Background: In the post–COVID-19 pandemic era, many countries have launched apps to trace contacts of COVID-19 infections. Each contact-tracing app (CTA) faces a variety of issues owing to different national policies or technologies for tracing contacts. Objective: In this study, we aimed to investigate all the CTAs used to trace contacts in various countries worldwide, including the technology used by each CTA, the availability of knowledge about the CTA from official websites, the interoperability of CTAs in various countries, and the infection detection rates and policies of the specific country that launched the CTA, and to summarize the current problems of the apps based on the information collected. Methods: We investigated CTAs launched in all countries through Google, Google Scholar, and PubMed. We experimented with all apps that could be installed and compiled information about apps that could not be installed or used by consulting official websites and previous literature. We compared the information collected by us on CTAs with relevant previous literature to understand and analyze the data. Results: After screening 166 COVID-19 apps developed in 197 countries worldwide, we selected 98 (59%) apps from 95 (48.2%) countries, of which 63 (66.3%) apps were usable. The methods of contact tracing are divided into 3 main categories: Bluetooth, geolocation, and QR codes. At the technical level, CTAs face 3 major problems. First, the distance and time for Bluetooth- and geolocation-based CTAs to record contact are generally set to 2 meters and 15 minutes; however, this distance should be lengthened, and the time should be shortened for more infectious variants. Second, Bluetooth- or geolocation-based CTAs also face the problem of lack of accuracy. For example, individuals in 2 adjacent vehicles during traffic jams may be at a distance of ≤2 meters to make the CTA trace contact, but the 2 users may actually be separated by car doors, which could prevent transmission and infection. In addition, we investigated infection detection rates in 33 countries, 16 (48.5%) of which had significantly low infection detection rates, wherein CTAs could have lacked effectiveness in reducing virus propagation. Regarding policy, CTAs in most countries can only be used in their own countries and lack interoperability among other countries. In addition, 7 countries have already discontinued CTAs, but we believe that it was too early to discontinue them. Regarding user acceptance, 28.6% (28/98) of CTAs had no official source of information that could reduce user acceptance. Conclusions: We surveyed all CTAs worldwide, identified their technological policy and acceptance issues, and provided solutions for each of the issues we identified. This study aimed to provide useful guidance and suggestions for updating the existing CTAs and the subsequent development of new CTAs.

Owing to the aging of the rural population in the hilly and mountainous areas of Japan, mowing on narrow ridges and steep slopes is done manually by the elderly—individuals over 65 years of age. Studies have shown that many accidents that occurred during mowing were caused by workers’ unstable posture, especially when mowing on steep surfaces where there is a high risk of falling. It is necessary to analyze the body movements of mowing workers to elucidate the elements related to the risk of falls. Therefore, in this study, based on a high-precision motion-capture device and a series of experiments with elderly, skilled mowing workers, we focused on the movements of mowing. We sought to identify effective and safe mowing patterns and the factors that lead to the risk of falls. In various mowing styles, compared to the stride (S) and downward (D) mowing patterns, the basic (B) and moving (M) patterns were the most efficient; however, the risk of falls was also the highest among these patterns. While mowing, workers need to pay more attention to their arm strength and take appropriate measures to reduce the risk of falls according to their age and physique. The results can be used as data for the development of fall-detection systems and offer useful insights for the training of new mowing workers.

Previous studies have shown that about 90% of traffic accidents are due to human error, which means that human factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes a braking motion. However, most studies have mounted sensors on the brake pad, ignoring to some extent an analysis of the driver's behavior before the brake pad is pressed (pre-braking). Therefore, to determine the effect of different human factors on drivers' pre-braking behaviors, this study focused on analyzing drivers' local joints (knee, ankle, and toe) by a motion capture device. A Hilbert–Huang Transform (HHT)-based local human body movement analysis method was used to decompose the realistic complex pre-braking actions into sub-actions such as intrinsic mode functions (IMF1, IMF2, etc.). Analysis of the results showed that IMF1 is a common and necessary action when pre-braking for all drivers, and IMF2 may be the safety assurance action that allows right-foot transverse movement at the beginning part of the pre-braking process. We also found that the experienced, male, and Phys.50 groups may have consistent characteristics in the HHT scheme, which could mean that such drivers would have better performance and efficiency during the pre-braking process. The results of this study will be useful in decomposing and discerning the specific actions that lead to accidents, providing insights into driver training for novice drivers, and guiding the construction of daily automated driver assistance or accident prevention systems (advanced driver assistance systems, ADASs).

