

    Proximity awareness, the ability to actively (or passively) and continuously search for relevant value in one's physical proximity, is at the core of mobile revolution that is changing the way we interact with people and things around us. Especially, Device-to-Device (D2D) (peer-to-peer (P2P)) solutions support infrastructure-free and self-organized proximity services, and have great commercial potential from application viewpoint. However, astonishingly, the glaring absence of the practical and easy-to-use proximity service development framework is alarming. This paper aims at investigating the Qualcomm AllJoyn middleware, an open source peer-to-peer software development framework for ad-hoc proximity based D2D communication, and exploring how this middleware can enable the development of distributed application in mobile social networks in proximity (MSNP). Specifically, we thoroughly overview the core concepts and basic components in AllJoyn framework, and summarize the typical workflow of developing AllJoyn based proximity application. Furthermore, an AllJoyn based MSNP prototype, AllChat, is designed and implemented, in which users can enjoy text chat and photo sharing with both group and peer interaction modes in real time.

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • Social Stream Organization Based on User Role Analysis for Participatory Information Recommendation

    Xiaokang Zhou, Bo Wu, Qun Jin, Shoji Nishimura, Julong Pan, Wenbin Zheng, Jianhua Ma

    2014 7TH INTERNATIONAL CONFERENCE ON UBI-MEDIA COMPUTING AND WORKSHOPS (UMEDIA)     105 - 110  2014  [Refereed]

    　View Summary

    In this study, we propose an integrated approach to organize and refine the social streams in accordance with the analysis of both social data and social roles within a social group. The social stream data will be first collected and organized based on users' individual needs. After the calculation and analysis of users' importance based on the identification and classification of users' dynamical social roles within a user group, a mechanism is developed to organize and refine social streams and further provide users with more suitable and useful information that best fits their needs from more related users, in order to better assist the participatory information search and recommendation process in the social networking environment.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Message from the ITME 2013 general chairs

    Yongnian Liu, Xiaohong Jiang, James J. Park, Qun Jin, Hong Liu

    Lecture Notes in Electrical Engineering   269  2014  [Invited]

  • Preface

    Qun Jin, Jason C. Hung

    International Journal of Computational Science and Engineering   9 ( 3 ) 153 - 154  2014  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • A progressive approach for cross-browser web data generation

    Jin Zhu, Yoshiyori Urano, Hidenori Nakazato, Qun Jin

    International Journal of Computational Science and Engineering   9 ( 3 ) 235 - 246  2014  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • A probabilistic timing constraint modeling and functional validation approach to dynamic service composition for LBS

    Weimin Li, Xiaohua Zhao, Jiulei Jiang, Xiaokang Zhou, Qun Jin

    Lecture Notes in Electrical Engineering   274   501 - 508  2014  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • An integrated recommendation approach based on influence and trust in social networks

    Weimin Li, Zhengbo Ye, Qun Jin

    Lecture Notes in Electrical Engineering   309   83 - 89  2014  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Capturing unselfconscious information seeking behavior by analyzing gaze patterns via eye tracking experiments

    Guangyu Piao, Xiaokang Zhou, Qun Jin, Shoji Nishimura

    2013 IEEE Conference Anthology, ANTHOLOGY 2013    2014  [Refereed]

    　View Summary

    In recent years, eye tracking has been widely applied in a variety of fields, such as web usability studies and psychological experiments. To develop a personalized system or network service, it is important to recognize and capture users' needs, situations and contexts in order to create an effective user model. In this paper, we present an integrated approach on how to capture users' unselfconscious information seeking behavior by analyzing their gaze patterns using an eye tracker. We describe the design of an eye tracking experiment, and analyze the eye tracking data to extract gaze patterns, which can be used for use modeling. We further discuss the experiment result and highlight our future work. © 2013 IEEE.

    DOI

    Scopus

  • Blended learning support with social media empowered by ubiquitous personal study

    Xiaokang Zhou, Haifeng Man, Hong Chen, Yan Wu, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7697   130 - 139  2014  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Analysis of sharable learning processes and action patterns for adaptive learning support

    Xiaokang Zhou, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   8613   173 - 178  2014  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

  • Recommendation of optimized information seeking process based on the similarity of user access behavior patterns

    Jian Chen, Xiaokang Zhou, Qun Jin

    PERSONAL AND UBIQUITOUS COMPUTING   17 ( 8 ) 1671 - 1681  2013.12  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    20
    Citation
    (Scopus)

  • Modeling user-generated contents: an intelligent state machine for user-centric search support

    Neil Y. Yen, James J. (Jong Hyuk) Park, Qun Jin, Timothy K. Shih

    PERSONAL AND UBIQUITOUS COMPUTING   17 ( 8 ) 1731 - 1739  2013.12  [Refereed]

    　View Summary

    Researchers tend to agree that an increasing quantity of data has caused the complexity and difficulty for information discovery, management, and reuse. An essential factor relates to the increasing channels (i.e., Internet, social media, etc.) for information sharing. Finding information, especially those meaningful or useful one, that meets ultimate goal (or task) of user becomes harder then it is used to be. In this research, issues concerning the use of user-generated contents for individual search support are investigated. In order to make efficient use of user-generated contents, an intelligent state machine, as a hybridization of graph model (Document Graph) and petri-net model (Document Sensitive Petri-Net), is proposed. It is utilized to clarify the vague usage scenario between user-generated contents, such as discussions, posts, etc., and to identify correlations and experiences within them. As a practical contribution, an interactive search algorithm that generates potential solutions for individual is implemented. The feasibility of this research is demonstrated by a series of experiments and empirical studies with around 350,000 user-generated contents (i.e., documents) collected from the Internet and 200 users.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Research on life-cycle of user model in U-Business

    Bofeng Zhang, Jianxing Zheng, Jianhua Ma, Yinsheng Li, Guobing Zou, Qun Jin

    PERSONAL AND UBIQUITOUS COMPUTING   17 ( 7 ) 1449 - 1457  2013.10  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Intelligent route generation: Discovery and search of correlation between shared resources

    Neil Y. Yen, Runhe Huang, Jianhua Ma, Qun Jin, Timothy K. Shih

    International Journal of Communication Systems   26 ( 6 ) 732 - 746  2013.06  [Refereed]

    　View Summary

    Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes it possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any place. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e., geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes to facilitate search process and to enrich the learning activity. The empirical experiments revealing the feasibility and performance (e.g., accuracy and effectiveness) are conducted in the universities in North Taiwan. © 2012 John Wiley &amp
    Sons, Ltd.

    DOI

    Scopus

    14
    Citation
    (Scopus)

  • Enriching user search experience by mining social streams with heuristic stones and associative ripples

    Xiaokang Zhou, Neil Y. Yen, Qun Jin, Timothy K. Shih

    Multimedia Tools and Applications   63 ( 1 ) 129 - 144  2013.03  [Refereed]

    　View Summary

    Recently, social networking sites such as Facebook and Twitter are becoming increasingly popular. The high accessibility of these sites has allowed the so-called social streams being spread across the Internet more quickly and widely, as more and more of the populations are being engaged into this vortex of the social networking revolution. Information seeking never means simply typing a few keywords into a search engine in this stream world. In this study, we try to find a way to utilize these diversified social streams to assist the search process without relying solely on the inputted keywords. We propose a method to analyze and extract meaningful information in accordance with users' current needs and interests from social streams using two developed algorithms, and go further to integrate these organized stream data which are described as associative ripples into the search system, in order to improve the relevance of the results obtained from the search engine and feedback users with a new perspective of the sought issues to guide the further information seeking process, which can benefit both search experience enrichment and search process facilitation. © 2012 Springer Science+Business Media, LLC.

    DOI

    Scopus

    26
    Citation
    (Scopus)

  • Effective session key distribution for secure fast handover in mobile networks (vol 44, pg 97, 2010)

    Jong Hyuk Park, Qun Jin

    TELECOMMUNICATION SYSTEMS   52 ( 1 ) 359 - 359  2013.01  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Discovery of action patterns in task-oriented learning processes

    Xiaokang Zhou, Jian Chen, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   8167   121 - 130  2013  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Eye-Tracking Experiment Design for Extraction of Viewing Patterns in Social Media

    Guangyu Piao, Qun Jin, Xiaokang Zhou, Shoji Nishimura, Kanoksak Wattanachote, Timothy K. Shih, Neil Y. Yen

    2013 IEEE 10TH INTERNATIONAL CONFERENCE ON AND 10TH INTERNATIONAL CONFERENCE ON AUTONOMIC AND TRUSTED COMPUTING (UIC/ATC) UBIQUITOUS INTELLIGENCE AND COMPUTING     308 - 313  2013  [Refereed]

    　View Summary

    Recently, eye-tracking has been widely applied in a wide spectrum of fields for both academic researches and Business. In this study, we concentrate on the analysis of instant (and often subconscious) information generated from interactions between an individual and devices, such as a PC, laptop, and mobile phone. We present the experiment design to capture and extract the viewing patterns in Twitter using the eye-tracking technology. We show a set of experiment results based on the analysis of eye gazing data, in order to demonstrate how the subjects look for specified keywords in the Twitter timeline, which can further contribute to categorization of viewing patterns.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Organic Streams: Data Aggregation and Integration Based on Individual Needs

    Xiaokang Zhou, Qun Jin, Bo Wu, Wei Wang, Julong Pan, Wenbin Zheng

    2013 INTERNATIONAL JOINT CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY & UBI-MEDIA COMPUTING (ICAST-UMEDIA)     535 - +  2013  [Refereed]

    　View Summary

    With the high accessibility of the social media, more and more people have been accustomed to sharing their personal contents across the social networks, which results in an explosive increase of data scale. In this study, in order to support information and knowledge discovery in big data, we propose an approach to aggregation and integration of personal big data from life logs in accordance with individual needs, which can benefit the sustainable information utilization process. In details, the organic stream, which is designed as an extensible data carrier, is introduced and developed to formulize and organize the personal big data, in order to extract dynamical individual needs from the tremendous amount of data posted through social media, and further aggregate and integrate the related data in a meaningful way, which can also facilitate the personalized information retrieval and reuse process. The architecture of the system with the foundational modules is given, and the experiment result is presented to demonstrate the usability and effectiveness of our approach.

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Dynamically Identifying Roles in Social Media by Mapping Real World

    Bo Wu, Qun Jin, Xiaokang Zhou, Wei Wang, Fuhua Lin, Henry Leung

    2013 INTERNATIONAL JOINT CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY & UBI-MEDIA COMPUTING (ICAST-UMEDIA)     573 - +  2013  [Refereed]

    　View Summary

    With the rapid growing of users in the SNS environments, their network relationships in Internet have become as complex as in the real world. On the other hand, the user's social role plays an important role in providing individualized services, such as information recommendation in the SNS environments. However, as we know, people will switch or change their social roles dynamically in the real society, which is also true in the cyber network space, such as SNS. In this paper, we present a basic model to describe social roles in both the real world and the SNS environment, in which a set of attributes and factors are considered and introduced to represent the time-changing social roles in different situations and contexts. The mechanism that we develop to identify the roles is twofold: mapping of real world situations to cyber space, and analyzing social role attributes based on the mapping and synthesizing. We further describe an application scenario in regard to how to map the different situations and analyze the role attributes, in order to dynamically identify roles in the cyber space.

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Overview mobile social networking in proximity (MSNP): applications, characterstics and challenges

    Yufeng Wang, Tang Jing, Qun Jin, Jianhua Ma

    2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC)     2112 - 2119  2013  [Refereed]

    　View Summary

    Recently, mobile social networking applications have gained tremendous attention, which free users from face-to-monitor life, while they still can share information and stay in touch with their friends on the go. However most MSN applications regard mobile terminals just as entry points to existing social networks, depend on centralized servers (for storage and processing of all application/context data) and continual Internet connectivity, even though mobile users are within proximity area (like campus, event spot, and community), and can directly exchange data through various wireless technologies (e.g., WiFi Direct, etc.). In this paper, we focus on thoroughly overviewing the mobile social networking in proximity (MSNP), including existing applications, characteristics and challenges. Our primary goal is to identify the characteristics, technical challenges and potential solution for future MSNP applications, capable to flexibly adapt to different application domains and deployment requirements.

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Message from the FiSTA 2013 chairs

    Jianhua Ma, Qun Jin, Rafael Santos, Agustinus Borgy Waluyo, Andrew Flahive, Bernady O. Apduhan, Atsuko Takefusa, Ching Hsien Hsu, Fenghui Yao, Guifeng Shao, Hai V. Tran, Hiroaki Higaki

    Proceedings of the 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013    2013  [Invited]

    DOI

    Scopus

  • Special issue on cognitivebased text understanding and web wisdom

    Xiangfeng Luo, Qing Li, Qun Jin, Feifei Xu

    International Journal of Cognitive Informatics and Natural Intelligence   7 ( 2 )  2013  [Invited]

  • Message from the ICWL 2013 program committee co-chairs

    Yueh Min Huang, Frederick Li, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   8167 LNCS  2013  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • 3rd international workshop on advances in semantic information retrieval

    Vitaly Klyuev, Maxim Mozgovoy, Stefano Borgo, Katarzyna Budzynska, Massimiliano Carrara, Jolanta Cybulka, Vladimir Dobrynin, Krzysztof Goczyla, Yannis Haralambous, Wladyslaw Homenda, Qun Jin, Janusz Kaczmarek, Tuomo Kakkonen, Piotr Kulicki, Cristian Lai, Sabina Leonelli, Simone Ludwig, Jacek Martinek, Nikolay Mirenkov, Ahsan Morshed, Grzegorz J. Nalepa, Raúl Palma, Maciej Piasecki, Evgeny Pyshkin, Marek Reformat, Roman Shtykh, Larisa Soldatova, Mari Carmen Suárez De Figueroa Baonza, T. Tadeusiewicz, Robert Trypuz, Miroslav Vacura, Eloisa Vargiu, Alexander Vazhenin, Haofen Wang, Shih Hung Wu, Slawomir Zadrozny, Agnieszka Lawrynowicz

    2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013     241  2013  [Invited]

  • Special issue on technology-enhanced social learning

    Chengjiu Yin, Xinyou Zhao, Qun Jin

    International Journal of Distance Education Technologies   11 ( 1 )  2013.01  [Invited]

    Authorship：Last author

  • Integration of range-based and range-free localization algorithms in wireless sensor networks for mobile clouds

    Yufeng Wang, Qun Jin, Jianhua Ma

    Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013     957 - 961  2013  [Refereed]

    　View Summary

    Usually, in mobile server cloud computing (MSCC) environments, there exist enormous sensors conducting various tasks. Localization of sensor nodes using the technologies in Wireless Sensor Network (WSN) is critical to both cloud infrastructure operations and most applications. Specifically, in WSN, Malguki (the method's name, Malguki, means 'spring') is an effective range-based algorithm which can compute the location of a node using noisy distance estimations. However, through simulation, we found that, in original Malguki algorithm that uses an iterative process to locate unknown nodes, the initial positions of unknown nodes in iteration are evenly and randomly selected, which may cause large average localization error. Considering the mentioned weak point, this paper proposes to enhance the Malguki with a simple range-free Centroid localization algorithm, which intentionally obtains initial positions of unknown nodes in iteration by Centroid algorithm. Simulation results show that the integration of range-based and range-free localization algorithm, Centroid Malguki always performs better than original Malguki algorithm. © 2013 IEEE.

