Qun Jin

Waseda University, School of Human Sciences, Faculty Member

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Lisa Elsinger

University of Wisconsin-Madison

Élisabeth Roudinesco

École Normale Supérieure

Jesus Tramullas

University of Zaragoza

Samuel LÉZÉ

École Normale Supérieure de Lyon

Francesca Zantedeschi

University of Amsterdam

Taghreed Alrehaili

Taibah University, Madinah, Saudi Arabia

Antoni Verger

Universitat Autònoma de Barcelona

Salmiah Amin

Asia Pacific Institute of Information Technology (Malaysia)

Dr Abdulrahman M Al-Zahrani

University of Jeddah

Ana Cecília Rocha Veiga

UFMG - The Federal University of Minas Gerais

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Papers by Qun Jin

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

With the popularity of mobile Internet, smart phones and location-based services, Mobile Social N... more 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.

Information sharing across diverse media platforms with reconfigurable user grouping

Special issue on technology-enhanced social learning

International Journal of Distance Education Technologies, 2013

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Vote Parallel SVM: An Extension of Parallel Support Vector Machine

Support Vector Machine (SVM) is a set of machine learning algorithms, which has been widely used ... more Support Vector Machine (SVM) is a set of machine learning algorithms, which has been widely used in diverse domains. With the increasing size of datasets, the traditional SVM training algorithms for large-scale datasets become infeasible. Mathematical optimization and cascade parallelism are both popular strategies for accelerating SVM training. In these parallel methods, the use of appropriate parallel framework to reduce SVM training time has become a priority issue and a research focus. In this paper, we investigate and overview mathematical optimization algorithms and parallel technologies of SVM, and summarize parallel SVM solutions and application problems under different frameworks. We propose a Vote Parallel SVM to reduce the training time. Finally, we show experimental results comparing with baseline methods.

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

Springer eBooks, 2015

Recently, Device to Device D2D based mobile social networking in proximity MSNP has witnessed gre... more 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.

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

Future Generation Computer Systems, Mar 1, 2019

h i g h l i g h t s • Proposing an improved SSO algorithm based on gene selection for tumors risk... more h i g h l i g h t s • Proposing an improved SSO algorithm based on gene selection for tumors risk analysis. • Utilizing IG and PCC as a hybrid filter to select distinct and discriminative genes. • A new local search strategy selects informative but less correlated genes. • The proposed method iSSO-HF&LSS outperforms its competitors in several aspects.

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rivacy Protection for LBS in Mobile Environments: Progresses, Issues and Challenges

International journal of security and its applications, Jan 31, 2015

In recent years, mainly driven by the availability of modern mobile devices with cheap integrated... more In recent years, mainly driven by the availability of modern mobile devices with cheap integrated position sensors, location based services (LBS) have become more and more popular. Prominent examples are nearest friends finding in mobile social networks and the points of interest finders such as the nearest gas stations, hospitals, or places of interests etc. However, the users' privacy information such as location is threatened, when users enjoy the convenience and effectiveness provided by such location services. Therefore, how to secure users' privacy information must be taken into consideration. Many different approaches have been proposed to protect users' identity, location and so on. This paper reviews and analyzes existing privacy protection research works from an integrated perspective, gives the LBS category from two views, and discusses the challenges of securing privacy information. Lastly, our suggestions for future research works are presented.

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

Lecture Notes in Computer Science, 2023

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

Lecture Notes in Computer Science, 2023

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

Big Data Research

With the surge in popularity of wearable devices, collection of personal health data has become q... more 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.

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

Agriculture

In the mountainous areas of Japan, the weeds on the slopes of terraced rice paddies still need to... more In the mountainous areas of Japan, the weeds on the slopes of terraced rice paddies still need to be cut by the elderly manually. Therefore, more attention should be given to maintain proper postures while performing mowing actions (especially the pre-cutting actions) to reduce the risk of accidents. Given that complex mowing actions can be decomposed into different sub-actions, we proposed a joint angular calculation-based body movement analysis model based on the Hilbert–Huang transform to analyze the pre-cutting actions. We found that the two most important sub-actions were fast pre-cutting and slow pre-cutting. Based on field experiments, we analyzed the pre-cutting actions of workers with different experience levels and identified the factors that affected their falling risk (stability). The results showed differences and similarities in the actions’ frequency and amplitude in the sub-actions of workers with different mowing experience, confirmed the influence of body character...

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Effectiveness, Policy, and User Acceptance of Covid-19 Contact Tracing Applications (CTA) During the Post-COVID-19 Pandemic: An Experience and Comparative Study (Preprint)

BACKGROUND Background In the post-coronavirus disease (COVID-19) pandemic era, many countries lau... more BACKGROUND Background In the post-coronavirus disease (COVID-19) pandemic era, many countries launched apps to trace contacts of COVID-19 infections. Each contact tracing application (CTA) faces a variety of issues owing to different national policies or technologies to trace contacts. OBJECTIVE Objective We aimed to investigate all CTAs used to trace contacts in various countries worldwide, including the technology used by each CTA, the availability of knowledge information from official websites, the interoperability of the CTAs in various countries, the infection detection rate and policies of the specific country, and to summarize the current problems of the application based on the information collected. METHODS Method We investigated CTAs launched in all countries through Google, Google Scholar, and PUBMED. After eliminating CTAs that did not meet the screening criteria, we experimented with all applications that could be installed and complemented with information about appli...