Background and objectives: Infection with human papillomavirus (HPV) is the main cause of cervical cancer, and vaccination is an effective method to prevent HPV infection. In Japan, adverse reactions were reported in some HPV-vaccinated people in March 2013, and while Japan’s Ministry of Health, Labor, and Welfare withdrew active recommendation of the vaccine in June 2013, the social movement to refuse vaccination has continued. The Ministry of Health, Labor, and Welfare (MHLW) has devised a plan to accurately disseminate information that promotes vaccination, but less than 1% of the eligible population was vaccinated, and the number has not increased. Besides, inaccurate information about health information can disseminate rapidly on social networks. Social networking services (SNS), mainly used by young people, can be used by the public to obtain medical information. However, according to the World Health Organization (WHO), SNSs are prone to spreading inauthentic and misleading information when it comes to information related to health and medical care. “Infodemic” is defined as a situation in which unidentified and false information is widely disseminated on SNS, causing WHO to issue international alerts. This study aimed to organize information about HPV vaccination disseminated on SNS in Japan. Methods: We extracted 208 tweets with the keyword “HPV vaccine” posted in Japan between April 1, 2014, and September 30, 2017. The extracted tweets included data points such as ID, language, posting date and time, and latitude and longitude. The location information of the senders was obtained from the latitude and longitude, and the tweets were organized by prefecture, city, town, village, and ID. Then, we evaluated whether the information at the URLs was accurate by examining retweets, likes, and the number of comments on the tweet. Python version 3.7.7 was used to extract the tweets. Results: The results of classification of the tweets by prefecture are as follows: the Hokkaido prefecture accounted for four tweets; the northeast, six tweets; southern Kanto, 123 tweets; northern Kanto-Koshin, six tweets; Hokuriku, five tweets; Tokai, 35 tweets; Kinki, 10 tweets; Chugoku 4 tweets; Shikoku, three tweets; and Kyushu, nine tweets. A total of 93 users posted tweets; four users posted five or more tweets; 14 users posted 2–4 tweets, and 75 users posted one tweet. In particular, 66 tweets in Kanagawa prefecture, 14 tweets in Shizuoka prefecture, and two tweets in Tokyo were posted from the same ID. Regarding the type of tweet, there were 109 tweets, 65 retweets, and 34 replies. There were 137 tweets with and 71 tweets without URLs. When organized by the linked URL, 50 posts linked to a blog, 46 posts linked to a news item, seven posts linked to Facebook, five posts linked to a government agency homepage, four posts linked to YouTube, three posts linked to the home page of the City Council rep, two posts linked to a medical site, and 20 posts linked to other sources that could not be categorized. In terms of the authenticity of the posts, 25 tweets were judged as “accurate,” 14 were judged to be “inaccurate,” and 16 were judged as “unknown.” We classified the posts as follows; “accurate” for those that contained accurate information and “inaccurate” for those that contained inaccurate information. Discussion: The distribution of tweets and the uneven distribution of the users suggest that few people spread information about the HPV Vaccine on Twitter in Japan. Regarding the content, more than half of the tweets could not be judged as accurate or inaccurate because the verification results regarding adverse reactions of the HPV vaccine were not published at the time of sending, and in news and blog articles, personal opinions were stated rather than authentic medical information. In this study, we clarified the characteristics of tweets regarding HPV vaccination in Japan and the status of transmission. In the future, it will be necessary to change the keywords and time periods for which tweets need to be extracted, and the data set used for the analysis will need to be compared and examined.

The driver's driving experience is one of the important factors affecting his or her behaviors. Prior studies have noted the effect of driving experiences on drivers' eye-movements when right-turning. However, related studies usually focused on the accident scenarios, for drivers' eye-movements on daily driving when facing right-turn, the effects of drivers' experience remain unknown. Therefore, according to design and apply a set of experiments, this paper focused on the analysis of driver's eye-movements during the daily right-turn task to compare the differences between Experienced and Novice drivers. A total of 10 drivers were invited and be classified into two groups (Experienced and Novice) to participate in the experiments. All of the drivers are driving on the right-hand side of the road, and the steering wheel is on the left side of the vehicle. The aimed data were collected by a set of glasses type eye-tracker and be further classified into four driving vision-based AOI (Areas of Interest). The results of Mann-Whitney U-tests showed that Novice drivers have a disordered line of sight and tend to spend more attention on their right view and switch their line of sight back and forth between the AOIs. Moreover, Experienced drivers more tend to keep their view directly in front of their heads instead of using the peripheral vision. The results of this study may provide guidelines to prevent accidents in Advanced Driver Assistance Systems (ADAS) and offers useful insights for the training of new drivers.