    DOI

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    18
    Citation
    (Scopus)

  • Erratum: Effective session key distribution for secure fast handover in mobile networks (Telecommunication Systems (DOI 10.1007/s11235-009-9219-0))

    Jong Hyuk Park, Qun Jin

    Telecommunication Systems   52 ( 1 ) 359  2013.01  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • An adaptively emerging mechanism for context-aware service selections regulated by feedback distributions

    Yishui Zhu, Qun Jin

    Human-centric Computing and Information Sciences   2 ( 1 ) 1 - 15  2012.12  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    15
    Citation
    (Scopus)

  • Special Issue on Multidisciplinary Emerging Networks and Systems Foreword

    Qun Jin, Yufeng Wang

    JOURNAL OF COMPUTER AND SYSTEM SCIENCES   78 ( 6 ) 1671 - 1672  2012.11  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • Socialized ubiquitous personal study: Toward an individualized information portal

    Hong Chen, Xiaokang Zhou, Qun Jin

    JOURNAL OF COMPUTER AND SYSTEM SCIENCES   78 ( 6 ) 1775 - 1792  2012.11  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • Organic Stream: Meaningfully Organized Social Stream for Individualized Information Seeking and Knowledge Mining

    X. Zhou, J. Chen, Q. Jin, T.K. Shih

    Proc. U-Media2012 (The 5th IET International Conference on Ubi- Media Computing)    2012.08  [Refereed]

  • Goal-Driven Process Navigation for Individualized Learning Activities in Ubiquitous Networking and IoT Environments

    Jian Chen, Qun Jin, Runhe Huang

    JOURNAL OF UNIVERSAL COMPUTER SCIENCE   18 ( 9 ) 1132 - 1151  2012  [Refereed]

    Authorship：Corresponding author

  • AB-Chord: an efficient approach for resource location in structured P2P networks

    Yufeng Wang, Xiangming Li, Qun Jin, Jianhua Ma

    2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INTELLIGENCE & COMPUTING AND 9TH INTERNATIONAL CONFERENCE ON AUTONOMIC & TRUSTED COMPUTING (UIC/ATC)     278 - 284  2012  [Refereed]

    　View Summary

    Recently, P2P (Peer-to-Peer) technology has witnessed a rapid development. Basically, one of key components in successful P2P applications is how to efficiently look up resources. Considering that structured P2P is a relatively efficient way to locate resources, this paper conducted two improvements to increase the search efficiency in Chord-based algorithms, one of the most popular structured P2P resource lookup protocols. In detail, our contributions are twofold. First, considering the fact that routing information in Chord is not abundant enough for efficient resource search, and looking up resource can only be enforced in clockwise direction, a new algorithm called AB-Chord is proposed to reconstruct the finger tables in Chord, in which counter-clockwise finger table is added to achieve resource queries in both directions, and the density of neighboring fingers is increased. Additionally, AB-Chord implements a new operation to remove the redundant fingers introduced by adding fingers in AB-Chord. Experimental results show that AB-Chord's query efficiency has been improved in terms of the average lookup hops and average lookup delay. And furthermore, considering that the proposed AB-Chord algorithm enlarged the finger table which may cause the forwarding-storm of routing maintenance messages, we further propose AB-Chord+, which appropriately extends the periodic time of updating finger tables and makes the joining and leaving nodes actively send updating messages, to reduce the number of messages forwarded in the network. Simulated results show that AB-Chord+ reduced the network bandwidth consumption.

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Attachment factor in user experience over a time span: Experiment design and analysis

    Shinichiro Kajiwara, Qun Jin

    ACM International Conference Proceeding Series     45 - 50  2012  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012: Preface

    Xiaohong Jiang, Qun Jin, Hong Liu, Shaozi Li

    Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012   2  2012  [Refereed]  [Invited]

    DOI

    Scopus

  • Welcome message from the HumanCom 2012 general chairs

    Qun Jin, Martin Sang Soo Yeo, Bin Hu

    Lecture Notes in Electrical Engineering   182 LNEE  2012  [Invited]

    Authorship：Lead author

  • User-centric integrated recommendation by gradual adaptation based on focus of interests and its transition

    Jian Chen, Xiaokang Zhou, Qun Jin

    Proceedings - 2012 IEEE 12th International Conference on Computer and Information Technology, CIT 2012     435 - 441  2012  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Message from MENS-12 symposium chairs

    Yoshiaki Kakuda, Yufeng Wang, Jianhua Ma, Qun Jin, Zhingming Cai, Chin-Chih Chang, Yinong Chen, Felicita Di Giandomenico, Juergen Dunkel, Xinxin Fan, Cheng Fu, Ruijun He, Teresa Higuera, Eitaro Kohno, Runhe Huang, Ruidong Li, Miroslaw Malek, Tomoyuki Ohta, Yizhi Ren, Achim Rettberg, Kenichi Takahashi, Athanasios V. Vasilakos, Feng Xia, Baoliu Ye, Deqing Zou

    Proceedings - IEEE 9th International Conference on Ubiquitous Intelligence and Computing and IEEE 9th International Conference on Autonomic and Trusted Computing, UIC-ATC 2012     xl - xli  2012  [Invited]

    DOI

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  • On studying relationship between altruism and the psychological phenomenon of self-deception in rational and autonomous networks

    Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

    Proceedings - 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012     336 - 341  2012  [Refereed]

    　View Summary

    In open networking environments, resources, services, strategies and actions are voluntarily provided, maintained, chosen and determined by independent, rational and autonomous peers. Basically, Game theory is a basic tool for modeling choices by rational agents in those environments, which, usually assumes players choose strategies which maximize utility of game outcomes given their beliefs about what others players will do. This means that the most challenging question is often how beliefs are formed. Intuitively, beliefs depend not only on what people know to be true, but also on what they want to be true (desire). This paper introduces a model of rational choices that allows for this possibility that peers' beliefs are affected by their interests (desires), and, based on this model, analyzes the impact of psychological belief (optimistic bias and pessimistic bias) on the existing altruism-based cooperative mechanisms in Peer-to-Peer (P2P) systems. We found that, when there exist free riders, on the contrary to the intuitive thought, pessimistic bias of belief on contribution level can facilitate the P2P systems to converge to the stable equilibrium in easier way than optimistic bias. © 2012 IEEE.

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Message from the Third International Workshop on Future Information System Technologies and Applications (FISTA 2012) chairs

    Bernady O. Apduhan, Jianhua Ma, Qun Jin

    Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012     xxix  2012  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • Knowledge organization aided by eye-tracking in a social media enhanced learning environment

    Xiaokang Zhou, Guangyu Piao, Qun Jin

    Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012   1   6 - 10  2012  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • User correlation discovery and dynamical profiling based on social streams

    Xiaokang Zhou, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7669   53 - 62  2012  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Learning activity sharing and individualized recommendation based on dynamical correlation discovery

    Xiaokang Zhou, Jian Chen, Qun Jin, Timothy K. Shih

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7558   200 - 206  2012  [Refereed]

    Authorship：Corresponding author

    DOI

    Scopus

  • A human-centric integrated approach to web information search and sharing

    Roman Y Shtykh, Qun Jin

    Human-centric Computing and Information Sciences   1 ( 1 ) 1 - 37  2011.12  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    49
    Citation
    (Scopus)

  • Pervasive Learning Tools and Technologies

    Neil Y. Yen, Qun Jin, Hiroaki Ogata, Timothy K. Shih, Y. Yano

    Pervasive Computing and Networking     37 - 50  2011.06  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Message from the CPSCom 2011 workshop chairs

    Qun Jin, Alvin Chin, Yan Zhang

    Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011     28  2011  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • A multiple response approach for adaptive learning service with context-based multimedia contents

    Xinyou Zhao, Qun Jin, Toshio Okamoto

    Lecture Notes in Electrical Engineering   102 LNEE   269 - 280  2011  [Refereed]

    DOI

    Scopus

  • Constructing robust digital identity infrastructure for future networked society

    Jianming Yong, Sanjib Tiwari, Xiaodi Huang, Qun Jin

    Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2011     570 - 576  2011  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A service-oriented architecture for context-aware ubiquitous learning delivery

    Xinyou Zhao, Qun Jin

    Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011   4   2461 - 2465  2011  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Foreword

    Qun Jin

    Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures    2011  [Invited]

    Authorship：Lead author

    DOI

    Scopus

  • CAPK: A learning process model for web 2.0 technology enhanced community of practice

    Haifeng Man, Hong Chen, Yan Wu, Qun Jin

    Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011     546 - 551  2011  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A hybrid P2P search engine for social learning

    Ashraf Uddin Ahmed, Tanvir Shahid, Hong Chen, Qun Jin

    Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011     564 - 569  2011  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Goal-driven navigation for learning activities based on process optimization

    Jian Chen, Haifeng Man, Qun Jin, Runhe Huang

    Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011     389 - 395  2011  [Refereed]

    　View Summary

    This paper describes an integrated approach to provide an optimized learning process to students by analyzing the log data of learning activities and extracting their learning patterns. Our analysis results show that most of students almost always use their main learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimize the process of learning actions using the extracted learning patterns, infer the learning goal of students, and then navigate them a personalized learning process according to the similarity of the extracted learning patterns. © 2011 IEEE.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Enabling open learning process with learning activity streams: Model, metaphor and specification

    Haifeng Man, Hong Chen, Jian Chen, Xiaokang Zhou, Yan Wu, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7048   233 - 242  2011  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Automated lecture template generation in CORDRA-based learning object repository

    Neil Y. Yen, Timothy K. Shih, Qun Jin, Li-Chieh Lin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7048   295 - 304  2011  [Refereed]

    　View Summary

    Sharing resources and information on Internet has become an important activity for education. The MINE Registry, a branch of distributed repository, inherited the architecture of CORDRA has been developed for storing and sharing Learning Objects. Following the usage experiences, especially those being utilized to generate the lecture, the interaction structure is defined to clarify the relationships among Learning Objects. The methods to social network analysis are applied to quantify the implicit correlations and to evaluate the interdependency. In addition, an intelligent mining algorithm is proposed to explore the developed interaction structure and automatically generates lecture templates corresponding to the query criteria. The concentration of this study is to facilitate the complex and time-consuming process of creating lectures through a simple search mechanism. The implemented system has demonstrated the preliminary results and the feasibility are also revealed by the evaluation results. © 2011 Springer-Verlag.

    DOI

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  • Automatic learning sequence template generation for educational reuse

    Neil Y. Yen, Qun Jin, Timothy K. Shih, Li-Chieh Lin

    Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011     773 - 778  2011  [Refereed]

    　View Summary

    Sharing resources and information on Internet has become an important activity for education. The learning object repository has been developed to achieve efficient management of learning objects. Following usage experiences of learning objects collected in the past, this study concentrates on investigating implicit information between learning objects. We define a social structure for identifying relationship between learning objects and define a set of metrics to evaluate the interdependency. The structure identifies usage experiences and can be graphed in terms of implicit and explicit relations among learning objects. As a practical contribution, an adaptive algorithm is proposed to mine the social structure. The algorithm generates adaptive learning sequence by identifying possible interactive search input and assists them in completing self-paced learning situation. © 2011 IEEE.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Discovery of implicit correlation between shared information in an open environment

    Neil Y. Yen, Qun Jin

    MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - ACM International Workshop on Multimedia Technologies for Distance Learning, MTDL'11     43 - 46  2011  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Flowable services: A human-centric framework toward service assurance

    Qun Jin, Yishui Zhu, Roman Y. Shtykh, Neil Y. Yen, Timothy K. Shih

    Proceedings - 2011 10th International Symposium on Autonomous Decentralized Systems, ISADS 2011     653 - 658  2011  [Refereed]

    　View Summary

    Service computing aims to provide IT and computing resources to users in a way that it simply serves them. However, many issues remain in, such as portability, interoperability, and heterogeneity of diverse services, in addition to service modeling, creation, deployment, discovery, recommendation, composition, and delivery, in order to provide a service that best fits user needs and contexts at the time. In this study, we propose a new model of flowable services. Its primary purpose is to realize seamless integration and provision of diverse services in an intuitive "flowable" way maximally close to the "flow" of users' activities and thoughts, and as pertinent as possible to their needs, thus gain the most satisfaction. In this paper, we propose and discuss a human-centric framework of flowable services toward service assurance. We further describe the evaluation of the model, and an application scenario for adaptive delivery of personalized learning service under the proposed framework.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Adaptive object re-ranking mechanism for ubiquitous learning environment

    Neil Y. Yen, Timothy K. Shih, Qun Jin, Jason C. Hung, Qingguo Zhou, Louis R. Chao

    Journal of Multimedia   6 ( 2 ) 129 - 138  2011  [Refereed]

    　View Summary

    Ubiquitous Learning (U-Learning), as an emerging learning paradigm, makes it possible for learners to carry out the learning activities at any places and at anytime. With the advantages of the devices, learners can obtain a variety of supplementary materials from the Internet. In the scope of distance learning, LOR (Learning Object Repository) stands for managing and sharing of learning related materials (known as learning objects). However, some challenges may raise while performing these activities. For instance, a huge amount of learning objects may appear while learners utilize the search service provided by LOR. Learners have to spend time on collecting relevant resources for specific purposes. This situation may discourage the reusability of learning objects especially in a ubiquitous environment. In this paper, based on systematic re-examination of reuse scenarios, an adaptive mechanism, as a resource discovery and search middleware, was proposed to assist learners in obtaining possible objects under ubiquitous environment. Achievement of the proposed mechanism can produce search results adaptive to specific situations in order of similarity degree based on the mixed information. We try to filter out some irrelevant results by using the past usage history, current geographical information and input query, so as to enhance the efficiency of learning objects retrieval in a ubiquitous environment. As a pilot test, Apple iPhone was utilized to be the major client testbed. © 2011 Academy Publisher.

    DOI

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    7
    Citation
    (Scopus)

  • Generating associative ripples of relevant information from a variety of data streams by throwing a heuristic stone

    Xiaokang Zhou, Hong Chen, Qun Jin, Jianming Yong

    Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011    2011  [Refereed]

    　View Summary

    Recently, the vast dialog in the microblog, such as twitter, Facebook has become increasingly popular. As we post more messages in microblogs, information is spreading more quickly and widely. These widely spread and diversified contents could be viewed as data streams, which have become an important part of the Internet resources. However, these separated data streams are littery and meaningless, so we need to collect and organize them together to provide us with meaningful information. It is hard to imagine that we could find useful information by simply inputting a few keywords into a search engine in such a stream environment. In this study, we try to find a way to seek the information related to users' personal and current interests and needs among these data streams and provide users with other more relevant information. We introduce a set of metaphors to represent a variety of data streams in different levels, and define two new metaphors: heuristic stone and associative ripple to assist the seeking process and describe the results. Based on these, we further propose two algorithms for the information seeking and processing, and discuss a scenario of the information seeking process that utilizes the proposed metaphors and algorithms. Copyright 2011 ACM.

    DOI

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  • Dynamical user networking and profiling based on activity streams for enhanced social learning

    Xiaokang Zhou, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7048   219 - 225  2011  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Organizing learning stream data by eye-tracking in a blended learning environment integrated with social media

    Xiaokang Zhou, Guangyu Piao, Qun Jin, Runhe Huang

    ITME 2011 - Proceedings: 2011 IEEE International Symposium on IT in Medicine and Education   2   335 - 339  2011  [Refereed]

    　View Summary

    In this study, we integrate social media into the blended learning environment, and further delve into utilizing the eye-tracking technology to enhance learning to be socialized and more efficient. We propose an approach to employ eye-tracking to extract those related learning stream data according to different seeking patterns in a learning process. Based on these, we go further to organize these raw stream data into meaningful learning contents in accordance with specific tasks in order to benefit both teachers and students, which can assist the learning process and promote the learning efficiency in the blended learning environment. © 2011 IEEE.

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Effective session key distribution for secure fast handover in mobile networks

    Jong Hyuk Park, Qun Jin

    TELECOMMUNICATION SYSTEMS   44 ( 1-2 ) 97 - 107  2010.06  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Evaluation of Drowsiness during Driving based on Heart Rate Analysis - a driving simulation study

    Masaru Tasaki, Hui Wang, Motoaki Sakai, Mai Watanabe, Qun Jin, Daming Wei

    2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW)     411 - 416  2010  [Refereed]

    　View Summary

    t is a common sense that drowsiness during driving could cause traffic accidents. Related researches show that drowsiness occurs when the parasympathetic nerve system predominates over others, and the high frequency (HF) component of heart rate variability (HRV) on an electrocardiogram (ECG) is closely related with the parasympathetic nerve activity, so it is reasonable to evaluate drowsiness based on heart rate analysis. In the driving simulation study, ECG and calculated R-R intervals were put on record during the monitoring process of drowsiness degrees. Relations among different indexes, such as, temporal change of HF band, RR50, Coefficient of Variation of R-R interval (CVRR), and LF to HF ratio (LF/HF) were evaluated as well. The experimental results suggest that there exist certain correlations between drowsiness and HF, RR50, CVRR, or LF/HF, which will be compared in the future with data collected in real driving experiments.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Dynamic Navigation for Personalized Learning Activities Based on Gradual Adaption Recommendation Model

    Jian Chen, Haifeng Man, Neil Y. Yen, Qun Jin, Timothy K. Shih

    ADVANCES IN WEB-BASED LEARNING-ICWL 2010   6483   31 - +  2010  [Refereed]

    　View Summary

    This study aims to provide learners with appropriate learning activities navigation based on a learning process recommendation system that gradually adapts to their needs. A learning activity consists of a series of purposeful learning actions with a specific sequence. In the system, user profile is generated from various learning related activities that are collected over different time spans. A dynamic user group is generated based on the similarity of user profiles which have had successful learning experience, and can be used to create a personalized navigation of learning activities for a target learner. In this paper, after introducing how to create a dynamic design of learning activities navigation, we focus on discussing the design and implementation issues of the prototype system for personalized learning support.

