A Review of the Authentication Techniques for Internet of Things Devices in Smart Cities: Opportunities, Challenges, and Future Directions by Ashwag Alotaibi, Huda Aldawghan, Ahmed Aljughaiman

“…This study aims to identify gaps and propose future research directions to develop robust authentication frameworks that protect user privacy and data integrity.…”
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A Bibliometric Analysis on Federated Learning by Ersin Namlı, Yusuf Sait Türkan, Mesut Ulu, Ömer Algorabi

“…With the rapid advancement of technology and growing concerns about data privacy, federated learning (FL) has attracted considerable attention from the scientific community. …”
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Future perspectives on internet of vehicles resource management: digital twin-enabled edge computing frameworks by Jihong Xie, Gui Wu, Xiang Zhou, Shanshan Deng

“…Existing approaches are then discussed and compared using clustering, matching, and offloading approaches. …”
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COVID-19 and the implications of social and hospital isolation for older adults by Renata Bezerra de Holanda Bessa, Karla Patrícia Martins Ferreira, Cynthia de Freitas Melo, Letícia Keroly Bezerra Alexandrino, Bianca de Sousa Nogueira

“…Method This is an exploratory, descriptive, and qualitative study conducted with 16 hospitalized older adults, who answered a sociodemographic questionnaire and a guiding question. Data were analyzed through textual analysis using the Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires (IRaMuTeQ) software. …”
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Dispute Resolution in Islamic Economic Transactions: The Role and Function of Sharia Arbitration by Gunawan Widjaja

“…This study examines the function and role of Sharia-based arbitration, focusing on its alignment with the values of justice, efficiency, and confidentiality within Islamic law. Using a literature-based methodology, the research analyzes secondary data from legal sources and previous studies on Sharia arbitration in Indonesia, particularly the practices of the Sharia Arbitration Body (BASYARNAS-MUI). …”
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A Comprehensive Survey of Deep Learning Approaches in Image Processing by Maria Trigka, Elias Dritsas

“…Metrics used for rigorous model evaluation are also discussed, underscoring the importance of performance assessment in varied application contexts. …”
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The Role of Artificial Intelligence in Personalized Medicine: A Computer Science Perspective by Raul Mihai RADULESCU

“… This abstract investigates the role of AI in personalized medicine using a computer science lens that connects the underlying theories with their actual applications. …”
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Artificial Intelligence in Religious Education: Ethical, Pedagogical, and Theological Perspectives by Christos Papakostas

“…Amid increasing digital transformation in education, theological institutions are exploring AI tools for teaching, assessment, and pastoral engagement. Using a critical literature review and analysis of institutional case studies, the paper examines the historical development of AI in education, current applications in general and theological contexts, and the ethical challenges it introduces, especially regarding decision making, data privacy, and bias as well as didactically grounded opportunities such as AI-mediated dialogic simulations. …”
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Towards responsible artificial intelligence in education: a systematic review on identifying and mitigating ethical risks by Haotian Zhu, Yao Sun, Junfeng Yang

“…In the technology dimension, risks include privacy invasion, data leakage, algorithmic bias, the black box algorithm, and algorithmic error. …”
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Artificial intelligence and machine learning in production efficiency enhancement and sustainable development: a comprehensive bibliometric review by Aristidis Bitzenis, Nikos Koutsoupias, Marios Nosios

“…Despite the promising advancements, the review identifies gaps in ethical considerations, especially in data privacy and labor market implications, and suggests avenues for future research, including the implementation of AI and ML in developing economies and Small and Medium Enterprises (SMEs).…”
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Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

“…This learning approach is particularly useful but challenging due to the limited availability of labeled video data in practice. …”
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Knowledge and Views of Patients With Cardiovascular Disease Toward Pharmacogenomics in The United Arab Emirates by Maram O. Abbas, Azhar T. Rahma, Iffat Elbarazi, Bassam R. Ali, George P. Patrinos, Farah Nagy, Alya Osman, Reem K. Alneyadi, Anwar S. Alshamsi, Mohamed Alraqabani, Zeina Al‐Mahayri, Fatma Al‐Maskari