Many accidents are caused by drivers abruptly braking, or by their braking-related behaviors. However, it is challenging to collect data on the pre-braking behaviors of drivers by using sensors installed on vehicles, because of which this issue has not been adequately studied. In this paper, we focus on the differences in pre-braking behaviors between experienced and novice drivers by analyzing data collected from a motion capture device attached to them. The results of experiments and the Mann-Whitney U-test show that experienced drivers usually set their feet farther than novice drivers from the braking pad to reduce the chances of pressing it by mistake. However, when they needed to brake, their right foot had a lower response time for pushing the braking pad than novice drivers. The results of this study can provide guidelines for preventing accidents in the development of advanced driver assistance systems and can offer useful insights for training new drivers.

IEEE 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 analytics. Three categories of personal data are identified from an individual & #x0027;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 advice to improve the living quality of an individual. Finally, we report a feasibility study with an application scenario by using personal and environmental data.

© 2018 IEEE. This study used wearable devices and traditional Chinese medicine (TCM) diagnosis, which verifies the promotion of wearable devices on the health habits of the elderly, and the correlation between pulse diagnosis and health. We used wearable devices and TCM diagnosis (including TCM doctor diagnosis and Pulse diagnosis instrument) to record health information for the elderly. One-way repeated measures analysis of variance (ANOVA) was used to determine health changes. Correlation analysis was used to determine the relationship between pulse and health indicators. There was significant change in the number of steps for the elderly before and after using the wearable device. Systolic blood pressure (SBP) was negatively correlated with pulse wave time. Diastolic blood pressure (DBP) was negatively correlated with pulse duration. Pulse diagnosis can be used as an indicator to report the health of the elderly. And used wearable devices can quantify health indicators and improve the health awareness.

In this study, we use wearable devices to monitor the health and physiological indicators of the elderly, and analyze the effects of the elderly's walking steps and sleep as the measurable health and physiological indexes. Eighteen cases of the elderly who received health management services are selected. We establish the generalized linear mixed model, and Pearson correlation analysis result shows statistically significant for the number of walking steps and systolic blood pressure/diastolic blood pressure. The number of walking steps is positively correlated with the systolic/diastolic pressure. The more walking steps and the better the sleep quality, the more stable the daily blood pressure is. Therefore, it is possible to effectively control the elderly's blood pressure by exercising and managing sleeping. It can be better for the elderly to have self-esteem health managed by using wearable devices, and encourage the elderly to exercise at a certain extent.

In 2003, the School of Human Sciences, Waseda University (Japan), established the e-School, Japan's first complete undergraduate program enabling students to earn their bachelor degrees solely through e-learning. Supported by the availability of high-speed Internet connections, it has become possible to economically transmit high-quality videotaped lectures across Japan and throughout the world. Waseda's e-School has many features that contribute to its success, among these are that lecture contents are transmitted with an image quality that allows students to easily read what is written on the blackboard. In addition, online classes are relatively small-21 students on average-and new classes are created to respond to students' needs and interests. This chapter outlines the e-School's first 10 years of operation: Its history, curriculum, administration, and management learning system. Data are also presented for student engagement with the e-School system for the first ten years of operation (2003-2012).

In this study, we concentrate on a feasibility study on personal data analysis for well-being oriented life support. We introduce our basic concept and model to describe the personal data collected from people's daily life, and discuss how to utilize the personal analysis to provide users with the individualized services in their daily lives. Finally, we present the experimental analysis based on people's daily activity data, to demonstrate the feasibility of our proposed approach.

Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals' daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

The world has become an aging society with exponentially increasing social security benefit expenditure and nursing care costs. To help solve these issues and challenges, utilization of advanced ICT is highly expected to allow more elderly people to remain independent for their proactive social participation irrespective of age. In this study, we propose a human-centric safe and secure framework of ubiquitous living environments (Ubi-Liven) for the elderly people towards seamless integration of the cyber-enabled ubiquitous holistic living support system with a physical living environment. We further address and discuss the design and technical issues for the implementation of a smart living environment on the fly under the proposed framework, empowered by ubiquitous assistive technologies such as cloud, IoT and big data analytics based on life logs to provide holistic support for the elderly's activities of daily living and healthcare.