    DOI

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    8
    Citation
    (Scopus)

  • Open Learning: A Framework for Sharable Learning Activities

    Haifeng Man, Hong Chen, Qun Jin

    ADVANCES IN WEB-BASED LEARNING-ICWL 2010   6483   387 - 392  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • A novel WYSIWYG approach for generating cross-Browser web data

    Jin Zhu, Xiao Liu, Yoshiyori Urano, Qun Jin

    Proceedings - 2010 10th International Conference on Computational Science and Its Applications, ICCSA 2010     155 - 164  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Shift to Cyber-I: Reexamining personalized pervasive learning

    Neil Y. Yen, Qun Jin, Jianhua Ma, Runhe Huang, Timothy K. Shih

    Proceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010     685 - 690  2010  [Refereed]

    　View Summary

    Recently, there have been lots of researches on how to provide personalized services to different users according to their personal characters, needs, situations, contexts and so on. Such personalized services are often based on users' profiles provided by the users in the beginning, and users' records or experiences in using corresponding systems in certain periods. However, different systems or terminals collect user information independently and cannot share the user's personal information collected by these different systems/terminals. As a result, each system can only utilize the limited information collected by the system itself to provide services or recommendations, and it thus cannot meet what users' needs in varied situations across the different systems/terminals. Therefore, it is still an open issue on how to gather, share and utilize various kinds of personal information to effective personalized services in right time, right place and right means to users. In this paper, a case study for personalized pervasive learning is discussed as one typical application of the concept of Cyber-I, an individual's counterpart on the cyberspace. The Cyber-I aims to provide a better environment for users to obtain what they may really need on the Web, and it can be considered as an innovated possibility of web usage scenario in the near future. Our case study using pervasive devices (iPad, cell phone, and laptop) for learning issues can be regarded as the best practice to support the proposed Cyber-I. © 2010 IEEE.

    DOI

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    6
    Citation
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  • A framework of organic streams: Integrating dynamically diversified contents into ubiquitous personal study

    Hong Chen, Xiaokang Zhou, Haifeng Man, Yan Wu, Ashraf Uddin Ahmed, Qun Jin

    Proceedings - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC 2010 and ATC 2010 Conferences, UIC-ATC 2010     386 - 391  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Preface of MENS'10: The 2nd International Symposium on Multidisciplinary Emerging Networks and Systems

    Yufeng Wang, Goutam Chakraborty, Kuan-Ching Li, Tadashi Dohi, Mieso Denko, Ma. Jianhua, Qun Jin

    Proceedings - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC 2010 and ATC 2010 Conferences, UIC-ATC 2010     xxxv - xxxvi  2010  [Invited]

    Authorship：Last author

    DOI

    Scopus

  • A new paradigm of ranking & searching in learning object repository

    Neil Y. Yen, Timothy K. Shih, Qun Jin

    MTDL'10 - Proceedings of the 2010 ACM Workshop on Multimedia Technologies for Distance Leaning, Co-located with ACM Multimedia 2010     1 - 6  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Harnessing user contexts to enable flowable services model

    Yishui Zhu, Roman Y. Shtykh, Qun Jin

    2010 3rd International Conference on Human-Centric Computing, HumanCom 2010    2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A re-examination of ranking metrics for Learning Object repository

    Neil Y. Yen, Ying-Hong Wang, Qun Jin, David J.T. Yang

    2010 3rd IEEE International Conference on Ubi-Media Computing, U-Media 2010     91 - 94  2010  [Refereed]

    　View Summary

    In line with the popularity of Internet and the development of search engine, users request information through Web-based services. Although general purpose searching such as one provided by Google is powerful, searching mechanism for specific purposes could rely on metadata. We followed SCORM and CORDRA specifications to develop a registry system, called the MINE Registry, for storing and sharing 20,738 Learning Objects created in the past five years. As a contribution, we propose the concept of "Reusability Tree" to represent the relationships among relevant Learning Objects and to enhance CORDRA. We further collect relevant information while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from community users are also considered as critical elements for evaluating significance degree of Learning Objects. Through these factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories. © 2010 IEEE.

    DOI

    Scopus

  • Provision of flowable services in cloud computing environments

    Yishui Zhu, Roman Y. Shtykh, Qun Jin

    2010 5th International Conference on Future Information Technology, FutureTech 2010 - Proceedings    2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • An agent based approach for promoting interactive teaching and active learning

    Runhe Huang, Jianhua Ma, Qun Jin

    2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010     349 - 354  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • An integrated system to assist personalized learning based on gradual adaption recommendation model

    Jian Chen, Qun Jin, Jianhua Ma, Runhe Huang

    2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010     300 - 306  2010  [Refereed]

    　View Summary

    This study presents an integrated adaptive system to support and facilitate individual learning based on a recommendation model that gradually adapts to a learner's needs and information access behaviors, including various learning related activities, over different time spans. In this paper, we focus on describing the integrated framework and discussing the design and implementation issues of the prototype system for personalized learning support. ©2010 IEEE.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Putting adaptive granularity and rich context into learning objects

    Haifeng Man, Qun Jin

    2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010     140 - 145  2010  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Trend of e-learning: The service mashup

    Neil Y. Yen, Timothy K. Shih, Qun Jin, Hui-Huang Hsu, Louis R. Chao

    International Journal of Distance Education Technologies   8 ( 1 ) 69 - 88  2010.01  [Refereed]

    　View Summary

    With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack interoperability. The only way to reuse these applications is to redevelop them for specific purposes. In order to solve this situation and norm the various learning resources, IMS proposes a new e-learning standard named "Common Cartridge". This standard not only integrates the past e-learning standards like LOM, SCORM and QTI but also proposes a technical architecture called Learning Tools Interoperability to allow applications to reuse different systems without reprogramming. In this paper, we firstly introduce the current e-learning environment. Then we pay attention on the usage of Common Cartridge standards and discuss the architecture of Learning Tools Interoperability. According to these standards, we will point out the e-learning standard that might be widely utilized in the future. Copyright © 2010, IGI Global.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Ubiquitous Personal Study: a framework for supporting information access and sharing

    Hong Chen, Qun Jin

    PERSONAL AND UBIQUITOUS COMPUTING   13 ( 7 ) 539 - 548  2009.10  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • Specification, standards and information management for distributed systems

    Irfan Awan, Qun Jin, Kuo-Ming Chao

    COMPUTER STANDARDS & INTERFACES   31 ( 5 ) 869 - 869  2009.09  [Invited]

    DOI

    Scopus

  • Dynamically constructing user profiles with similarity-based online incremental clustering

    Roman Y. Shtykh, Qun Jin

    International Journal of Advanced Intelligence Paradigms   1 ( 4 ) 377 - 397  2009.06  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Integrating Search and Sharing: User-Centric Collaborative Information Seeking

    Roman Y. Shtykh, Qun Jin

    PROCEEDINGS OF THE 8TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE     388 - +  2009  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Resource Retrieval Service to Enhance U-Learning Environment

    Neil Y. Yen, Louis R. Chao, Qun Jin, Jianhua Ma, Timothy K. Shih

    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INFORMATION TECHNOLOGIES & APPLICATIONS (ICUT 2009)     365 - +  2009  [Refereed]

    　View Summary

    E-Learning makes it possible for learners to study at any time. With the improvement of ubiquitous technologies and corresponding devices, learners can conduct their learning activities without any limitations from the environment. Instructors can utilize various kinds of resources to create more plentiful learning materials for learners. In this situation, instructors or learners have to spend more time on collecting relevant resources for a specific purpose. In our previous works, we utilized the geographical information and RFID (Radio Frequency Identification) to develop an outdoor adventure game to support learning procedures. In this paper, we go further to propose and develop a resource retrieval mechanism to assist learners in collecting relevant learning resources. This mechanism can be regarded as a search procedure. We aim at providing search results in the order of relevant degree based on learners' current geographical information. It can make resource retrieval more efficient in ubiquitous learning environments.

    DOI

    Scopus

  • A Context-Aware Framework for Flowable Services

    Roman Y. Shtykh, Yishui Zhu, Qun Jin

    THIRD INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING (MUE 2009)     251 - +  2009  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Preface of MANS'09

    Yufeng Wang, Kuan Ching Li, Qun Jin, Hongbo Zhu, Jianhua Ma

    UIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences    2009  [Invited]

    DOI

    Scopus

  • A flowable service model for seamless integration of services

    Yishui Zhu, Roman Y. Shtykh, Qun Jin, Jianhua Ma

    Proceedings of the IASTED International Conference on Advances in Computer Science and Engineering, ACSE 2009     199 - 204  2009  [Refereed]

  • Information sharing across diverse media platforms with reconfigurable user grouping

    Roman Y. Shtykh, Qun Jin, Guozhen Zhang, Runhe Huang

    Proceedings of the IASTED International Conference on Advances in Computer Science and Engineering, ACSE 2009     89 - 94  2009  [Refereed]

  • Message from the 2CCom 2009 symposium chairs

    Albert Zomaya, Qun Jin, Bharat K. Bhargava, Naixue Xiong, Sang Soo Yeo

    Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009   2  2009  [Invited]

    DOI

    Scopus

  • Message from the PICom-09 chairs

    William Zhu, Qun Jin, Alessio Vecchio, Mingtian Zhou, Ajith Abraham, Hussein Mouftah, Jianhua Ma, Laurence T. Yang

    8th IEEE International Symposium on Dependable, Autonomic and Secure Computing, DASC 2009     xxi - xxii  2009  [Invited]

    DOI

    Scopus

  • A web recommender system based on dynamic sampling of user information access behaviors

    Jian Chen, Roman Y. Shtykh, Qun Jin

    Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009   2   172 - 177  2009  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A user location-aware music playing system

    Youhei Katori, Jianhua Ma, Tomomi Kawashima, Bernady O. Apduhan, Runhe Huang, Qun Jin

    UIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences     377 - 382  2009  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • A tree-structured intelligence entity pool and its sharing among ubiquitous objects

    Runhe Huang, Jianhua Ma, Qun Jin

    Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009   2   318 - 325  2009  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Improving Mobile Web Search Experience with Slide-Film Interface

    Roman Y. Shtykh, Qun Jin

    SITIS 2008: 4TH INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGY AND INTERNET BASED SYSTEMS, PROCEEDINGS     659 - +  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Inferring User Interests from Relevance Feedback with High Similarity Sequence Data-Driven Clustering

    Roman Y. Shtykh, Qun Jin

    PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON UNIVERSAL COMMUNICATION     390 - +  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Harnessing user contributions and dynamic profiling to better satisfy individual information search needs

    Roman Y. Shtykh, Qun Jin

    INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES   4 ( 1 ) 63 - 79  2008  [Refereed]

    Authorship：Last author, Corresponding author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Implementation of Ubiquitous Personal Study Using Web 2.0 Mash-up and OSS Technologies

    Hong Chen, Nozomi Ikeuchi, Qun Jin

    2008 22ND INTERNATIONAL WORKSHOPS ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOLS 1-3     1573 - 1578  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Slide-film interface: Overcoming small screen limitations in mobile web search

    Roman Y. Shtykh, Jian Chen, Qun Jin

    ADVANCES IN INFORMATION RETRIEVAL   4956   622 - +  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Robots in smart spaces - A case study of a u-object finder prototype

    Tomomi Kawashima, Jianhua Ma, Bernady O. Apduhan, Runhe Huang, Qun Jin

    UBIQUITOUS INTELLIGENCE AND COMPUTING, PROCEEDINGS   5061   61 - +  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Modeling and analyzing individual's daily activities using lifelog

    Katsuhiro Takata, Jianhua Ma, Bernady O. Apduhan, Runhe Huang, Qun Jin

    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS     503 - +  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    16
    Citation
    (Scopus)

  • Message from the UASS 2008 chairs

    Jong Hyuk Park, Laurence T. Yang, Jianhua Ma, Qun Jin, Hangbae Chang

    Proceedings - International Conference on Advanced Information Networking and Applications, AINA     73  2008  [Invited]

    DOI

    Scopus

  • IMIS 2008 message from the workshop organizers MUE 2008

    Seong Moo Yoo, Bonam Kim, Hui Huang Hsu, Ilsun You, Jong Hyuk Park, Minyi Guo, Ching Hsien Hsu, David Simplot-Ryl, Edwin H.M. Sha, Hai Jin, Javier Lopez, Shu Ching Chen, Tatsuya Yamazaki, Junmo Yang, Wen Tzeng Huang, Akiyo Nadamoto, Chengcui Zhang, Ching Sheng Wang, Chunming Rong, Frode Eika Sandnes, Geyong Min, Howard Leung, Hyobeom Ahn, Hyunju Kim, Indrakshi Ray, Isabelle Simplot-Ryl, Ismail Khalil Ibrahim, Javier García-Villalba, Jemal H. Abawajy, Jinhua Guo, Jon Youn, Kouichi Sakurai, Kuei Ping Shih, Lawrence Y. Deng, Mei Ling Shyu, Mohammad Al-Shurman, Oh Heum Kwon, Pedro M. Ruiz, Pilar Herrero, Q. Shi, Qun Jin, Seungjin Park, Sang Hyuk Son, Whai En Chen, Witold Pedrycz, Xiaofeng Chen, Yin Fu Huang

    Proceedings - 2008 International Conference on Multimedia and Ubiquitous Engineering, MUE 2008    2008  [Invited]

    DOI

    Scopus

  • Capturing user contexts: Dynamic profiling for information seeking tasks

    Roman Y. Shtykh, Qun Jin

    Proc. - The 3rd Int. Conf. Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: Int. Conf. Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services     365 - 370  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    15
    Citation
    (Scopus)

  • Proceedings - 2008 IEEE Congress on Services, SERVICES 2008: Message from SCCM 2008 Chairs

    Mika Ylianttila, Jin Qun, Minyi Guo, Heming Zhang, Zhixiong Chen, Jukka Riekki, Jiehan Zhou, Mika Rautiainen

    Proceedings - 2008 IEEE Congress on Services, SERVICES 2008   PART2  2008  [Invited]

    DOI

    Scopus

  • Gradual adaption model for estimation of user information access behavior

    Jian Chen, Roman Y. Shtykh, Qun Jin

    Proc. - The 3rd Int. Conf. Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: Int. Conf. Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services     378 - 383  2008  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Enhancing IR with user-centric integrated approach of interest change driven layered profiling and user contributions

    Roman Y. Shtykh, Qun Jin

    Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07   2   240 - 245  2007  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Ubisafe computing: Vision and challenges (I)

    Jianhua Ma, Qiangfu Zhao, Vipin Chaudhary, Jingde Cheng, Laurence T. Yang, Runhe Huang, Qun Jin

    AUTONOMIC AND TRUSTED COMPUTING, PROCEEDINGS   4158   386 - 397  2006  [Refereed]

    Authorship：Last author

  • Scalable information sharing utilizing decentralized P2P networking integrated with centralized personal and group media tools

    Guozhen Zhang, Qun Jin

    20TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 2, PROCEEDINGS   2   707 - +  2006  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Enhancing ontology-based context modeling with temporal vector space for ubiquitous intelligence

    Shermann S. M. Chan, Qun Jin

    20TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 1, PROCEEDINGS   1   669 - +  2006  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Collaboratively shared information retrieval model for e-learning

    Shermann S. M. Chan, Qun Jin

    ADVANCES IN WEB BASED LEARNING - ICWL 2006   4181   123 - 133  2006  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Message from CAUL 2006 Workshop Organizers