Experiment Design and Analysis of Cross-Cultural Variation in Color Preferences Using Eye-Tracking

Lecture Notes in Electrical Engineering, 2019

With the development of eye-tracking technology, existing studies verified the effect of culture ... more With the development of eye-tracking technology, existing studies verified the effect of culture on eye movements. However, the detail of how the different cultures, especially the different Asian cultures affect people’s color preferences about products by visual attention remains in black box. In this paper, we focus on the difference between Chinese and Japanese who have similar but different cultures and try to identify their difference in visual attention about color preferences when selecting goods by using eye-tracking. The finding proves that people with different Asians cultures have different viewing patterns when faced to select goods with different colors. The results also indicate that culture as a factor does affect to ones’ evaluation of products. The results can provide guidelines for products design or visual marketing management.

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

IEEE Access, 2020

The prebraking-related actions typically studied are the main maneuvers carried out to avoid coll... more The prebraking-related actions typically studied are the main maneuvers carried out to avoid collision. Especially for those braking actions taken when turning or parking, accidents often occur because of human errors such as the incorrect choice of pedal. However, regarding these daily braking-related driving behaviors, the effects of the driver characteristics, such as driving experience and gender, on the prebraking behaviors remain unknown. Therefore, defining prebraking behaviors as the movements of a driver's body before his or her foot touches the brake pedal, this paper identifies the details of drivers' driving behaviors while prebraking by analyzing the data collected from a wearable high-precision 23-joint motion capture device and further confirms the effects of driver experience, gender and stature on these behaviors. According to two-way analyses of variance (ANOVAs) that were performed on 100 sets of motion data collected from a set of driving experiments involving two different tasks, drivers perform similar prebraking body actions even under different braking scenarios. Moreover, the results of an interaction effects analysis confirmed the impact of drivers' experiences, gender and stature on their prebraking actions. The results of this study can serve as guidelines for future self-driving and advanced driver assistance system (ADAS) development and provide useful insights for the identification and training of new drivers. INDEX TERMS Motion measurement, motion analysis, experimental design, vehicle driving, driver characteristics, driver experience, braking behaviors analysis.

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Analyzing Eye-movements of Drivers with Different Experiences When Making a Turn

2020 16th International Conference on Mobility, Sensing and Networking (MSN), 2020

The driver’s driving experience is one of the important factors affecting his or her behaviors. P... more 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.

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

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), 2021

Due to the aging of rural population, in Japan's terraced field areas, many elderly people ha... more Due to the aging of rural population, in Japan's terraced field areas, many elderly people have to do the mowing works of paddy levees manually. However, it takes the high risk of falling when mowing on slops, and many accidents are caused by the unstable postures. The analysis of their body motion becomes necessary. Based on our previous study, the personal factors could be important on affecting the mowing behaviors. Therefore, in this paper, we focus more on the mowing workers' personal factors (such as age and physique) and try to analyze the effect on their falling risk via a high precision motion capture device. A set of experiments was conducted in September 2020, and four new mowing workers over 60 years old were invited to participate in the experiments. Their joints angles data and related personal factor data were used to analyze the factors that have the greatest influence on body stability during slop mowing. The results of stepwise regression showed that the mowing workers' age and physique have significant effects on the stability of their body motion. The results of this study can clarify the factors that prevent accidents in the fall detection systems and offer useful insights for the training of new mowing workers.

Analyzing Pre-braking Behaviors of Drivers with Varying Experience

2020 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), 2020

Many accidents are caused by drivers abruptly braking, or by their braking-related behaviors. How... more 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.

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

2016 International Conference on Advanced Cloud and Big Data (CBD), 2016

The world has become an aging society with exponentially increasing social security benefit expen... more 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.

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

2018 9th International Conference on Information Technology in Medicine and Education (ITME), 2018

This study used wearable devices and traditional Chinese medicine (TCM) diagnosis, which verifies... more 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.

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

2018 9th International Conference on Information Technology in Medicine and Education (ITME), 2018

People’ visual information when walking on stairs is regarded an important variable that may affe... more People’ visual information when walking on stairs is regarded an important variable that may affect their posture and balance in previous studies, but the detail of their eye movement remains unclear. In this study, we focus on people’s eye-movement when walking on stairs and design an experiment to examine subjects’ visual information (visual field and fixation) and possible influencing factors by using a mobile eye tracker. Based on data analysis, our results proved that the movement of going up/down stairs are significantly related to subjects’ visual field. The results also indicated that the factor of subjects’ gender affects both visual field and average number of fixation, but the factor of load-carrying situation only affects visual field. Some foundational insights of this study can be used to detect the fall risk for the elderly.

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