“…Participants were invited via phone calls or in‐person contact at clinics. Data analysis was conducted using SPSS V.29, incorporating descriptive statistics and multivariable logistic regression. …”
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GPS tracking methods for spatiotemporal air pollution exposure assessment: comparison and challenges in study implementation by Kalliopi Kyriakou, Benjamin Flückiger, Danielle Vienneau, Nicole Probst-Hensch, Ayoung Jeong, Medea Imboden, Aletta Karsies, Oliver Schmitz, Derek Karssenberg, Roel Vermeulen, Gerard Hoek, Kees de Hoogh

“…Participants completed a baseline questionnaire, carried a GPS device (SODAQ) for 2 weeks, and used a smartphone app for a time activity diary. …”
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HIV Self-Testing: A Discussion on the Benefits, Limitations, and Implications for Public Health with a Focus on Poland by Aleksandra Kozieł, Igor Domański, Aleksandra Szymczak, Tomasz Dudzik, Brygida Knysz, Bartosz Szetela

“…Results: HIVST is well-accepted, especially among key populations; it can reduce stigma and enhance privacy. The results of studies conducted in Poland indicate that heterosexuals are more inclined to use self-testing methods than traditional diagnostic procedures. …”
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Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review by Oluwadamilola Ogundiya, Thahmina Jasmine Rahman, Ioan Valnarov-Boulter, Tim Michael Young

“…The rapid evolution and use of web-based and digital techniques have been significantly transforming this field since the beginning of the new millennium. …”
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Parents’ understanding and attitudes toward the application of AI in pediatric healthcare: a cross-sectional survey study by Yan-Dan Huang, Shu-Long Zeng, Jie Lin, Zhi-Peng Mao, Qi-Liang Zhang, Gao-Zhong Feng, Qiong-Xia Ou

“…Most participants (91.1%) believed that AI cannot replace doctors in the future.ConclusionAlthough most parents were aware of the use of AI in pediatric healthcare and recognized its convenience and efficiency, they expressed concerns about accuracy, accountability, and data privacy. …”
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Receptiveness to participating in cannabis research in pregnancy: a survey study at The Ottawa Hospital [version 1; peer review: 2 approved] by Kira Bombay, Amy McGee, Christina Cantin, Kathryn M Denize, Malia SQ Murphy, Daniel J Corsi, Mark C Walker, Shi Wu Wen, Ruth Rennicks White

“…In the design of new cohort studies to evaluate the patterns and outcomes of cannabis use in pregnancy, consideration must be given to the factors influencing participation, data sharing, and contribution of biological samples. …”
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When and Why Adults Abandon Lifestyle Behavior and Mental Health Mobile Apps: Scoping Review by Patrick G Kidman, Rachel G Curtis, Amanda Watson, Carol A Maher

“…ObjectiveWe explored the abandonment of apps used for managing physical activity, diet, alcohol, smoking, and mental health in free-living conditions, examining the duration of app use before abandonment and the underlying reasons. …”
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A comprehensive analysis of model poisoning attacks in federated learning for autonomous vehicles: A benchmark study by Suzan Almutairi, Ahmed Barnawi

“…Due to the increase in data regulations amid rising privacy concerns, the machine learning (ML) community has proposed a novel distributed training paradigm called federated learning (FL). …”
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Robust hierarchical federated learning with dual-layer filtering mechanism by Chaoyi Yang, Wei Liang, Yuxiang Chen, Jiahong Xiao, Dacheng He, Tianxiong Liu, Jin Wang, Amr Tolba

“…Hierarchical federated learning (HFL) is an effective “cloud-edge-device” distributed model training framework that protects data privacy. During HFL training, poisoning attacks on local data and transmitted models can affect the accuracy of the global model. …”
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