    Shian Shyong Tseng, Kinshuk, Stephen J.H. Yang, Gwo Jen Hwang, Nian Shing Chen, Mohamed Ally, Johnny Biström, Jan Brase, William C.C. Chu, Jen Yao Chung, Francis C.M. Lau, Kuo En Chang, Gwo Dong Chen, Ming Syan Chen, Irene Chen, Shih Wei Chou, Andrea Detti, Claus Eikemeier, Jun H. Jo, Yueh Min Huang, Qun Jin, Vicki Jones, Soraya Kouadri Most'efaoui, Jaakko Kurhila, Stefano Levialdi, Sheng Tun Li, Anthony Y.H. Liao, Pierpaolo Loreti, Kiyoshi Nakabayashi, Haruo Nishinosono, Caoimhín O'Nualláin, Timothy K. Shih, Charles A. Shoniregun, Marten J. Van Sinderen, Judy C.R. Tseng, David Yang, Yao Ming Yeh, Pao Ta Yu, Jia Zhang, Rick Chen, Angus Huang, Jeff Huang, Blue Lan, Norman Shao, Addison Su, Jun Ming Su, Jui Feng Weng

    Proceedings - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing   2006 I  2006  [Invited]

    DOI

    Scopus

  • A survey of distance education challenges and technologies

    Timothy K. Shih, Jason C. Hung, Jianhua Ma, Qun Jin

    Future Directions in Distance Learning and Communication Technologies   1 ( 1 ) 1 - 25  2006  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Design of bookmark-based information space to support exploration and rediscovery

    Roman Y. Shtykh, Jin Qun

    Proceedings - Sixth IEEE International Conference on Computer and Information Technology, CIT 2006    2006  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Peer-to-peer solution to support group collaboration and information sharing

    Roman Shtykh, Guozhen Zhang, Qun Jin

    International Journal of Pervasive Computing and Communications   1 ( 3 ) 187 - 198  2005  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Research on collaborative service solution in ubiquitous learning environment

    GZ Zhang, Q Jin

    PDCAT 2005: Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, Proceedings   2005   804 - 806  2005  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    11
    Citation
    (Scopus)

  • Ubiquitous learning on pocket SCORM

    HP Chang, WC Chang, YL Sie, NH Lin, CH Huang, TK Shih, Q Jin

    EMBEDDED AND UBIQUITOUS COMPUTING - EUC 2005 WORKSHOPS, PROCEEDINGS   3823   171 - 179  2005  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Peer-to-peer based social interaction tools in ubiquitous learning environment

    GZ Zhang, Q Jin, TK Shih

    11th International Conference on Parallel and Distributed Systems, Vol I, Proceedings   1   230 - 236  2005  [Refereed]

    　View Summary

    This paper discusses a fundamental notion and model of ubiquitous computing technology support learning (uLearning) system. In order to increase learners' social skills and support social interaction among learners, the authors design a collection of support tools; these tools serve for three processes: encounter communication and collaboration. Furthermore, prototyping implementation of the social interaction support tools is introduced.

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • A framework of social interaction support for ubiquitous learning

    GZ Zhang, Q Jin, M Lin

    AINA 2005: 19TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 2   2   639 - 643  2005  [Refereed]

    　View Summary

    This paper describes the computer supported ubiquitous learning system and the social interaction between learners. We define the ubiquitous learning with five prime attributes, and present a generalized social interaction support model for the ubiquitous learning. Moreover in order to support learners with increasing social skill, a solution for constructing social interaction in ubiquitous learning environment is designed, which includes three major functions: encounter communication and collaboration support functions.

    DOI

    Scopus

    45
    Citation
    (Scopus)

  • Design of peer-to-peer groupware integrated with interactive browser for active information sharing and collaboration support

    R Shtykh, GZ Zhang, Q Jin

    FOURTH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, PROCEEDINGS     404 - 409  2004  [Refereed]

    Authorship：Last author

  • Multi-agent system for Online course content management

    R Komatsu, JH Ma, Q Jin

    18TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 1 (LONG PAPERS), PROCEEDINGS   1   183 - 188  2004  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • NetIsle: A hybrid peer-to-peer groupware system based on push technology for small group collaboration

    R Shtykh, Q Jin

    DATABASES IN NETWORKED INFORMATION SYSTEMS, PROCEEDINGS   2822   177 - 187  2003  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Collaborative information browser: Collecting and organizing information through group collaboration

    Qun Jin, Nobuko Furugori, Katsuyoshi Hanasaki, Norifumi Asahi, Yoshiteru Ooi

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics   6   170 - 174  2002  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Mobile Agent Platform Supports to e-Marketing

    Ying Hong Wang, Qun Jin, Shih Wel Kao, Huei Yuan Chan

    11th Golden West International Conference on Intelligent Systems 2002, ICIS 2002     143 - 148  2002  [Refereed]

  • A push-type groupware system to facilitate small group collaboration

    R. Shtykh, Qun Jin

    Proceedings - 1st International Symposium on Cyber Worlds, CW 2002     354 - 359  2002  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Individualized collaboration support for online leaning communities

    Q Jin

    INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, VOLS I AND II, PROCEEDINGS     784 - 788  2002  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

  • Peer-to-peer file sharing with integrated attribute descriptions in XML and an embedded database engine

    S Takizawa, Q Jin

    DATABASES IN NETWORKED INFORMATION SYSTEMS   2544   225 - 238  2002  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Design of a virtual community based interactive learning environment

    Q Jin

    INFORMATION SCIENCES   140 ( 1-2 ) 171 - 191  2002.01  [Refereed]  [International journal]

    Authorship：Lead author, Corresponding author

    　View Summary

    In this paper, we propose a conceptual framework for every-citizen learning communities based on a recently widespread Internet tool known as Multi-user dimension Object-Oriented (MOO). We discuss the design and development of a prototype system of the virtual community based interactive learning environment, which supports human-human communication in addition to human-computer communication. with emphasis on social interaction. (C) 2002 Elsevier Science Inc. All rights reserved.

    DOI

    Scopus

    26
    Citation
    (Scopus)

  • Design of multilingual agents for community-based collaborative virtual universities

    Q. Jin, J. Huang, Z. Y. Peng

    Journal of Shanghai University   5 ( SUPPL. SEPT. ) 248 - 253  2001.09  [Refereed]

    Authorship：Lead author

  • A shopping negotiation agent that adapts to user preferences

    Runhe Huang, Jianhua Ma, Qun Jin

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   2252   45 - 56  2001  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Computer supported social networking for augmenting cooperation

    H. Ogata, Y. Yano, N. Furugori, Q. Jin

    Computer Supported Cooperative Work   10 ( 2 ) 189 - 209  2001  [Refereed]

    Authorship：Last author

    DOI

    Scopus

    56
    Citation
    (Scopus)

  • Optimum Order Time for a Spare Part Inventory System Modeled by a Non-Regenerative Stochastic Petri Net

    JIN Qun, VIDALE Richard F., SUGASAWA Yoshio

    IEICE transactions on fundamentals of electronics, communications and computer sciences   83 ( 5 ) 818 - 827  2000.05  [Refereed]

    Authorship：Lead author

    CiNii

  • Design of a virtual community based interactive learning environment

    Q Jin

    PROCEEDINGS OF THE FIFTH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1 AND 2   5 ( 2 ) A636 - A642  2000  [Refereed]

    Authorship：Lead author

  • Proposal and Experiment of Supporting Social Networks Exploration with Past Results

    OGATA Hiroaki, YANO Yoneo, FURUGORI Nobuko, JIN Qun

    Transactions of Information Processing Society of Japan   40 ( 2 ) 632 - 641  1999.02  [Refereed]

    Authorship：Last author

    　View Summary

    The exploration of social networks is essential to find capable cooperators who can help in problem-solving and in augmenting cooperation among workers in an organization. PeCo-Mediator-II is an agent based system that helps gathering, exploring, and visualizing social networks among users. This paper proposes a user model with history logs to support exploration, to share individual knowledge, and to reduce overload of cooperators. Experimental results show that the system facilitated users encounter cooperators and helped develop new relationships between users and cooperators.

    CiNii

  • PeCo-Mediator-II:Supporting to Find Partner(s) through Personal Connections in a Networked Environment

    OGATA Hiroaki, FURUGORI Nobuko, JIN Qun, YANO Yoneo

    The transactions of the Institute of Electronics, Information and Communication Engineers   80 ( 7 ) 551 - 560  1997.07  [Refereed]

    CiNii

  • Design issues and experiences from having lessons in text-based social virtual reality environments

    Qun Jin, Yoneo Yano

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics   2   1418 - 1423  1997  [Refereed]

    Authorship：Lead author

  • Expermental Use and Evaluation of a Virtual Environment for Collaborative Learning

      14 ( 3 ) 29 - 36  1997  [Refereed]

    Authorship：Lead author

    CiNii

  • Stochastic Petri net model of an Ethernet-based manufacturing system

    Q Jin, Y Yano, Y Sugasawa

    STOCHASTIC MODELLING IN INNOVATIVE MANUFACTURING   445   46 - 57  1997  [Refereed]

    Authorship：Lead author

  • Design issues and experiences from having lessons in text-based social virtual reality environments

    Q Jin, Y Yano

    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5     1418 - 1423  1997  [Refereed]

    Authorship：Lead author

  • Non-regenerative stochastic Petri nets: Modeling and analysis

    Q Jin, Y Yano, Y Sugasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E79A ( 11 ) 1781 - 1790  1996.11  [Refereed]

    Authorship：Lead author, Corresponding author

    　View Summary

    We develop a new class of stochastic Petri net. non-regenerative stochastic Petri net (NRSPN), which allows the firing time of its transitions with arbitrary distributions, and can automatically generate a bounded reachability graph that is equivalent to a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. Thus, it can model and analyze behavior of a system whose states include some non-regeneration points. We show how to model a system by the NRSPN, and how to obtain numerical solutions For the NRSPN model. The probabilistic behavior of the modeled system can be clarified with the reliability measures such as the steady-state probability, the expected numbers of visits to each slate per unit lime, availability, unavailability and mean time between system failure. Finally, to demonstrate the modeling ability and analysis power of the NRSPN model, we present an example for a fault-tolerant system using the NRSPN and give numerical results for specific distributions.

  • Modeling and analysis of agents' probabilistic behavior by a non-regenerative Stochastic Petri net

    Q Jin, Y Yano, Y Sugasawa

    INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4   1   187 - 192  1996  [Refereed]

    Authorship：Lead author

  • Design of a supporting tool for knowledge creation

    N Furugori, Q Jin, H Ogata, Y Yano

    INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4   1   580 - 585  1996  [Refereed]

    　View Summary

    Knowledge Creation from flooding information is one of the most burdensome subject we face today. We have developed a supporting tool to create knowledge for effective use of information. As a basis of the tool, we propose a cooperative framework, where user and the system cooperate each other to derive knowledge from gathered information. After presented the structure of the tool, we illustrate two major functions with examples. First one is the systematic arrangement of knowledge and the second is the elaborated search referencing knowledge base.

  • Distributed PeCo-Mediator: Finding partners via personal connections

    H Ogata, A Goji, Q Jin, Y Yano, N Furugori

    INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4   1   802 - 807  1996  [Refereed]

  • COMES: Collaborative organizational memory system

    H Ogata, K Tsutsumi, Q Jin, Y Yano, N Furugori

    INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4   2   983 - 987  1996  [Refereed]

  • PeCo-Mediator:Development and Modelling of a Supporting System for Sharing and Handling Personal Connections

    Ogata Hiroaki, Yano Yoneo, Furugori Nobuko, Jin Qun

    IPSJ Journal   36 ( 6 ) 1299 - 1309  1995.06  [Refereed]

    Authorship：Last author

    　View Summary

    A PeCo(Personal Connection) is often a starting point for business activities. This paper describes : 1)PeCo-Mediator, which facilitates access to others who can help problem solving in business activities by sharing and using wide ranges PeCos beyond individuals, 2)its flexible database which has a flexible data-structure and key concepts "flexibility and adaptability", 3)a model of PeCos. The flexible database allows users to store their diverse personal information and to easily find people who can help solve their business problems. Use of shared PeCos through PeCo-Mediator facilitates ...

    CiNii

  • Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets

    Q. Jin, Y. Sugasawa

    Mathematical and Computer Modelling   22 ( 10-12 ) 109 - 118  1995  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

    9
    Citation
    (Scopus)

  • Analyzing system reliability using non-regenerative stochastic petri nets

    Y. Sugasawa, R. F. Vidale, Q. Jin

    IEEE Symposium on Emerging Technologies & Factory Automation   3   399 - 406  1995  [Refereed]

    Authorship：Last author

  • PeCo-Mediator: Supporting access to unknown partners for cooperation using collective personal connections - Adaptable menu-based query interface

    H OGATA, Y YANO, N FURUGORI, Q JIN

    SYMBIOSIS OF HUMAN AND ARTIFACT: FUTURE COMPUTING AND DESIGN FOR HUMAN-COMPUTER INTERACTION   20 ( C ) 397 - 402  1995  [Refereed]

    Authorship：Last author

    DOI

    Scopus

  • Modeling and analysis of reliability performance for a distributed dual-processor system

    Qun Jin, Yoshio Sugasawa

    Computers and Industrial Engineering   27 ( 1-4 ) 497 - 500  1994.09  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • COMPUTER-SUPPORTED ENVIRONMENT FOR COMMON EXPLOITATION OF PERSONAL INFORMATION

    N FURUGORI, Q JIN, H OGATA, Y YANO

    COMPUTERS & INDUSTRIAL ENGINEERING   27 ( 1-4 ) 189 - 192  1994.09  [Refereed]

    　View Summary

    Personal connections have great influences on various social activities, e.g., a business negotiation. However, data of personal connections are usually diverse, dynamic and ill-formed. In this paper, we firstly propose a model and representation for personal connections, then describe the framework to deal with ill-formed information. We discuss some key criteria on developing a common exploitation environment integrated with an adaptable data-base and user interface to support group decision. Finally, we give illustrations to show that the developed environment is effective and useful.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Extended stochastic Petri Net models for systems with parallel and cooperative motions

    Yoshio Sugasawa, Qun Jin, Koichiro Seya

    Computers and Mathematics with Applications   24 ( 1-2 ) 119 - 126  1992.07  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Behavioral Analysis and Performance Evaluation of a Cooperative Motion System Modeled by Petri Net

      33 ( 5 ) 602 - 610  1992.05  [Refereed]

    CiNii

  • 分散処理におけるシンク発生の確率モデルと挙動解析

    金 群, 菅沢 喜男, 瀬谷 浩一郎

    電子情報通信学会論文誌. A, 基礎・境界 = The IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Japanese edition). A / 電子情報通信学会 編   75 ( 3 ) p658 - 660  1992.03  [Refereed]

    Authorship：Lead author

    　View Summary

    記事分類: データ処理・計算機器

    CiNii

  • Analysis of Stochastic Petri Net model with non-exponential distributions using a generalized Markov Renewal Process

    Qun Jin, Yoshio Sugasawa, Koichiro Seya

    Microelectronics Reliability   31 ( 5 ) 933 - 939  1991  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

  • Modelling and analysis of a semaphore system by an extended stochastic petri net

    Yoshio Sugasawa, Qun Jin, Jian Ting Zhang, Koichiro Seya

    International Journal of Systems Science   22 ( 1 ) 217 - 224  1991.01  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Probabilistic behavior and reliability analysis for a multi-robot system by applying Petri net and Markov renewal process theory

    Qun Jin, Yoshio Sugasawa, Koichiro Seya

    Microelectronics Reliability   29 ( 6 ) 993 - 1001  1989  [Refereed]

    Authorship：Lead author

    DOI

    Scopus

    11
    Citation
    (Scopus)

▼display all

Books and Other Publications

  • Device-to-device based proximity service: Architecture, issues, and applications

    Yufeng Wang, Athanasios V. Vasilakos, Qun Jin

    CRC Press  2017 ISBN: 9781498724180

    　View Summary

    D2D-based proximity service is a very hot topic with great commercial potential from an application standpoint. Unlike existing books which focus on D2D communications technologies, this book fills a gap by summarizing and analyzing the latest applications and research results in academic, industrial fields, and standardization. The authors present the architecture, fundamental issues, and applications in a D2D networking environment from both application and interdisciplinary points of view.

