文 鄭 (ブン テイ)

写真a

所属

理工学術院 基幹理工学部

職名

講師(任期付)

学内研究所等 【 表示 / 非表示

  • 2020年
    -
    2022年

    国際情報通信研究センター   兼任研究員

学歴 【 表示 / 非表示

  • 2013年09月
    -
    2019年02月

    早稲田大学  

  • 2005年09月
    -
    2009年06月

    武漢大学  

学位 【 表示 / 非表示

  • Waseda University   博士

所属学協会 【 表示 / 非表示

  •  
     
     

    IEEE

  •  
     
     

    電子情報通信学会

 

研究分野 【 表示 / 非表示

  • 情報ネットワーク

研究キーワード 【 表示 / 非表示

  • IoT

  • ブロックチェーン

  • 人工知能

  • 通信ネットワーク

  • 災害管理

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論文 【 表示 / 非表示

  • Congestion-aware suspicious object detection system using information-centric networking

    Xin Qi, Toshio Sato, Keping Yu, Zheng Wen, San Hlaing Myint, Yutaka Katsuyama, Kiyohito Tokuda, Takuro Sato

    2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021    2021年01月

     概要を見る

    Deadly diseases and terrorist attacks are greatly threatening human safety, which challenges global security. To address this issue, urban surveillance systems are being applied at a rapid pace with mature but inefficient solutions in large scale networks. When a surveillance network is managing the data generated from multiple edge nodes, it is easy to create congestions due to concentrated data traffic and inefficient data delivery mechanism. In parallel, 5G technology, cope with explosive mobile data traffic growth and massive device connections, can realize a true 'Internet of Everything' and build the social and economical digital transformation. In this paper, in the context of 5G technology, we propose an Information-Centric Networking (ICN) surveillance system based on our designed Suspicious Object Network System (SONS) over the concept of next-generation networking. In this solution, the edge nodes in the network distribute the computing and data storage requirements. We first describe the current surveillance issues and our proposed system architecture. Then we use simulation to verify and evaluate the system performance between legacy all-to-one centralized surveillance system and ICN based decentralized surveillance system.

    DOI

  • 3D Remote Healthcare for Noisy CT Images in the Internet of Things Using Edge Computing

    Jing Zhang, Dan Li, Qiaozhi Hua, Xin Qi, Zheng Wen, San Hlaing Myint

    IEEE Access   9   15170 - 15180  2021年

     概要を見る

    Edge computing can provide many key functions without connecting to centralized servers, which enables remote areas to obtain real-time medical diagnoses. The combination of edge computing and Internet of things (IoT) devices can send remote patient data to the hospital, which will help to more effectively address long-term or chronic diseases. CT images are widely used in the diagnosis of clinical diseases, and their characteristics are an important basis for pathological diagnosis. In the CT imaging process, speckle noise is caused by the interference of ultrasound on human tissues, and its component information is complex. To solve these problems, we propose a 3D reconstruction method for noisy CT images in the IoT using edge computing. First, we propose a multi-stage feature extraction generative adversarial network (MF-GAN) denoising algorithm. The generator of MF-GAN adopts the multi-stage feature extraction, which can ensure the reconstruction of the image texture and edges. Second, we apply the denoised images generated from the MF-GAN method to perform the 3D reconstruction. A marching cube (MC) algorithm based on regional growth and trilinear interpolation (RGT-MC) is proposed. With the idea of regional growth, all voxels containing iso-surfaces are selected and calculated, which accelerates the reconstruction efficiency. The intersection point of the voxel and iso-surface is calculated by the trilinear interpolation algorithm, which effectively improves the reconstruction accuracy. The experimental results show that MF-GAN has a better denoising effect than other algorithms. Compared to other representative 3D algorithms, the RGT-MC algorithm greatly improves the efficiency and precision.

    DOI

  • Communication-Based Book Recommendation in Computational Social Systems

    Long Zuo, Shuo Xiong, Xin Qi, Zheng Wen, Yiwen Tang

    Complexity   2021  2021年

     概要を見る

    This paper considers current personalized recommendation approaches based on computational social systems and then discusses their advantages and application environments. The most widely used recommendation algorithm, personalized advice based on collaborative filtering, is selected as the primary research focus. Some improvements in its application performance are analyzed. First, for the calculation of user similarity, the introduction of computational social system attributes can help to determine users' neighbors more accurately. Second, computational social system strategies can be adopted to penalize popular items. Third, the network community, identity, and trust can be combined as there is a close relationship. Therefore, this paper proposes a new method that uses a computational social system, including a trust model based on community relationships, to improve the user similarity calculation accuracy to enhance personalized recommendation. Finally, the improved algorithm in this paper is tested on the online reading website dataset. The experimental results show that the enhanced collaborative filtering algorithm performs better than the traditional algorithm.