Nowadays, the analysis of social networks, as well as the community evolution has become a hotly discussed topic in social computing field. In this paper, we focus on mining and tracking the dynamic communities based on social networking analysis. Based on a generic framework for the dynamic community discovery, a computational approach is developed to extract users' static and dynamic features for the temporal trend detection. A dynamically socialized user networking model is then presented to describe users' various social relationships. A mechanism is proposed and developed to detect the dynamic user communities, and track their evolving changes. Experiments using Twitter data demonstrate the effectiveness of our method in tracking how communities dynamically create, split, and merge from a group of connected people in social media environments.

As more and more users use the mobile terminals of high computing power, the location-based services (LBS) recommendations for mobile users have become an important and interesting topic. Mobile users are eager to get their interested and reliable services quickly. A considerable number of research works have been dedicated to service recommendation based on users' preferences and locations. In this paper, we study the credibility of recommended services, and propose a set of composite measures on how to provide more reliable services. We further propose the trustworthy Skyline of LBS recommendation in terms of the trust degree based on the newly introduced composite measures to achieve more credibility to provide recommendation services. Experimental results show that our method can recommend desired and trusted services to users.

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.

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.

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.

社会人との交流を基本とした中学生対象のキャリア教育を,総合的な学習の時間の一環として05年〜08年度の4年間実施した.本授業実践では,社会の先輩としての社会人メンターと中学生を,インターネットの電子会議室やSNSで結び,質疑応答を基本としたコミュニケーション機会を提供した点に特徴がある.本研究では,キャリア教育としての本授業実践の評価を検討すると同時に,生徒が社会人に対して行った質問内容の特徴を検討した.量的・質的検討の結果,社会人メンターとの質疑応答機会を提供したことには一定の評価が見られ,生徒の質問の特徴を明らかにすることができた.一方,生徒・メンター間の交流の深化については課題も明らかになった.

様々な職業に対する関心の育成を目的とした中学生対象のキャリア教育を,総合的な学習の時間の一環として,中学校と大学との共同で実施した.本授業実践では,社会の先輩としての社会人メンターと,中学生をインターネット上の電子掲示板で結び,質疑応答を基本としたコミュニケーション機会を提供した.本研究では,キャリア教育としての本授業実践の評価を検討すると同時に,生徒が社会人に対して行った質問内容を分析し,生徒の質問の特徴や仕事観を検討する.量的・質的検討の結果,社会人メンターとの質疑応答機会を提供したことには一定の評価が見られた.また,生徒の質問は,メンターの経験や仕事内容,感情面などに焦点が当てられているという結果が得られた.

本論文では,電子ネットワークを利用した第二言語学習環境における日本人大学生の学習過程について状況論的な視点から分析した.その結果,日本人大学生について次のことが明らかになった.1)文字ベースの学習状況では,過去の英語使用経験に基づき「受験文化」の学習方略を用いる.2)「受験文化」と「実践文化」の英語使用の差異からコンフリクトを覚える。3)「実践文化」への適応過程において,米国人大学生の「語彙パターン」,インターネット上の「翻訳サイト」などの「リソース」を利用する.4)それら「リソース」の利用を通して,受験文化に規定された「学習方略」,さらには「英語使用観」を変容させる.以上,1)〜4)より,ICTを利用した第二言語学習環境における学習は,用いた「テクノロジー」の影響を受けつつ,さらに,「過去-現在の歴史的文脈」,「他者やリソースといった状況要因との関係性」の中で織りなされていることが示唆された.

自然環境問題をテーマとした総合的な学習の時間の授業プログラムを,中学校と大学の連携によって実施した.本研究では,授業の協調的なデザイン過程を検討することで,異なる組織間による授業デザインの特徴と課題を,組織論における製品開発の視点から明らかにする.複数データの質的検討の結果,授業開始当初は,大学担当者が授業プログラムを汎用的なモジュール(部分)として生徒に提供しようとしていたが,授業実践途中で当初の計画が困難に陥ったことを契機として,生徒,中学教員,大学担当者間の摺り合わせ(統合)が生じ,授業内容が再構成されたことが示された.また,その際のインターネットをはじめとする道具の役割について考察した.

This article describes a practical study of international computer communication between Waseda University and Case Western Reserve University. The study is comprised of two parts : One is the preparation of the computer communication environment and the development of a curriculum to teach intercultural communication skills by means of international computer communication. The other is the evaluation of the curriculum. Although this evaluation was done only for the students of Waseda University, a significant increase was recognized in their TOEFL score. To validate the outcome of the evaluation, we conducted 30 min interviews, asking the students about their computer communication behavior and their impressions.