    DOI

  • Distance Education Environments and Emerging Software Systems: New Technologies, Advances in Distance Education Technologies series

    Q. Jin( Part： Edit)

    IGI Global  2011

  • Intelligent Learning Systems and Advancements in Computer-Aided Instruction: Emerging Studies, Advances in Distance Education Technologies series

    Q. Jin( Part： Edit)

    IGI Global  2011

  • Enabling Society with Information Technology

    Q. Jin, J. Li, N. Zhang, J. Cheng, C. Yu, S. Noguchi

    Springer  2002

  • Proceedings of Sixth International Conference of Educational Innovation through Technology

    J. Liu, S. Nishimura, H. Zhang and Q. Jin (Eds.)

    IEEE Computer Society CPS  2017

  • Proceedings of IEEE DASC-PICom-DataCom-CyberSciTec 2016

    K. Wang, Q. Jin

    IEEE Computer Society CPS  2016

  • Proceedings of Fifteenth International Conference on Ubiquitous Computing and Communications and Eighth International Symposium on Cyberspace Safety and Security

    J.G. Blas, J. Carretero, I. Ray, Q. Jin, N. Georgalas (Eds.)

    IEEE Computer Society CPS  2016

  • Human Centric Technology and Service in Smart Space: HumanCom 2012, Lecture Notes in Electrical Engineering, Vol. 182

    J.J. Park, Q. Jin, S.S. Yeo, B. Hu

    Springer  2014

  • Frontier and Future Development of Information Technology in Medicine and Education: ITME 2013, Lecture Notes in Electrical Engineering, Vol. 269

    S. Li, Q. Jin, X. Jiang, J.J. Park

    Springer  2013

  • Technology Enhanced Learning: Quality of Teaching and Educational Reform, Communications in Computer and Information Science Series, Vol. 73

    M.D. Lytras, P.O. De Pablos, D. Avison, J. Sipior, Q. Jin (Eds.).

    Springer  2010

  • Proceedings of Second IEEE Asia-Pacific Service Computing Conference

    J. Li, M. Guo, Q. Jin

    IEEE Computer Society CPS  2007

▼display all

Research Projects

  • Empowering the life style and wellbeing of eastern Asian elders with intelligent IoT

    JSPS  A3 Foresight Program

    Project Year :

    2020.08
    -
    2025.07
     

    Jin Nakazawa

  • Making effective use of Information and Communication Technology in social work education

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2021.04
    -
    2025.03
     

  • Visualization of a Pre-Symptomatic Health State by Human Sciences Approach and Construction of Health Promotion Model Based on Traditional Chinese Medicine Concept

    Masaru Ibuka Foundation  Human Sciences Research Project on Oriental Medicine

    Project Year :

    2022.04
    -
    2025.03
     

    Qun Jin

  • Project for Mid-to-Long-Term City Development through Health Promotion Based on Health Data Analysis

    Cabinet Office, Government of Japan  National Initiative Promotion Grant for Digital Rural City

    Project Year :

    2022.04
    -
    2025.03
     

    Minano Town of Saitama-Ken, Waseda University Advanced Research Center for Human Sciences, and INES Research Institute, Inc.

  • Individual-Initiated and Decentralized Trustworthy Data Sharing with Blockchain and Federated Learnin

    Waseda University-NICT Matching Funds Program

    Project Year :

    2021.04
    -
    2023.03
     

    Qun Jin

  • E-Inclusion: Creating Accessible Local/Social Services for People with Disabilities

    Japan Science and Technology Agency (JST)  Solution-Driven Co-creative R&D Program for SDGs (SOLVE for SDGs)

    Project Year :

    2019.11
    -
    2021.10
     

    Mamoru Iwabuchi

  • Fundamental Health Control Model Based on Integrated Analysis of Life Logs and Pulse Data toward Holistic Living Support for the Elderly

    Masaru Ibuka Foundation  Human Sciences Research Project on Oriental Medicine

    Project Year :

    2016.04
    -
    2019.03
     

    Qun Jin

  • Fundamental Models and Mechanisms for Sustainable Use of Personal Big Data

    Waseda University  Grants for Special Research Projects

    Project Year :

    2014.04
    -
    2015.03
     

    Qun Jin

  • Development of Distributed Collaborative Knowledge and Information Sharing Systems as the Foundation of Growing Campus

    Waseda University  Advanced Research Center for Human Sciences Seeds-Type Research Project

    Project Year :

    2010.04
    -
    2013.03
     

    Shoji Nishimura

  • Integration of Real-World Experiment, Practice and Experience with Ubiquitous Learning

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (A)

    Project Year :

    2007.04
    -
    2010.03
     

    Yoneo Yano

    　View Summary

    In this study, we developed and evaluated ubiquitous learning systems that close the gap between real world and virtual world, and lecture and practice. The systems are based on ubiquitous technologies such as mobile devices, sensors, multimedia contents and wireless networks.

  • Development of Human-Centric Distributed Collaborative Knowledge and Information Sharing Systems and Applications at E-School

    Waseda University  Advanced Research Center for Human Sciences Seeds-Type Research Project

    Project Year :

    2004.04
    -
    2007.03
     

    Qun Jin

  • Development of a New Learning Community Model for Higher Education Using Broadband Networks

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2003.04
    -
    2007.03
     

    Chiharu Kogo

    　View Summary

    To get substantive outcomes of e-learning courses, it is necessary for e-learning system including learning management systems to facilitate learners learning. Also it is necessary for teachers, coaches, and supporting staffs to work respectively. Teachers have three types of work: design, management and evaluation of the courses. Designing the detailed course structure is the new and important part of work for the teachers. And then online coaches appear to have a greater part of work to support the teacher and to facilitate classroom activities. Coaches have three types of work: facilitating the classroom activities, making classroom atmosphere and standards, facilitating the discussion processes. Many kind of learning management systems are now available free or commercially. The minimum functions are video streaming, bulletin board system, and testing, but these functions should be carefully designed and become more usable to get more substantive learning outcomes. Talking about the future learning environments, learner will be able to access directly his/her own working spaces by opening web brouser.

  • Learning Communities Using Virtual Reality Environment Media

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2000.04
    -
    2003.03
     

    Qun Jin

    　View Summary

    Internet provides a universal, free, and equal electronic communication environment for people of all ages with different education backgrounds, ability levels, and personal inclinations. It has been changing how people work, live and play. Internet makes knowledge delivery, sharing and building possible among large and diverse groups of people across the networks. It has brought great impact on the existing education systems and learning styles.
    In this study, we propose a new framework for every-citizen learning communities, as an alternative solution for distance education/learning, in which not only the delivery of knowledge is intelligently supported, but also the exchange and sharing of information is actively encouraged and facilitated. The central purpose of learning communities is to provide an online learning environment that widely opens to large and diverse group of people who have the will to learn and to share their knowledge with others across the networks. Online learning communities are participants-driven. That is, participants who are the members of the learning communities, share a common interest in a topic or area, a way of knowing, and a set of practices. They may be large, the task general, and the communication open. Alternatively, they can be small, the task specific, and the communication close.
    Through this project, we have designed and developed a pilot implementation of online learning communities based on a social virtual reality system known as MOO (Multi user dimension Object Oriented). It has been designed as a networked virtual workspace, integrated with various groupware tools and learning resources, in which computation is effectively utilized to support both human-human and human-computer communication, interaction and collaboration, towards assisting and enhancing learning activities in the virtual environments to the utmost.

  • Development of Agent-based Collaborative Learning Support Systems focusing on Social Networks

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2000.04
    -
    2002.03
     

    Hiroaki Ogata

    　View Summary

    Recently, researchers in educational systems attempt to provide technological support for cooperative and collaborative learning advocated by educational theories. The explosive growth of networking, in particular, raises the possibility of widespread collaborative and open-ended learning activities. We have investigated on technological support for open-ended and collaborative learning activities.
    In this research, CoCoA -(Communicative Correction Assistant system) has been developed for supporting foreigners and teachers to exchange marked-up documents by e-mail. Its environment is very similar to a real one in which people use paper and pen. CoCoA allows teachers not only to correct the compositions sent from foreigners by E-mail, but also foreigners to see where and why the teacher had corrected them. CoCoA improves the opportunities that foreigners have for writing Japanese compositions and for receiving instructions from teachers.
    Next, we proposed a foreign language supporting system called Neckle (Network-based communicative kanji learning Environment). Neckle has a software agent into Internet communication environment, considering the difference between learner's mother and target languages. The agent observing the conversation between learner and native speaker, and detects communicative gap according to CGM, and notice the gap, then, supporting language learning congenial to each learner. Learners also get different knowledge from native speaker and the knowledge database is enlarged.

  • Development of Flexible Collaborative Learning Environments for Japanese Language Instruction Using Agents

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    1997.04
    -
    2001.03
     

    Yoneo Yano

    　View Summary

    Recently, researchers in educational systems attempt to provide technological support for cooperative and collaborative learning advocated by educational theories. The explosive growth of networking, in particular, raises the possibility of widespread collaborative and open-ended learning activities. We have investigated on technological support for open-ended and collaborative learning activities.
    In this research, CoCoA (Communicative Correction Assistant system) has been developed for supporting foreigners and teachers to exchange marked-up documents by e-mail. Its environment is very similar to a real one in which people use paper and pen. CoCoA allows teachers not only to correct the compositions sent from foreigners by E-mail, but also foreigners to see where and why the teacher had corrected them. CoCoA improves the opportunities that foreigners have for writing Japanese compositions and for receiving instructions from teachers.
    Next, we proposed a foreign language supporting system called Neckle (Network-based communicative kanji learning Environment). Neckle has a software agent into Internet communication environment, considering the difference between learner's mother and target languages. The agent observing the conversation between learner and native speaker, and detects communicative gap according to CGM, and notice the gap, then, supporting language learning congenial to each learner. Learners also get different knowledge from native speaker and the knowledge database is enlarged.

  • Development of Multimedia Dictionay for Japanese Language Learning on Internet

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    1997.04
    -
    2001.03
     

    Yoneo yano

    　View Summary

    We advanced the project of treatment expression study system Jecy, Chinese character idiom dictionary system KIDS-II, onomatopoeia mimicry dictionary system Jamios, and the Chinese character study support systems JUPITER and Anckle as research of the open and extensible electronic dictionary system for Japanese study using the Internet represented by WWW.Jecy is the treatment expression study support system that directed its attention to personal relations. We realized the learning environment that follows up how to catch the personal relations by the treatment expression knowledge base and the cultural difference. Then we applied the result to treatment expression dictionary Jedy. JAMIOS used Multimedia information was used for an onomatopoeia and mimesis, and it realized semantic understanding by the cultural difference, and the flexible electronic dictionary that used multimedia as the key. KIDS-II is a dictionary system that supports an analogy of a Chinese character idiom. It mounted the reading candidate derivation mechanism over the arbitrary Chinese character idioms that directed their attention to the appearance frequency of a Chinese character. JUPITER mounted Chinese character selection filtering which applies KIDS-II, applies information filtering technology and selects a study Chinese character. Anckle is a study support system that performs study support with consideration to the semantic difference in the Chinese character in Japanese and Chinese. This system has an electronic dictionary treating difference knowledge in the daytime, and supports communication of a student and a mother-tongue speaker using a software agent. These systems operated on Microsoft Windows platform and were mounted by the framework of the Internet correspondence by the formation of a software component. Moreover, each system performs trial evaluation in the Japanese educational spot, and the good result was obtained.

  • Text-Based Virtual Reality for Collaborative Learning Support

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Encouragement of Scientists (A)

    Project Year :

    1998.04
    -
    2000.03
     

    Qun Jin

  • Development of Active Database Systems for Collaborative Learning

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research on Priority Areas

    Project Year :

    1997.04
    -
    1998.03
     

    Yoneo Yano

▼display all

Misc

  • 特集「人間中心のユニバーサル/ユビキタス・ネットワークサービス」の編集にあたって

    金群, 荒金陽助

    情報処理学会論文誌   49 ( 1 )  2008.11

    CiNii

  • Phenome-wide causal proteomics enhance systemic lupus erythematosus flare prediction: A study in Asian populations

    Liying Chen, Ou Deng, Ting Fang, Mei Chen, Xvfeng Zhang, Ruichen Cong, Dingqi Lu, Runrun Zhang, Qun Jin, Xinchang Wang

       2024.11

    　View Summary

    Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease
    characterized by unpredictable flares. This study aimed to develop a novel
    proteomics-based risk prediction model specifically for Asian SLE populations
    to enhance personalized disease management and early intervention. Methods: A
    longitudinal cohort study was conducted over 48 weeks, including 139 SLE
    patients monitored every 12 weeks. Patients were classified into flare (n = 53)
    and non-flare (n = 86) groups. Baseline plasma samples underwent
    data-independent acquisition (DIA) proteomics analysis, and phenome-wide
    Mendelian randomization (PheWAS) was performed to evaluate causal relationships
    between proteins and clinical predictors. Logistic regression (LR) and random
    forest (RF) models were used to integrate proteomic and clinical data for flare
    risk prediction. Results: Five proteins (SAA1, B4GALT5, GIT2, NAA15, and RPIA)
    were significantly associated with SLE Disease Activity Index-2K (SLEDAI-2K)
    scores and 1-year flare risk, implicating key pathways such as B-cell receptor
    signaling and platelet degranulation. SAA1 demonstrated causal effects on
    flare-related clinical markers, including hemoglobin and red blood cell counts.
    A combined model integrating clinical and proteomic data achieved the highest
    predictive accuracy (AUC = 0.769), surpassing individual models. SAA1 was
    highlighted as a priority biomarker for rapid flare discrimination. Conclusion:
    The integration of proteomic and clinical data significantly improves flare
    prediction in Asian SLE patients. The identification of key proteins and their
    causal relationships with flare-related clinical markers provides valuable
    insights for proactive SLE management and personalized therapeutic approaches.

  • Evolutionary Causal Discovery with Relative Impact Stratification for Interpretable Data Analysis

    Ou Deng, Shoji Nishimura, Atsushi Ogihara, Qun Jin

       2024.04

    　View Summary

    This study proposes Evolutionary Causal Discovery (ECD) for causal discovery
    that tailors response variables, predictor variables, and corresponding
    operators to research datasets. Utilizing genetic programming for variable
    relationship parsing, the method proceeds with the Relative Impact
    Stratification (RIS) algorithm to assess the relative impact of predictor
    variables on the response variable, facilitating expression simplification and
    enhancing the interpretability of variable relationships. ECD proposes an
    expression tree to visualize the RIS results, offering a differentiated
    depiction of unknown causal relationships compared to conventional causal
    discovery. The ECD method represents an evolution and augmentation of existing
    causal discovery methods, providing an interpretable approach for analyzing
    variable relationships in complex systems, particularly in healthcare settings
    with Electronic Health Record (EHR) data. Experiments on both synthetic and
    real-world EHR datasets demonstrate the efficacy of ECD in uncovering patterns
    and mechanisms among variables, maintaining high accuracy and stability across
    different noise levels. On the real-world EHR dataset, ECD reveals the
    intricate relationships between the response variable and other predictive
    variables, aligning with the results of structural equation modeling and
    shapley additive explanations analyses.

  • Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-Attention

    Ou Deng, Qun Jin

       2023.08

    　View Summary

    Addressing missing data in complex datasets including electronic health
    records (EHR) is critical for ensuring accurate analysis and decision-making in
    healthcare. This paper proposes dynamically adaptable structural equation
    modeling (SEM) using a self-attention method (SESA), an approach to data
    imputation in EHR. SESA innovates beyond traditional SEM-based methods by
    incorporating self-attention mechanisms, thereby enhancing model adaptability
    and accuracy across diverse EHR datasets. Such enhancement allows SESA to
    dynamically adjust and optimize imputation and overcome the limitations of
    static SEM frameworks. Our experimental analyses demonstrate the achievement of
    robust predictive SESA performance for effectively handling missing data in
    EHR. Moreover, the SESA architecture not only rectifies potential
    mis-specifications in SEM but also synergizes with causal discovery algorithms
    to refine its imputation logic based on underlying data structures. Such
    features highlight its capabilities and broadening applicational potential in
    EHR data analysis and beyond, marking a reasonable leap forward in the field of
    data imputation.