    DOI

  • A Lightweight Ledger-Based Points Transfer System for Application-Oriented LPWAN

    Keping Yu, Kouichi Shibata, Takanori Tokutake, Rikiya Eguchi, Taiki Kondo, Yusuke Maruyama, Xin Qi, Zheng Wen, Toshio Sato, Yutaka Katsuyama, Kazue Sako, Takuro Sato

    2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020     1972 - 1978  2020年12月

     概要を見る

    Along with the rapid development of IoT technology, Low power wide area network (LPWAN) has become the primary technology for IoT access today due to its characteristics of low cost, low power consumption, long-distance, and mass connections. At the same time, the points transfer system, as a typical third-party payment application, is attracting more and more extensive attention from academia and industry. Therefore, the research and development of a points transfer system for LPWAN are of great practical importance. However, the current points transfer systems often face problems such as centralization, high requirements on node computing power, and low robustness, which are difficult to adapt to the development of IoT. To address these problems, we propose a lightweight ledger-based points transfer system for application-oriented LPWAN. The system enables the points transfer between tags in LPWAN, where both tags and nodes are limited. Furthermore, it can be utilized even in disaster situations. Experimental results show that our proposed system is intensely robust and has a lower processing time than Bitcoin-like systems to cope with LPWAN's requirement.

    DOI

  • AI-Based W-Band Suspicious Object Detection System for Moving Persons Using GAN: Solutions, Performance Evaluation and Standardization Activities

    Yutaka Katsuyama, Keping Yu, San Hlaing Myint, Toshio Sato, Zheng Wen, Xin Qi

    2020 ITU Kaleidoscope: Industry-Driven Digital Transformation, ITU K 2020    2020年12月

     概要を見る

    With the intensification of conflicts in different regions, the W-band suspicious object detection system is an essential security means to prevent terrorist attacks and is widely used in many crucial places such as airports. Because artificial intelligence can perform highly reliable and accurate services in the field of image recognition, it is used in suspicious object detection systems to increase the recognition rate for suspicious objects. However, it is challenging to establish a complete suspicious object database, and obtaining sufficient millimeter-wave images of suspicious objects from experiments for AI training is not realistic. To address this issue, this paper verifies the feasibility to generate a large number of millimeter-wave images for AI training by generative adversarial networks. Moreover, we also evaluate the factors that affect the AI recognition rate when the original images used for CNN training are insufficient and how to increase the service quality of AI-based W-band suspicious object detection systems for moving persons. In parallel, all the international standardization organizations have been collectively advancing the novel technologies of AI. We update the reader with information about AI research and standardization related activities in this paper.

    DOI

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Misc 【 表示 / 非表示

  • Using linguistic properties of place specification for network naming to improve mobility performance

    Jairo López, Quang Ngoc Nguyen, Zheng Wen, Keping Yu, Takuro Sato

    Sensors (Switzerland)   19 ( 13 )  2019年07月

     概要を見る

    By considering the definitions and properties from the field of linguistics regarding place specification, a questionnaire that can be used to improve naming in networks is obtained. The questionnaire helps introduce the idea of place specification from linguistics and the concept of metric spaces into network naming schemes. The questionnaire results are used to improve the basic Information-Centric Networking (ICN) architecture’s notoriously lax network naming structure. The improvements are realized by leveraging components from the Named-Node Network Architecture, a minor ICN design, to supply the resulting network architecture with the properties the questionnaire highlights. Evaluation results from experiments demonstrate that modifying the network architecture so that the proposed questionnaire is satisfied results in achieving high mobility performance. Specifically, the proposed system can obtain mean application goodput at above 88% of the ideal result, with a delay below 0.104 s and with the network time-out Interest ratio below 0.082 for the proposed single mobile push producer, single mobile consumer scenario, even when the nodes reach the maximum tested speed of 14 m/s.

    DOI PubMed

  • Content-oriented disaster network utilizing named node routing and field experiment evaluation

    Xin Qi, Zheng Wen, Keping Yu, Kazunori Murata, Kouichi Shibata, Takuro Sato

    IEICE Transactions on Information and Systems   E102D ( 5 ) 988 - 997  2019年05月

     概要を見る

    Low Power Wide Area Network (LPWAN) is designed for low-bandwidth, low-power, long-distance, large-scale connected IoT applications and realistic for networking in an emergency or restricted situation, so it has been proposed as an attractive communication technology to handle unexpected situations that occur during and/or after a disaster. However, the traditional LPWAN with its default protocol will reduce the communication efficiency in disaster situation because a large number of users will send and receive emergency information result in communication jams and soaring error rates. In this paper, we proposed a LPWAN based decentralized network structure as an extension of our previous Disaster Information Sharing System (DISS). Our network structure is powered by Named Node Networking (3N) which is based on the Information-Centric Networking (ICN). This network structure optimizes the excessive useless packet forwarding and path optimization problems with node name routing (NNR). To verify our proposal, we conduct a field experiment to evaluate the efficiency of packet path forwarding between 3N+LPWA structure and ICN+LPWA structure. Experimental results confirm that the load of the entire data transmission network is significantly reduced after NNR optimized the transmission path.

