Article
Computer Science, Hardware & Architecture
Fan Zhou, Weifeng Zhang, Yong Wang, Ting Zhong, Goce Trajcevski, Ashfaq Khokhar
Summary: Understanding the initial assignment and predicting the potential usage of an IP address can improve the efficiency of IP-based applications. However, there is a lack of research and benchmark datasets in this area. This paper collects large-scale real-world data and uses sophisticated networking tools to extract features, introducing a series of tabular information retrieval methods to learn network signals and identify IP usage scenarios.
Review
Education & Educational Research
Lehong Shi, Theodore J. Kopcha
Summary: The advancement of technologies has led to the increasing integration of mobile technologies in science education in the past decade. This study conducted a meta-analysis of 34 studies to examine the effects of users' pedagogical role on K-16 students' achievement in science when engaging in mobile learning (ML). The findings indicated that ML had a significant overall effect on science learning outcomes, and the users' pedagogical role significantly moderated the ML effects. Collaborative and student-led uses had a significant impact on student science learning, while teacher-led use did not.
BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY
(2022)
Review
Environmental Sciences
Sungjoon Kim, Donghyun Han, Jiwoo Ryu, Kihun Kim, Yun Hak Kim
Summary: Exposure to mobile phones is associated with reduced sperm motility, viability, and concentration. The decrease in sperm quality after RF-EMW exposure was not significant, even when the mobile phone usage increased. This finding was consistent across experimental in vitro and observational in vivo studies.
ENVIRONMENTAL RESEARCH
(2021)
Article
Computer Science, Information Systems
Ryan Wen Liu, Jiangtian Nie, Sahil Garg, Zehui Xiong, Yang Zhang, M. Shamim Hossain
Summary: This paper proposes a two-phase data-driven machine learning framework for vessel trajectory reconstruction, aiming to improve the quality of vessel trajectory records by identifying and restoring outliers in AIS data. Experimental results demonstrate the superiority of this framework compared to other methods, showing potential for promoting intelligent vessel traffic services in maritime IoT systems enabled by 6G.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Public, Environmental & Occupational Health
Wen-Chin Li, Peter Kearney, Jingyi Zhang, Yueh-Ling Hsu, Graham Braithwaite
Summary: Fatigue is an inevitable hazard in air traffic services but not the main cause of air traffic management occurrences. High traffic volume can increase ATCOs' cognitive task load, surpassing available attention resources and leading to occurrences. While ATCOs are affected by circadian fatigue, their human resilience drives them to maintain operational safety.
Article
Automation & Control Systems
Xiaohan Zhang, Xinghua Li, Yinbin Miao, Xizhao Luo, Yunwei Wang, Siqi Ma, Jian Weng
Summary: This article proposes a monitor-based usage control model that utilizes blockchain smart contract and software guard extensions to enable efficient data trading and full control of user identities and operations, effectively preventing data abuse and ensuring fair data exchange.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Review
Behavioral Sciences
Konstantinos Ioannidis, Charlotte Taylor, Leah Holt, Kate Brown, Christine Lochner, Naomi A. Fineberg, Ornella Corazza, Samuel R. Chamberlain, Andres Roman-Urrestarazu, Katarzyna Czabanowska
Summary: The study revealed a significant correlation between Problematic Usage of the Internet (PUI) and eating disorder and related psychopathology. These effects were not moderated by gender, PUI facet, or study quality.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Review
Health Care Sciences & Services
Carolin Sophie Alber, Lena Violetta Kraemer, Sophia Marie Rosar, Claudia Mueller-Weinitschke
Summary: This systematic review and meta-analysis found that internet-based behavioral activation (iBA) is effective in reducing depressive symptoms. It also highlighted that iBA can significantly reduce anxiety and improve quality of life and activation. These findings suggest that iBA represents a promising treatment option, especially for those who are unable to access traditional treatment.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Review
Biochemistry & Molecular Biology
Jeremy E. Solly, Roxanne W. Hook, Jon E. Grant, Samuele Cortese, Samuel R. Chamberlain
Summary: This study conducted a meta-analysis to identify significant spatial convergence in gray matter regions in individuals with Problematic Usage of the Internet (PUI), finding reductions in the medial/superior frontal gyri, the left anterior cingulate cortex/cingulate gyrus, and the left middle frontal/precentral gyri. These findings suggest replicable gray matter changes in specific brain regions related to reward processing and inhibitory control in PUI.
MOLECULAR PSYCHIATRY
(2022)
Article
Information Science & Library Science
Shaohui Wu, Yong Tan, Yubo Chen, Yitian (Sky) Liang
Summary: Mobile application use has become essential in people's daily lives. Understanding cross-app uses and the impact of contexts is crucial. This paper develops a hidden Markov model to study cross-app uses and examines the influence of contextual factors.
INFORMATION SYSTEMS RESEARCH
(2022)
Article
Environmental Sciences
Eun-Young Park
Summary: The COVID-19 pandemic has led to changes in the internet usage of people, including those with disabilities. This study analyzed data from the 2020 Digital Divide Survey and found that the non-disabled population showed a significantly higher increase in internet usage compared to people with disabilities. The specific changes in service usage, experience, and usefulness varied depending on the type of disability. The study suggests that digital services need to be developed flexibly to meet the unique needs of people with different types of disabilities.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Review
Computer Science, Information Systems
Vanice Canuto Cunha, Arturo Zavala Zavala, Damien Magoni, Pedro R. M. Inacio, Mario M. Freire
Summary: This article discusses the application of statistical methods in Internet traffic classification. With the prevalence of traffic encryption and multi-layer data encapsulation, some classic classification methods have become ineffective, while machine learning strategies have shown potential in traffic classification. However, some methods have high computational resource consumption, limiting their use in real-time or large-scale classification. Therefore, statistical methods have been applied to classify real-time or large-scale traffic by identifying traffic types through statistical properties.
Article
Computer Science, Information Systems
Tong Li, Tong Xia, Huandong Wang, Zhen Tu, Sasu Tarkoma, Zhu Han, Pan Hui
Summary: This article provides a comprehensive review of recent research on smartphone app usage analysis. It covers data collection methods, as well as studies in the app domain, user domain, and smartphone domain. The research reveals the connections between users, apps, and smartphones through the collection and analysis of app usage traces, and highlights challenges and future directions in this field.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Article
Engineering, Electrical & Electronic
Shen Fang, Xianbing Pan, Shiming Xiang, Chunhong Pan
Summary: The study introduces a meta-learning based multi-source spatio-temporal network model for traffic flow prediction. The model captures neighboring temporal dependencies with an encoder, extracts periodic features with a decoder, and integrates multi-source external data through fusion modules, addressing the issues faced in extracting complicated intrinsic and extrinsic features in existing methods.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Automation & Control Systems
Liangyu Tay, Joanne Mun-Yee Lim, Shiuan-Ni Liang, Chua Kah Keong, Yong Haur Tay
Summary: This paper proposes a novel method to predict traffic volume for the entire network by estimating 10% of the ground truth data. Spatial-temporal weightage is assigned to each road before performing predictions on connecting roads. Experimental results show that the weighting approach improves the accuracy of the model and significantly reduces the average percentage error compared to existing methods.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