  • 地域・福祉サービスのデータ連携に向けた障害情報の電子化インタフェースに関する検討: Study on Data Collaboration and Digital Inclusion of Local/Social Services for People with Disabilities

      35 ( 1 ) 97 - 108  2022.03

  • High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection

    Yunxiang Li, Yifan Zhang, Yaqi Wang, Shuai Wang, Ruizi Peng, Kai Tang, Qianni Zhang, Jun Wang, Qun Jin, Lingling Sun

       2021.03

    　View Summary

    As the most economical and routine auxiliary examination in the diagnosis of
    root canal treatment, oral X-ray has been widely used by stomatologists. It is
    still challenging to segment the tooth root with a blurry boundary for the
    traditional image segmentation method. To this end, we propose a model for
    high-resolution segmentation based on polynomial curve fitting with landmark
    detection (HS-PCL). It is based on detecting multiple landmarks evenly
    distributed on the edge of the tooth root to fit a smooth polynomial curve as
    the segmentation of the tooth root, thereby solving the problem of fuzzy edge.
    In our model, a maximum number of the shortest distances algorithm (MNSDA) is
    proposed to automatically reduce the negative influence of the wrong landmarks
    which are detected incorrectly and deviate from the tooth root on the fitting
    result. Our numerical experiments demonstrate that the proposed approach not
    only reduces Hausdorff95 (HD95) by 33.9% and Average Surface Distance (ASD) by
    42.1% compared with the state-of-the-art method, but it also achieves excellent
    results on the minute quantity of datasets, which greatly improves the
    feasibility of automatic root canal therapy evaluation by medical image
    computing.

  • Enabling the Social Internet of Things and Social Cloud

    Weishan Zhang, Qun Jin, Didier El Baz

       2019.04

    　View Summary

    Social Internet of Things are changing what social patterns can be, and will
    bring unprecedented online and offline social experiences. Social cloud is an
    improvement over social network in order to cooperatively provide computing
    facilities through social interactions. Both of these two field needs more
    research efforts to have a generic or unified supporting architecture, in order
    to integrate with various involved technologies. These two paradigms are both
    related to Social Networks, Cloud Computing, and Internet of Things. Therefore,
    we have reasons to believe that they have many potentials to support each
    other, and we predict that the two will be merged in one way or another.

    DOI

  • Growing Campusの基盤をなす分散協調型知識情報共有システムの構築

    西村 昭治, 金 群, 尾澤 重知

    人間科学研究   26 ( 2 ) 221 - 222  2013.09

    CiNii

  • Seminar communication : Qun Jin

      25 ( 1 ) 44 - 46  2012

    CiNii

  • Web標準の進化に対応したWebオーサリング手法の提案と実装—Proposal and Implementation of a Web Authoring Method Corresponding to Web Standards Evolution

    Zhu, Jin, Nakazato, Hidenori, Urano, Yoshiyori, Jin, Qun, 朱, 槿, 中里, 秀則, 浦野, 義頼, 金, 群

    GITS/GITI Research Bulletin   2010-2011   25 - 35  2011.10

    CiNii

  • Web標準の進化に対応したWebオーサリングツールの開発—The Development of Web Authoring Tool Corresponding to Web Standards Evolution

    朱 槿, 浦野 義頼, 金 群

    日本ソフトウェア科学会大会論文集 / 日本ソフトウェア科学会 編   27   1 - 17  2010.09

    CiNii

  • An Information Recommendation Model Based on Concept Classes Extracted from Wikipedia Categories

    CHEN Jian, SHTYKH Roman Y., JIN Qun

    JSAI Technical Report, Type 2 SIG   2009 ( SWO-020 ) 10  2009.01

    　View Summary

    In this study, we present an information recommendation model based on a set of concept classes that are extracted from Wikipedia categories and pages. The indices of all the pages are organized so that they represent concepts. Using this information, data representing the users' access behavior are collected and categorized according to the concept classes. The proposed model is then established by analyzing the preprocessed data in terms of short, medium, long periods, and calculating the probabilities corresponding to each concept.

    DOI CiNii

  • Editor’s Message to Special Issue on Human-Centered Universal/Ubiquitous Network Services

      49 ( 1 ) 1  2008.01

    CiNii

  • スライド教材の編集による教育・学習支援環境の試作

    松浦 健二, 金西 計英, 矢野 米雄, 金 群

    電子情報通信学会和文論文誌D Vol.91-D,No.2     259 - 268  2008  [Refereed]

  • 利用者の情報アクセス行動を推定する逐次適応モデル—Gradual adaptation model for estimation of human information access behavior—データベースシステム グループウェアとネットワークサービス

    陳 健, Roman Y. Shtykh, 金 群

    情報処理学会研究報告 = IPSJ SIG technical reports   2008 ( 7 ) 19 - 24  2008.01

    CiNii

  • Will Digital Media Lead to Self-Extension?

      2007   69 - 70  2007.11

    CiNii

  • CubicSNS: Social Networking through Temporal-Spatial Information

      2007   65 - 66  2007.11

    CiNii

  • Scrolless Interface for Mobile Search

      2007   67 - 68  2007.11

    CiNii

  • Implementation of Information Accessing and Sharing Support Environments Using Mashup of Web Services

      2007   95 - 100  2007.11

    CiNii

  • Dynamic Construction of Groups of Users with Similar Interests and Their Participation Recommendation Based on Web Search Activities

      2006   57 - 58  2006.11

    CiNii

  • Wikiの普及と個性化の保持

    陳健, 金群

    ワークショップ2006 （GN Workshop 2006) 論文集   2006   67 - 68  2006.11

    　View Summary

    生まれてからわずか 10 年間、多くの Wiki クローンが作成され、様々なプラットフォームに移植され、活用されている。一方、多様性をもつ Wiki は、異なるクローンを超えた情報共有に不便を与えている。また、Wiki の標準化をしようとする動きが活発になっている。本稿では、Wiki の普及と個性化・多様性の保持について論じる。

    CiNii

  • Towards Better Search and Sharing: the Growing Role of Relevance Feedback for Personalized Web Search

      2006   109 - 113  2006.11

    CiNii

  • Design of a Supportive Information Access and Sharing Environment Utilizing Cross Social Networking Services

      2006   103 - 108  2006.11

    CiNii

  • Information Sharing across Different Media Platforms Using P2P Network

    IIMURA T., YOSHIMI K., TAKEI N., ZHANG G., JIN Q.

    IPSJ SIG Notes   2006 ( 60 ) 25 - 30  2006.05

    　View Summary

    In this study, we propose an information sharing support environment that integrates information media platforms such as Blog, Wiki and XOOPS, which are well-known for an individual user to share various contents with others freely, by using peer-to-peer network technology. We have implemented a prototype system that supports a user individually, in a small/large size group, or even in an open community to create, manage, exchange and share information flexibly and collaboratively anywhere and anytime.

    CiNii

  • Issues on Ubiquitous Information Management over a Lifetime (Position Paper)

      2005   53 - 54  2005.11

    CiNii

  • 分散型P2P ネットワークと集中型メディアツールの統合によるスケーラブルな情報共有システムの実現

    張国珍

    ワークショップ2005 （GN Workshop 2005) 論文集   2005   59 - 60  2005.11

    　View Summary

    本研究では分散型 P2P ネットワーク技術と集中型情報メディアツールが融合した情報共有手法を提案する。本手法では、個人情報発信ツール Blog 及びグループ共同編集ツール Wiki と P2P ネットワークを統合させ、ユーザの増減によるスケールアップ・スケールダウンに対応可能な情報共有システムを構築する。

    CiNii

  • A Practice of the "Campus" Model e-Learning : Case Study of "e-School" of Human Sciences, Waseda University

    NISHIMURA Shoji, ASADA Tadashi, KOGO Chiharu, KIKUCHI Hideaki, JIN Qun, MATSUI Tatsunori, NOJIMA Eiichiro

      20   149 - 152  2004.09

    CiNii

  • E-school of Waseda University : Perspective on e-Learning in Higher Education

    KOGO Chiharu, NISHIMURA Shoji, ASADA Tadashi, KIKUCHI Hideaki, JIN Qun, NOJIMA Eiichiro

    Research report of JET Conferences   2004 ( 3 ) 17 - 23  2004.05

    CiNii

  • Database Agents for Collaborative Learning in Virtual Environments

    JIN Qun, OGATA Hiroaki, YANO Yoneo

    全国大会講演論文集   55 ( 3 ) 298 - 299  1997.09

    　View Summary

    通信技術のめざましい発展に伴い, 近年, インターネットを介した仮想コミュニティ, 仮想オフィス, 仮想クラスルームが次々と現われ, このような仮想空間に入り込んで, 仕事したり, 学習したりすることは単なる夢ではなく, 現実のものとなりつつある。MOO (Multi user dimension Object-Oriented)と呼ばれるマルチユーザシミュレーション環境が, こうした仮想空間を容易に実現できるシステムとして注目を集めている。我々はMOOをベースにした協調学習環境の構築を行っている。仮想学習環境の外部にあるデータベースやインターネット上にある豊富な情報資源を教育/学習の教材として活用するため, 外部データベースやWWWサーバなどへのアクセスが必要となる。本研究報告では, それらのアクセスを可能にするエージェントについて述べる。

    CiNii J-GLOBAL

  • Development of a Collaborative Learning System Based on a Simulated Virtual Environment

    SHAO Yingzhi, SIRAKUSA Yoshihiro, JIN Qun, YANO Yoneo

    IEICE technical report. Education technology   96 ( 578 ) 175 - 180  1997.03

    　View Summary

    A text-based virtual reality system known as MOO (Multiple user dimension Object-Oriented) has been reported very suitable to aid education on the Internet. When being used to support collaborative learning, however, MOO has two major problems: (1) It is not very appropriate for handling a vast amount of data; (2) From Moo, it is too difficult for us to make full use of information and knowledge which exist on the Internet. To solve these two problems, we have made some extensions to MOO by making MOO accessible to an external database and to any WWW servers as well. In this paper, we introduce MOO virtual community, discuss MOO's problems and their solutions, and describe the MOO based collaborative learning support system we have developed.

    CiNii

  • A Collaborative Learning Enviroment Using a Text-Based Virtual Reality System

    SHIRAKUSA Yoshihiro, SHAO Yingzhi, JIN Qun, TANO Yoneo

      1996 ( 2 ) 3 - 8  1996.09

    CiNii

  • (67)学生による授業評価アンケート : 工学部全学生、全クラスに対する実施と評価(第19セッション 教育評価(II))

    矢野 米雄, 金 群, 森吉 孝

    工学・工業教育研究講演会講演論文集   8   215 - 218  1996.07

    DOI CiNii

  • Development of a Supporting System for Group Use of Personal Connections Using Collaborative Agents.

    相曽友宏, 郷司敦史, 緒方広明, JIN Q, 矢野米雄, 古郡延子

    電子情報通信学会技術研究報告   96 ( 71(OFS96 10-15) ) 31 - 36  1996.05

    　View Summary

    Recently, the internet makes it ver easy and convenient for various kinds of experts to communicate with each other and they form a knowledgeable network. We consider their personal connections (PeCo) to be the network and investigate the way to use the network for their problem solving. We expect that the users can obtain excellent results by integrating their ideas through the network. This paper describes PeCo-Collector which gathers and manages their respective PeCo, and PeCo-Agent which searches cooperative and capable partner(s) in the network.

    CiNii J-GLOBAL

  • Development of a Japanese Mimesis and Onomatopoeia Dictionary System for Foreigners.

    川崎桂司, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

    電子情報通信学会技術研究報告   95 ( 604(ET95 112-131) ) 33 - 40  1996.03

    　View Summary

    This paper describes the development of a Japanese mimesis and onomatopoeia dictionary system called JAMIOS. Mimesis and onomatopoeia tend to be used frequently in Japan. However, they are words that express diverse feelings particular to the Japanese culture. Therefore, it is difficult for foreigniers to understand mimesis and onomatopoeia. We focus on the situation, pronunciation, meaning, usage and feeling. JAMIOS has the following features : (1)The system presents the situation using multi media, and the user can advance the search by changing the situation or the pronunciation. (2)Users can search knowledge or related words along the feature of mimesis and onomatopoeia. (3)The system presents the usage of Japanese using example sentences.

    CiNii J-GLOBAL

  • Development of a Japanese Polite Expressions CAI system

    MURATA Rie, OCHI Youji, AYALA Gerardo, OGATA Hiroaki, JIN Qun, YANO Yoneo, HAYASHI Toshihiro, NOMURA Chieko, KOUNO Nayoko

    IEICE technical report. Education technology   95 ( 604 ) 41 - 48  1996.03

    　View Summary

    When foreigners who study Japanese are used to the language, they find some difficulties with polite expressions. For instance, they can't make themselves fully understand in Japanese because of the different point of views between the Japanese people and the student. It causes a change in the complexity of polite expressions because of a change in the situation or in the personal relations. Foreigners have problems in the use of polite expressions when (1)they don't understand the personal relations in Japan. (2)they don't understand the suitable polite expressions for a situation accordin...

    CiNii J-GLOBAL

  • Development of a Japanese Onomatopoeia and Mimesis Dictionary System for Foreigners.

    川崎桂司, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

    教育システム情報学会全国大会講演論文集   20th   225 - 228  1995.08

    CiNii J-GLOBAL

  • Development of a Japanese Honorific Expressions CAI System with Consideration of Personal Relations.

    村田利恵, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

    教育システム情報学会全国大会講演論文集   20th   221 - 224  1995.08

    CiNii J-GLOBAL

  • Construction of mimetic word and imitation sound word dictionary system for foreigners.

    川崎桂司, 越智洋司, アヤラ ヘラルド, 緒方広明, 金群, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子

    電気関係学会四国支部連合大会講演論文集   1995   332  1995

    J-GLOBAL

  • Modeling of human connection search agent in human connection utilization support system.

    緒方広明, 郷司敦史, 金群, 矢野米雄

    電気関係学会四国支部連合大会講演論文集   1995   346  1995

    J-GLOBAL

  • PeCo-Collector: Human connection database system in internet environment.

    郷司敦史, 緒方広明, 金群, 矢野米雄

    電気関係学会四国支部連合大会講演論文集   1995   344  1995

    J-GLOBAL

  • Construction of Japanese respect expression learning support system considering personal relations.

    村田利恵, 越智洋司, アヤラ ヘラルド, 緒方広明, 金群, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子

    電気関係学会四国支部連合大会講演論文集   1995   334  1995

    J-GLOBAL

  • Construction of ORMEX, a joint ownership system of know-how based on case examples.

    堤清二, 緒方広明, 金群, 矢野米雄

    電気関係学会四国支部連合大会講演論文集   1995   340  1995

    J-GLOBAL

  • Flexible‐structured framework for handling nonstandard information.Connection utilization support system.

    古郡延子, JIN Q, 緒方広明, 矢野米雄

    システムシンポジウム講演論文集   20th   165 - 168  1994

    J-GLOBAL

  • Development of a supporting system for practical use of personal connections : Personal information sharing and handling environment

    Ogata Hiroaki, Morikawa Tomiaki, Yano Yoneo, Furugori Nobuko, Jin Qun

    IPSJ SIG Notes   93 ( 95 ) 29 - 36  1993.10

    　View Summary

    A new project is often promoted and a negotiation is often concluded by using various fields and many personal connections (PeCo) positively. This system aims to share and use PeCo that each group member obtains in her/his social relationships. Generally it is difficult for traditional database systems to share and handle dynamic, ill-formed and private data such as PeCo. This paper describes an environment which clears up this problem. This environment supports users allowing them to share private and ill-formed information, the database of this system evolves in proportion to its use.

    CiNii

  • Development of a supporting system for practical use of personal connections.