    DOI

  • A novel base-station selection strategy for cellular vehicle-to-everything (C-V2X) communications

    Qiaozhi Hua, Keping Yu, Zheng Wen, Takuro Sato

    Applied Sciences (Switzerland)   9 ( 3 )  2019年02月

     概要を見る

    Cellular vehicle-to-everything (C-V2X) communication facilitates the improved safety, comfort, and efficiency of vehicles and mobility by exchanging information between vehicles and other entities. In general, only the macrocell or only the femtocell is the communication infrastructure for C-V2X. Currently, a macro-femtocell network is used as the new C-V2X networking architecture. However, there are two unresolved problems for C-V2X in macro-femtocell networks. Firstly, vehicle mobility requires the frequent switching of connections between different base stations; invalid switching results in worse communication quality. Secondly, unintelligent base station selections cause network congestion and network-load imbalance. To address the above challenges, this paper proposes a base station selection strategy based on a Markov decision policy for a vehicle in a macro-femtocell system. Firstly, we present a mechanism to predict received signal strength (RSS) for base station selection. Secondly, a comparing Markov decision policy algorithm is presented in C-V2X. To the best of our knowledge, this is the first attempt to achieve predicted RSS based on a Markov decision policy in C-V2X technology. To validate the proposed mechanism, we simulated the traditional base station selection and our proposal when the vehicle moved at different speeds. This demonstrates that the effectiveness of a traditional base station selection policy is obvious only at high speeds, and this weakness can be resolved by our proposal. Then, we compare our solution with the traditional base station selection policy. The simulation results show that our solution is effective at switching connections between base stations, and it can effectively prevent the overloading of network resources.

    DOI

  • Design and performance evaluation of content-oriented communication system for iot network: A case study of named node networking for real-Time video streaming system

    Xin Qi, Yuwei Su, Keping Yu, Jingsong Li, Qiaozhi Hua, Zheng Wen, Jairo Lopez, Takuro Sato

    IEEE Access   7   88138 - 88149  2019年01月

     概要を見る

    Information-Centric Networking (ICN) was born in an era that more and more users are shifting their interests to the content itself rather than the location where contents are stored. This paradigm shift in the usage patterns of the Internet, along with the urgent needs for content naming, pervasive caching, better security, and mobility support, has prompted researchers to consider a radical change to the Internet architecture. However, ICN is still in its infancy and development stage, and many issues still exist and need to be addressed. The common ICN architecture is lacking the host-centric communication ability and difficult to provide seamless mobility in current solutions. To solve this problem, our team had proposed the Named-Node Networking (3N) concept, which not only naming the content but also naming the node and it proved to have better performance of providing seamless mobility in the simulation. However, the previous contributions were limited in the 3N namespace for seamless mobility support in both producer and consumer. In this paper, we have proposed a 3N system which includes 3N naming, data delivery, mobility support, and data security. Moreover, we have created a 3N-based real-Time video streaming system to evaluate data delivery performance and mobility handoff performance. The evaluation result proofs that our system performs better than TCP video streaming in a multi-client situation and a WiFi-based handoff was demonstrated.

    DOI

  • Content-Oriented Surveillance System Based on ICN in Disaster Scenarios

    Koki Okamoto, Toru Mochida, Daichi Nozaki, Zheng Wen, Xin Qi, Takuro Sato

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2018-November   484 - 489  2018年07月

     概要を見る

    This paper deals with an efficient image object detection method for use in a disaster prevention network that uses information-centric networking (ICN). In ICN for disaster prevention, a large number of surveillance cameras are arranged, and disaster image contents corresponding to the user's requests are distributed directly from the node attached to the surveillance camera. At this time, the name of the content requested by the user does not necessarily match the name of the image acquired by the surveillance camera. In this paper, the content requested by the user is processed and named using natural language processing (NLP). In addition, the image content from the surveillance camera is named using artificial intelligence technology. In this way, a method for improving the hit ratio between users and cameras was established. Furthermore, the volume of the interest packets decreases based on the information which area often occurs disaster. As a result, the network efficiency of ICN can be improved.

    DOI

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産業財産権 【 表示 / 非表示

  • FIB検索器、FIB検索方法、及びプログラム

    南 勇貴, 佐藤 拓朗, 文 鄭, 斉 欣

    特許権

    J-GLOBAL

共同研究・競争的資金等の研究課題 【 表示 / 非表示

  • サービスに応じたスライス動的生成・管理機能の実証と標準化を目的とする日欧連携5G移動通信基盤テストベッドの研究開発

    研究期間:

    2016年04月
    -
    2019年06月
     

  • IoT共通基盤技術の確立実証高効率かつセキュアなIoTデータ収集・配信ネットワーク制御技術の確立

    研究期間:

    2017年04月
    -
    2019年03月
     

  • 止まらない通信網”を活用した命をつなぐ減災推進事業

    研究期間:

    2016年04月
    -
    2018年03月
     

 

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