    緒方広明, 森川富昭, 林敏浩, 矢野米雄, 土定正明, 古郡延子, JIN Qun

    情報処理学会研究報告   93 ( 56(GW-2) ) 57 - 64  1993.06

    　View Summary

    It is said that every member of a group is considered as an information source. With the development of distributed offices, we consider the necessity of groupware systems that allow sharing information between each group member for its usage in each distributed office. Therefore we are developing a system whose aim is to share and use the personal connections (PC) that each group member obtains in her/his social relationships. We suppose that in this way our system can raise the productivity and the power of the group in general. When a group member uses other members' PC in the system, s/he has to evaluate the degree of that PC in some way. Therefore the system allows the quantification and visualization of a group PC. In this paper, we describe our considerations about practical use of the PC together with its quantification and visualization methods, the overview of the system and the practical use of the PC provided by this environment.

    CiNii J-GLOBAL

  • Reasoning with Uncertainty in Expert Systems and its Representarion by Petri Nets

      45   85 - 86  1992.09

    CiNii

  • Behavior Analysis of Trap Systems Using Stochastic Petry Nets

      42   345 - 346  1991.02

    CiNii

  • Representation of Buffer Capicity by an Extended Petri Net Model

      40   1550 - 1551  1990.03

    CiNii

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Other

  • https://nislab.human.waseda.ac.jp/

  • https://waseda.pure.elsevier.com/en/persons/qun-jin/publications/

 

Syllabus

▼display all

 

Overseas Activities

  • 利用者中心のネットワーク情報システムにおけるユーザモデルの研究

    2012.03
    -
    2013.03

    中国   中国計量学院、北京大学、上海大学

Sub-affiliation

  • Faculty of Human Sciences   Graduate School of Human Sciences

Research Institute

  • 2024
    -
    2026

    Waseda Center for a Carbon Neutral Society   Concurrent Researcher

Internal Special Research Projects

  • 因果探索によるヘルスデータアナリティクス

    2024  

    　View Summary

    ヘルスデータ分析による健康リスク評価と予測において、ビッグデータ分析手法により相関関係を明らかにするだけでは十分でない。データにおける潜在的な因果関係を推論し発見する探索的因果分析は有効であると期待されている。しかし、ヘルスデータは多くの要因が複雑に絡み合い、健康に関わる重要な特徴を適切に選択し適用することが容易でないなど多くの課題が残されている。本研究では、人工知能、機械学習、データサイエンス、統計学など分野を横断する学融合的な総合知を創出するConvergentResearchアプローチを用いて、因果探索による新たなヘルスデータアナリティクスの構築を目指して、基盤モデルとアルゴリズムを開発し、有用性と有効性を実験的に検証する。今年度の主な研究成果は以下の通りである。(1)     潜在的な健康リスク要因を特定することは、ヘルスデータ分析における重要な課題である。ニューラルネットワークに基づく多くの分析プロセスは説明可能ではない。分析プロセスを可視化する先行研究があるが、専門家によるドメイン知識が必要となる。本研究では、ドメイン知識に依存せず潜在的健康リスク要因を推定する探索的かつ解釈可能なアプローチを提案し、機械学習による重要な特徴を選択したうえ、因果探索によりリスク要因を発見し、ドメインモデルを構築する。さらに、2つのデータセットを用いて4つのベースラインと比較する評価実験を行った結果、提案するアプローチの有効性を検証している[1]。(2)     多くの特徴選択の手法があるが、本研究では、重み付け総合スコア（WTS）指数を導入し定義し、最適化方策による新たなヘルスデータ因果分析のための複数特徴選択手法を提案し、2つのデータセットを用いて従来の手法より優位な評価結果を得た[2]。さらに、提案手法をウェアラブルデバイスと被験者自己申告から得られたヘルスデータにおける因果関係発見によるライフスタイルと行動の分析に適用し、有用性を確認した[3](3)     人間を理解し健康維持・増進やウェルビーイング追究を支える諸課題と挑戦について検討し、ConvergentResearchによる学融合的な総合知を用いながら、とりわけ、因果探索によるヘルスデータアナリティクスとAIやIoT、ビッグデータなど新興技術との融合による新たな可能性と今後の展開について提示している[4-9]。

  • "Give-and-Take"に基づく分散データ共有モデルの構築

    2023  

    　View Summary

    高度デジタル化社会において、増え続けるビッグデータを有効的に利活用するため、データの所有者など利害関係者の利益保護が重要である。本研究は、データ所有者の意志と利益を守りながら、データは分散かつ秘匿状態のまま、利用権を持つ者が信頼して利用できる分散データ共有モデルを新たに提案し構築することが目的である。今年度の研究においては、ギブアンドテイクの考えに基づき、データ所有者と利用者の双方の利益を考慮するデータ共有のインセンティブ手法について検討し、これまでの先行研究で提案してきた利用者個人主導データアクセスコントロール方式及びブロックチェーンと分散型連合学習によるプライバシー保護強化メカニズムとの連携をはかり、実験的な検証を行っている。今年度の主な研究成果は以下の通りである。(1)    技術受容モデル（TAM）の基準に基づきAirbnbを例としてシナリオを設定し、アンケール調査を実施し、集めたデータを分析することにより、行動意図に影響を与える様々な要因を見つけ出し、供給者（提供側）と消費者（利用側）の信頼関係が最も重要な要因であることを明らかにした[1]。(2)     利用者個人主導データアクセスコントロール方式を用いた実験環境のもと、スマートコントラクトによるマルチレジャー協同メカニズムの実験検証[2]及びその結果の分析を行った上、ヘルスデータの統合・共有・分析と分析結果の可視化を検証する実験環境を構築し、適用の可能性と有効性を検討した[3]。(3)     提案モデルを用いてデータ共有と利活用を促進する方策と課題について検討し、ヘルスデータを含むビッグデータ分析により健康など人間が持っている多くの側面を理解し、連合学習やブロックチェーンなど新興技術融合による個人化支援サービスの構築における課題と今後の展開について提示している[4,5]。

  • ブロックチェーンと連合学習による高信頼データ共有基盤モデルの構築

    2022  

    　View Summary

    ビッグデータを有効的に利活用するため、セキュリティとプライバシー保護を強化することが不可欠である。本研究では、ブロックチェーンと連合学習を連携させ、データは分散状態のまま維持しつつ、データ所有者があらかじめ設定したポリシーと属性によるアクセス権限に従い、データの中身を明かさずに利用者のリクエストに応じ、データを共有し、利活用することができる高信頼データ共有モデルを新たに提案し構築することを目的とする。今年度においては、データの信頼性保証と取得・共有の効率性を両立する高信頼データアクセスを実現する基盤モデルとメカニズムの構築及び実験検証を行い、研究成果の一部は国際会議や学術論文誌に発表している。

  • ブロックチェーンを用いた連合学習における個人主導データアクセスコントロール

    2022  

    　View Summary

    連合学習はデータを集約せずに機械学習モデルを構築できる新たなプライバシー保護技術として注目を集めている。本研究は、データは分散状態のまま維持しつつ、その所有者が予め設定したアクセスポリシーに従い、ブロックチェーンを用いた連合学習における機械学習モデル構築で利用できる新たな個人主導データアクセスコントロール手法を開発することが目的である。今年度の研究においては、Hyperledger Fabricというコンソーシアム型ブロックチェーンと連合学習を連携させたうえ、CP-ABEというポリシーと属性ベース暗号方式による利用者個人主導データアクセスコントロールモデルの構築を試み、研究成果の一部は国際会議や学術論文誌に発表している。

  • 個人モデルに基づくヘルスデータの縦横比較分析

    2021  

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    ヘルスデータ分析に関するこれまでの研究では、時系列分析や異常検知などに重点を置くばかりで、個人を中心にした比較分析が行われていない。本研究は、過去のデータとの比較分析のみならず、同年代あるいは似た生活習慣など類似性を有する他の個人またはグループとの比較分析を行うため、個人モデルに基づくヘルスデータの縦横比較分析手法を新たに提案し、計算論的な方法論として構築し確立することが目的である。今年度の研究においては、常に更新するヘルスデータに適合する動的な特性を考慮した提案手法を実現するための基盤モデル構築とアルゴリズムを考案し検証を行っている。研究成果の一部は国際会議や学術論文誌に発表している。

  • 個人モデルに基づく個に適応するヘルスデータの比較分析法

    2021  

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    近年、ウェアラブルデバイスやセンサーにより歩数、睡眠などの活動量・生活データ、血圧、心拍などの健康関連データを含む個人に関わるパーソナルデータが持続的に収集し蓄積することが可能となった。本研究では、パーソナルデータを分析することにより個人モデルを構築し、それに基づきヘルスデータを比較しながら分析する、個に適応する新たな手法を提案し確立することを目的とする。具体的には、ヘルスデータを収集し、個人の現在のデータと過去のデータを比較分析するとともに、年齢や生活習慣など何らかの類似性を有する他の個人またはグループとの比較分析を行う検証実験を行った。研究成果の一部は国際会議や学術論文誌に発表している。

  • パーソナルアナリティクスによる個人化ヘルスケアのモデル構築

    2021  

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    本研究は、パーソナルデータ分析に基づき個に適するヘルスケアについて探究し、モデルを構築することが目的である。具体的には、ビッグデータと人工知能技術を用いて、ウェアラブルデバイスやセンサーで収集・蓄積される歩数、睡眠などの活動量・生活データ、血圧、心拍などの健康関連データを含む個人に関わるパーソナルデータを分析することにより個人モデルを構築するパーソナルアナリティクス手法を新たに提案する。今年度の研究においては、これまでの研究で提案している個人モデルの考えに基づき、個々の年齢、生活スタイルや健康状態に適する個人化ヘルスケアモデルの構築を試み、研究成果の一部は国際会議や学術論文誌に発表している。

  • ブロックチェーンを用いたパーソナルデータのプライバシー保護と利活用基盤モデル構築

    2020  

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    本研究は、パーソナルデータ利活用におけるプライバシー保護を強化するため、ブロックチェーン技術を用いてデータのオーナー（所有者）が主導でデータへのアクセスコントロールを可能とする安全性の高いプラットフォームを提案することが目的である。今年度の研究においては、データが時系列的に分散保持され、記録されたデータが改竄不可能といった高い信頼性が確保できるブロックチェーンの分散台帳機能を活かしながら、ハッシュや暗号化技術を利用したデータのオフチェーン保存など、個人主導によるデータアクセスコントルールを基本とする新たなフレームワークを提案し、検証を行った。研究成果の一部は国際会議や学術論文誌に発表している。

  • パーソナルデータ分析に基づく統合個人モデルの構築

    2018  

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    本研究は、特定のシステムに依存せず、複数の異なるシステムを跨り適用可能な個人モデルを提案し、パーソナルデータの特性を考慮しながらデータ分析に基づく統合個人モデル（UnifiedIndividual Model）の構築法を計算論的な方法論として開発し確立することが目的である。具体的には、ヘルスケアやソーシャルメディアにおけるパーソナルデータを実験データとして取得し、ブロックチェーンを利用したパーソナルデータにおけるプライバシー保護の強化をはかる仕組みづくりや関連基盤アルゴリズムの開発を行い、検証・評価実験を実施する。さらに、実験結果を分析し、今後の展開と応用の可能性と課題について検討する。

  • パーソナルデータ分析による個人モデルの構築法

    2017  

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    　本研究ではパーソナルビッグデータに基づくパーソナルアナリティックス（PersonalAnalytics）を新たに提案し、個人モデル（IndividualModel）を構築するための動的分割統治法を計算論的な方法論として研究開発するとともに、実験用データを収集し、検証実験を行い、結果を分析する。本研究は、パーソナルビッグデータの特性を考慮した動的分割統治法をコアに、「分人」という概念を導入した個人中心の統合モデリング手法（UnifiedIndividual Modeling）を新たに提案し確立することを目指すものである。また、本研究で提案している個人モデルは、従来のユーザモデルと違って、特定のシステムに依存しないものであり、それによりシステムをまたがる個別化サービスを提供すことが可能となる。

  • マイクロコンテンツを有効利用するためのソーシャルラーニング基盤モデルの構築

    2016   武　博

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    In this study, we propose a fundamentalmodel for social learning in order to effectively use micro contents aseducational resources, based on personal data analytics and individualmodeling. We improve data-driven individual modeling, proposed in our previousstudy, by introducing the concept of dividual and divide-and-conquer algorithm.We further propose a temporal social network analysis approach for dynamiccommunity mining and tracking, and develop overlap community detectionalgorithm by spectral clustering based on node convergence degree that takesboth the network structure and node attributes into account. We use topicevolution model and temporal social network analysis for topic tracking andassessing and pattern extraction as well. Experiments have been conducted basedon different data sets, and comparison with related works and result analysis haveshown the effectiveness of our proposed model and approach.

  • 学習プロセスを手助けするためのソーシャルラーニング基盤モデルの構築と実証実験

    2015  

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    本研究では、ソーシャルラーニングを、授業や研修、個人の読書、他人との情報共有やインタラクション、日々の生活や社会活動、仕事経験といった知識獲得プロセスを包括的かつ有機的に融合し、一種の拡張されたラーニングプロセスとしてとらえ、基盤モデルを構築する。さらに、利用者の情報アクセス履歴や学習活動を含むパーソナルデータを分析・マイニングすることにより、適応型学習支援を可能とする利用者の個人モデルを構築し、ソーシャルラーニングにおける学習プロセスを手助けするための支援メカニズムを開発し、実験的な試作と検証を行っている。

  • 個人ビッグデータの持続的活用を実現するための基盤モデルとメカニズムの研究開発

    2014  

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    本研究では、個人に関わる日々の情報行動や情報アクセス履歴を記録するライフログをパーソナルデータと呼び、長期間にわたり蓄積されたパーソナルデータを一種の個人ビッグデータととらえる。このような個人ビッグデータを持続的、効果的に活用するための基盤モデルを提案し、多種多様なデータを集約し、組織化するメカニズムおよび、個人化サービスを提供するためのユニファイド・インディビジュアル・モデリング手法を研究開発している。さらに、SNS環境における動的ユーザプロファイリング、ソーシャルデータ分析によるグループにおける個人の役割の特定、ソーシャルラーニングにおける学習行動分析などへの適用を試みた。

  • 適応型ラーニングサービスを提供するための統合ユーザモデルと基盤メカニズムの研究

    2013   周　暁康

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    本研究では、ソーシャルネットワーキング環境における利用者の情報アクセス行動履歴やログデータなどを解析し、利用者と情報環境両方の複合要素を考慮したユニファイドユーザモデリング手法を提案し、統合ユーザモデルを構築するとともに、適応型ラーニングサービスを提供するための基盤メカニズムおよび関連アルゴリズムを研究開発する。本年度では、・これまで提案している「進化する統合情報環境の基盤モデル」をベースに、ライフログのような個人ビッグデータを利活用するためのモデル改善と拡張を行い、データ整合、情報融合、再利用可能な知識化を行うとともに、個人ビッグデータに基づくアプリケーションに依存しないユニバーサルユーザモデルを構築する手法を提案している。・TwitterのようなSNS環境における利用者のメッセージやり取りやフォロー関係などから社会的役割と関係ネットワークを推定し、利用者参加型の情報検索・推薦メカニズムを考案するとともに、社会的役割に関わるさまざまな属性やSNS環境および実世界におけるさまざまな状況とコンテキストを総合的に考慮し、マッピングをすることにより社会的役割の特定を図り、基本モデルの構築及び必要なアルゴリズムの開発を行っている。・これまで提案しているDynamical Socialized User Networkingモデルに基づいて、ソーシャルネットワーキング環境における利用者の多次元属性データを解析することによる動的ユーザプロファイリング手法を提案し、中心性指数をベースにした複数のメジャーを新たに定義し導入することによって、ソーシャルネットワーキングにおける利用者個人の重要度と貢献度の定量化を図り、実験データを用いた実験評価を行っている。・ソーシャルネットワーキング環境における利用者のニーズに適合したデータの集約と整合を実現するため、これまで提案しているOrganic Streamsメタファーの改善と拡張を行い、Twitterから取得したデータを用いた評価実験を行っている。また、Eye-Trackingを用いたソーシャルメディアにおける閲覧パターン抽出法を考案し、評価実験を行った。・タスク指向ラーニングプロセスにおけるアクションパタンを発見するアルゴリズムを考案し、ゴール駆動ラーニンググループの動的構成及びそれに基づく適応型ラーニングコンテンツの推薦サービスを実現するためのメカニズムを開発し、プロトタイプシステムを用いて実験評価を行っている。・関連の研究成果をまとめた研究論文を発表している。

  • 利用者と情報環境の統合モデリングによる適用型学習支援メカニズムの研究開発

    2012  

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    　本研究では、「ユーザ中心」の理念に基づき、クラウド環境における利用者の情報アクセス行動や学習活動を解析し、利用者と情報環境の状況やコンテキストを考慮した統合モデリング手法を提案し、基盤モデルを構築するとともに、利用者のニーズに適合した利用者主導の適応型学習支援メカニズムおよび関連のアルゴリズムを研究開発する。本年度では、・クラウド環境における利用者の情報アクセス行動や学習活動を解析し、利用者と情報環境の状況やコンテキストを考慮した統合モデリングを実現するための統合情報環境のフレームワークを提案し、それに基づき、利用者の利便性とシステムの柔軟性を両立させるスケーラブルなサービス指向でありながら、ユーザモデルに基づく個人に適応する学習統合支援環境の基盤モデルを構築している。・利用者の情報アクセス行動または学習活動からユーザコンテキストをキャプチャーし、ユーザモデルを動的に作成する手法を提案している。・これまで提案している利用者とシステムのインタラクションに基づく逐次適応モデルと、新たに開発した挙動解析に基づく最適化プロセス推薦モデルを統合し、それに基づく目的駆動型学習プロセスナビゲーションシステムを構築している。・利用者の個性を重視しながら利用者間の共通性をも考慮し、利用者の興味とニーズや情報アクセスの変化などを適時に検知するアルゴリズムや、利用者の情報アクセス挙動をパターン化し、挙動パターンの類似度によって過去の成功した学習プロセスを抽出するアルゴリズムを考案し、目標学習者にとって最適化された学習プロセスを推薦する仕組みを開発し、適応型個人化学習サービスとして提供するプロトタイプシステムを構築し、実験的な評価を行っている。・TwitterやFacebookといったソーシャルメディアにおける大量に生成された非構造化ストリームデータ（ソーシャルストリーム）を有機的・効果的な利用が可能な知識情報コンテンツとして組織化するためのアルゴリズムを開発し、プロトタイプシステムを構築し、実験的な評価を行っている。・関連の研究成果をまとめた研究論文を発表している。

  • クラウド環境における適応型学習統合支援メカニズムの開発と実証実験システムの構築

    2011  

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    　近年、ソーシャルコンピューティングやライフログが声高に叫ばれ、クラウドサービスをはじめとするサービス・コンピューティングの研究や利活用が盛んに行われている。その一方、情報通信技術を活用したｅ－ラーニングは、何時でも何処でも求められる教育が手に入る技術として、研究開発が盛んに行われ、広く活用されている。クラウドサービスを利用した教育・学習資源とデジタルコンテンツの共有活用は、高等教育機関のみならず、社会人を対象とする職業訓練や特殊技能の習得、在職研修など企業や一般社会でも可能となり、持続発展可能な生涯学習社会の実現に向けて重要な意味をもつと考えられる。しかし、従来の多くのｅ－ラーニング支援システムは、先進な技術を利用した高度な機能の取り入れに重点を置く一方、各学習者のバックグランドや学習能力、現在の学習環境など個人的な特性といった人間的な側面はあまり考慮されていない。学習者は与えられたシステムと機能しか利用できなく、受動的に進めざるを得なかった。　そこで、本研究では、「ユーザ中心」の理念に基づき、クラウド環境における利用者の情報アクセス行動や学習活動を解析して、それに基づくラーニングオブジェクトのネットワークモデルを構築するとともに、利用者のニーズに適合した学習コンテンツをサービスとして提供する利用者主導の適応型学習統合支援システムを提案し、プロトタイプシステムを構築し、評価実験を行う。本年度では、　・利用者の情報アクセス行動や学習活動をソーシャルネットワーク分析手法によりマイニングし、ラーニングオブジェクトの内側の属性と他のラーニングオブジェクトとの関連性や利用者の関係やソーシャル的な要素を複合的に考慮したネットワークモデルを提案している。　・ソーシャルメディアから続々と大量に生成された構造化されていないデータに対応するため、これまで提案してきたユビキタス・パーソナル・スタディ（Ubiquitous Personal Study、略してUPS）を拡張し、ソーシャライズドUPS（Socialized Ubiquitous Personal Study、略してS- UPS）フレームワークを提案し、クラウド環境をベースにした試作システムを構築している。　・マイクロブロックサービスとS- UPS試作システムを統合し、ブレンディッドラーニング支援環境として実験的に試用し、実験評価を行っている。　・関連の研究成果をまとめた研究論文を発表している。

  • 何時でも何処でも手軽に使える利用者主導のサービス指向学習支援環境の構築と実証実験

    2008   シュティフ　ロマン

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    　近年、所謂Web 2.0が声高に叫ばれ、Webサービスをはじめとするサービス・コンピューティングの研究が盛んに行われている。本研究では、人間がテクノロジに迎合するのではなく、テクノロジが人間に適合するという「人間中心」の理念に基づき、サービス・コンピューティング技術を利用して、何時でも何処でも手軽に使える利用者主導のサービス指向学習支援環境を提案し、その基盤モデルを構築するとともに、初歩的な実証実験を行うものである。　これまで、個人の情報アクセスとコンテンツ共有を統合管理するメタファーとしてUPS (Ubiquitous Personal Study、ユビキタス個人書斎)およびそれを支援するためのフレームワークを提案している。本年度では、さらに、ユーザプロファイリングやコンテキストアウェアネス技術を活用し、システムが利用者に適合するメカニズムの開発および、Webサービスのマッシュアップによるプロトタイプシステムの試作を行っている。また、利用者のさまざまな情報探索行動からユーザコンテキストをキャプチャーすることにより動的ユーザモデルを構築し、それに基づき、人間のニーズにより適合した、何時でも何処でも手軽に使える利用者主導のサービスを提供するFlowable Service Modelを提案し、関連の研究成果をまとめた研究論文を発表している。

  • 人間中心のユニバーサル・ユビキタス情報アクセス共有活用支援環境の構築

    2007   シュティフ　ロマン

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    　情報通信技術（ＩＣＴ）の急速な進歩に伴い、何時でも何処でも誰でも使えるユビキタスネットワーク社会のインフラが整いつつある。このような社会であらゆる人がＩＣＴの恩恵を実感でき、安心して快適で便利な生活をしていくためには、誰もが時間的、空間的、身体的制約、知識、言語の壁を超えて、手軽に使いこなせる情報環境やユーザーインターフェースが必要不可欠である。本研究では、ユビキタス環境において、ライフタイムにわたる情報アクセス共有活用のあり方について検討し、それを支援するシステムを実現するための主な問題と課題を明らかにし、人間を中心に据えたアプローチと関連技術を研究開発し、ロングタームにわたるユビキタス情報アクセス・マネジメント・共有活用支援環境を構築し、実証実験を行うことを目指している。　本年度では、まず、共有・共同利用を念頭に、ロングタームにわたるユニバーサル・ユビキタス情報アクセス共有活用支援環境を実現するために、利用者の利便性とシステムの柔軟性やスケーラビリティの両立を可能とする人間中心のサービス指向アプローチについてサーベイや研究調査を行った。また、利用者の情報アクセス行動を推定する逐次適応モデルなどを提案し、人間の情報行動をモデル化するとともに、情報探索・推薦、情報アクセス・一括管理、共有活用を支援するプロトタイプシステムとして、BESS（Better Search and Sharing、「よりよい検索・共有」）やUPS（Ubiquitous Personal Study、「ユビキタス・パーソナル・スタディ」）、モバイル検索のためのスクロールなしのインタフェースなどを研究開発し、実験評価を行っている。

  • サービス指向ユビキタス・ラーニング支援環境の構築と実証実験

    2007   シュティフ　ロマン

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    　近年、Webサービスをはじめとするサービス・コンピューティングの研究が盛んに行われ、新たな学際的な研究分野としてサービス科学を提唱されている。本研究は、利用者主導のサービス指向ユビキタス・ラーニング支援システムを提案し構築するとともに、多様な利用者の異なる個性、能力、ニーズなどに柔軟に対応でき、現在普及しつつあるブロードバンドネットワーク環境を生かした高度な機能を研究開発することを目指すものである。本研究でいうサービスは、狭義的なｅ－サービス（Webサービス）やｕ－サービス（ユビキタス・サービス）にとどまらず、利用者の利便性とシステムの柔軟性やスケーラビリティを両立させた広義的なｕ－サービス（ユニバーサル・サービス）をめざすものである。サービスは、コンピュータやネットワークを人間に奉仕させるものだと位置づけるものである。　本年度では、デジタルキャンパスとフィジカルキャンパスとのシームレスな融合をめざす「成長するキャンパス（Growing Campus）」の理念のもと、利用者主導のユビキタス・ラーニングを支援するサービス指向モデルを提案し、さらに、実証環境システムのプロトタイプとして、ユビキタス・パーソナル・スタディ（Ubiquitous Personal Study、略してUPS）というメタファーを提案している。UPSは、個人のためにすべての情報・情報アクセスを一括管理・組織化するとともに、個人ポータルとして情報のアクセス共有活用を支援する統合環境を提供するものであり、一種の個人化されたデジタル仮想書斎である。個々に分散したUPS はさらにクロースSNS（Cross Social Networking Service、略してXSNS）を通して相互連結により友人関係を確立し、情報共有、情報推薦、友人推薦などの機能を提供する基盤プラットフォームとなる。UPSは、WEBサービスのマッシュアップによるシステムの試作を行い、実験評価を進めている。

  • 学習者と学習環境のインタラクションをさりげなく支援する知能情報メディアの研究

    2005  

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    　従来の多くのｅ－ラーニングシステムは、人間的な部分が抜け落ちた、単なる知識や情報の伝達でしかない。ラーニングコミュニティなど知識情報共有型ｅ－ラーニングシステムにおいて、学習コンテンツの作成・流通・再利用における統一規格や、異なるシステム間の互換性など多くの問題点と課題が残されている。本研究は、それらの問題を総合的に解決することを目指して、学習者と学習環境のインタラクションをさりげなく支援するとともに、人間とのインタラクションを通じて進化する知能情報メディアを提案し、モデル化とそのあり方について探求し明らかにするものである。　本年度では、これまでの研究において提案されている「社会的インタラクション支援フレームワーク」に基づき、知能情報メディアの基本モデルの洗練化をはかり、そのうえ、学習者間の社会的相互作用を促進するとともに、学習者と学習環境のインタラクションを支援する仕組みを考案し、サービス指向ユビキタス・ラーニング支援やスケーラブルな情報共有システムなどの実証環境の構築への適用を試みた。さらに、オントロジに基づくコンテキスト・アウェア・モデルを提案し、人間と情報環境のインタラクションをさりげなく支援することが可能な能動的な知能情報メディアへの展開の可能性について検討した。

  • 利用者主導の知識情報共有型ｅ－ラーニング支援環境の研究開発

    2005  

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    　情報通信技術を活用したｅーラーニングは、いつでもどこでも求める教育が手に入るシステムとして、盛んに研究開発が行われ、活用されている。しかし、ｅ－ラーニングを含めて一般的に自己学習は、学習者が孤独感に陥ったり、学習ペースがつかめず脱落したり、学習者の意欲や教育効果を殺ぐなど、挫折するケースが見受けられる。本研究は、ピア・ツー・ピア（P2P）ネットワーク技術を利用して、利用者主導の知識情報共有型ｅ－ラーニング支援システムを提案し、多様な利用者の異なる個性、能力、ニーズなどに柔軟に対応できる高度な機能を研究開発するとともに、教育／学習現場において評価実験を行いながら、問題点を明らかにし、改良を加え、その有効性を実証し、そのうえ、新たな知識情報共有型ｅ－ラーニング支援環境を構築するものである。　本年度では、従来のクライアント／サーバモデルに基づいたｅ－ラーニング・モデルと比較しながら、P2Pネットワークの特徴を生かした学習モデルおよび学習者個人のニーズや能力に柔軟に対応できる利用者主導のｅ－ラーニング支援仕組みを考案するとともに、これまでの研究において提案されている「社会的インタラクション支援フレームワーク」を発展させ、サービス指向ユビキタス・ラーニング支援環境を提案し、プロトタイプシステムの構築を行った。さらに、分散型P2P ネットワークと集中型個人・グループ・メディア・ツールの統合によるスケーラブルな知識情報共有システムを提案し、その試作を進んでいる。

  • 学習者と学習環境のインタラクションをさりげなく支援する知能情報メディアの研究

    2004  

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    　協調学習に基づくコミュニティ型ｅ－ラーニングシステムでは、学習者の自発的な参加および知識情報の共有が奨励される。実践において、こういった学習者主導型ｅ－ラーニングの難しさの１つとして、仮想環境におけるコミュニケーションとインタラクションにあると指摘されている。本研究は、学習者と学習環境のインタラクションをさりげなく支援するとともに、人間とのインタラクションを通じて進化する知能情報メディアを提案するものである。　本年度では、これまでの研究において提案されている仮想環境メディアの考え方を発展させ、知能情報メディアの基本要件を検討し、モデル化を試みるとともに、知能情報メディアモデルのコアとなる「社会的インタラクション支援フレームワーク」を考案した。また、利用者の個性の差異を超えて、相互理解を促進する仕組みを有し、人間とのインタラクションを通じて進化させるために、知能情報メディアに「暗黙の知」を用いた支援メカニズムを埋め込み、学習環境とコンテンツとのシームレスな統合をはかり、学習者同士間のコミュニケーション、学習者と学習環境やコンテンツとのインタラクションをさりげなく支援する手法を提案している。このような「支援メカニズム」を実現するためには、（１）人間の会話や挙動を観察し、人間とのインタラクションを通じて人間の意図を理解できる知的エージェント技術、（２）多様なデータと知識を統一規格で記述できるXML およびそれを発展させた技術、（３）利用者間のダイレクトなコミュニケーションと情報交換や、対等な知識共有と効率的な配送仕組みを提供できるピア・ツー・ピア（P2P）ネットワーク技術、を融合したアプローチを考案し、本年度では、「社会的インタラクション支援フレームワーク」に基づき、ユビキタスラーニングを実現するためのP2P型プロトタイプシステムを構築し、初歩的な実験を行った。

  • ピア・ツー・ピア技術を活用したラーニングコミュニティの研究

    2003  

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    　高度情報ネットワーク化社会において、知識の更新のペースがますます速めており、従来の学校、大学での教育では対応できなくなりつつある。そのため、生涯を通じた多様な学習者を対象とする教育／学習システムが求められている。　本研究は、ピア・ツー・ピア（P2P）技術を利用して、多様な学習者に対して広く開かれた新たなコミュニティ型ｅーラーニングシステムを提案することを目的とする。本年度では、学習者個々のニーズに柔軟に対応できるパーソン・ツー・パーソンｅーラーニングモデルを新たに考案し、P2Pネットワークの特徴を生かした教授／学習支援環境のあり方について検討するとともに、従来のクライアント／サーバモデルに基づいたｅーラーニングモデルとの比較を行った。また、ｅーラーニングに適したP2P技術とは何かについて、サーベイを行い、ラーニングコミュニティの特徴を発揮でき、従来のｅーラーニングシステムにおける学習者個性の喪失や孤独感、学習ペースがつかめにくいなどの問題を改善し、ｅーラーニングに適したP2P仕組みの提案を行った。それをもとに、ピア・ツー・ピア型ラーニングコミュニティにおけるコミュニケーションやコラボレーションを支援し、学習者個人のニーズや能力に応じた学習内容や進み方を設定可能な支援環境とグループウェアツールを設計し、試作を行った。さらに、ピア・ツー・ピア型ラーニングコミュニティを利用するためのクライアントシステムとGUIインターフェースをも試作し、初歩的な実験評価を行い、これからの改良・改善策をまとめた。　従来の多くのｅーラーニングシステムは、人間的な部分が抜け落ちた、単なる情報や知識の伝達でしかない。本研究は、P2P技術の利点とラーニングコミュニティの特徴を発揮し、融合することによって、ピア・ツー・ピアｅーラーニングに適した学習モデルと仕組みづくりを探求し、従来のｅーラーニングにおける問題点を解決し、改善するものである。

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