Context-Aware Trust and Reputation Routing Protocol for Opportunistic IoT Networks by Jagdeep Singh, Sanjay Kumar Dhurandher, Isaac Woungang, Han-Chieh Chao

“…Simulation experiments using the ONE simulator show that CATR is superior to the Epidemic protocol, the so-called beta-based trust and reputation evaluation system (denoted BTRES), and the secure and privacy-preserving structure in opportunistic networks (denoted PPHB+), achieving an improvement of 22%, 15%, and 9% in terms of average latency, number of messages dropped, and average hop count, respectively, under varying number of nodes, buffer size, time to live, and message generation interval.…”
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AI Robotics in Healthcare Between the EU Medical Device Regulation and the Artificial Intelligence Act<subtitle>Gaps and Inconsistencies in the Protection of Patients and Care Reci... by Martin Ebers

“…The growing inclusion of social robots in therapeutic situations raises a variety of unresolved legal and ethical issues, including risks to patient autonomy, human dignity and trust, the potentially life-threatening effects of inaccurate or malfunctioning technology, diminished privacy due to the reliance on enormous amounts of personal (sensitive health) data, new challenges to data security due to the cyber-physical nature of robots, and the problem of how to obtain informed consent to medical treatments based on opaque AI decision making. …”
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Federated learning-based user access strategy and energy consumption optimization in cell-free massive MIMO network by Yuanyuan YAO, Yiqiu LIU, Sai HUANG, Chunyu PAN, Xuehua LI, Xin YUAN

“…To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output (CF-mMIMO) network, a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First, users were evaluated and ranked for their channel quality and stability after channel sensing, and suitable access points were selected in sequence according to the order of the channel state information.Second, considering issues such as users' energy consumption and data security, a federal learning framework was used to enhance user's data privacy and security.Meanwhile, an alternating optimization variables algorithm based on energy consumption optimization was proposed to optimize the multi-dimensional variables, for the purpose of minimizing the total energy consumption of the system.Simulation results show that compared with the traditional user-centric in massive MIMO, the proposed access strategy can improve the average uplink reachable rate of users by 20%, and the uplink rate of users with poor channels can be double improved; in terms of energy consumption optimization, the total energy consumption can be reduced by much more than 50% after optimization.…”
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Energy Efficiency of Kernel and User Space Level VPN Solutions in AIoT Networks by ALEKSANDAR JEVREMOVIC, Zona Kostic, Ivan Chorbev, Dragan Perakovic, Andrii Shalaginov, Ivan Cvitic

“…The ability to process data locally using complex algorithms is becoming increasingly important in Internet of Things (IoT) contexts. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…However, several challenges, including the availability of relevant, labeled, high‐quality datasets, data privacy concerns, model interpretability, and algorithmic bias, must be carefully managed. …”
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AI-driven multimodal colorimetric analytics for biomedical and behavioral health diagnostics by Desta Haileselassie Hagos, Saurav Keshari Aryal, Patrick Ymele-Leki, Legand L. Burge

“…In addition, we highlight the need for robust data management systems and interpretable AI/ML models to ensure security, privacy, and reliability in biomedical and behavioral research. …”
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A distributed robust state estimation method based on alternating direction method of multipliers for integrated electricity‐heat system by Yanbo Chen, Yulong Gao, Zhe Fang, Jiaqi Li, Zhenda Hu, Yichao Zou, Jin Ma, Chunlai Li, Qinze Xiao, Zeyu Chen

“…Simulations demonstrate that the proposed method has higher estimation accuracy in both general and strongly correlated adverse data tests and also can ensure data privacy, good robustness and high estimation accuracy. …”
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Multidisciplinary Contributions and Research Trends in eHealth Scholarship (2000-2024): Bibliometric Analysis by Lana V Ivanitskaya, Dimitrios Zikos, Elina Erzikova

“…Researchers’ concerns for eHealth data security and privacy, including advanced access control and encryption methods, featured prominently in the maps, along with terminology related to health analytics. …”
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Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review by Gauri Kumari Chauhan, Patrick Vavken, Christine Jacob

“…While 20% (4/20) of the included apps had clinical integration features such as clinician dashboards, only 10% (2/20) had the potential to effectively enhance clinician workflows. Privacy policies were present in 95% (19/20) of the apps, with 75% (15/20) adhering to General Data Protection Regulation (GDPR) regulations; 1 app had no data protection policy. …”
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Examining Factors Impacting Online Survey Response Rates in Educational Research: Perceptions of Graduate Students by Amany Saleh, Krishna Bista

“…The authors used descriptive statistics (percentage, average mean) and inferential statistics (chi-square and correlations) to report the data analysis and findings. …”
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Towards AI-Powered Applications: The Development of a Personalised LLM for HRI and HCI by Khashayar Ghamati, Maryam Banitalebi Dehkordi, Abolfazl Zaraki

“…Furthermore, this study engages with the broader ethical dimensions of PLLM, critically discussing issues of generalisability and data privacy concerns in AI research. Our findings demonstrate the usability of using the PLLM in a human–robot interaction scenario in real-world settings, highlighting its applicability across diverse domains, including healthcare, education, and assistive technologies. …”
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Bibliometric analysis of digital transformation on organization design by Božić Katarina

“…Using the Bibliometrix software package in the R programming language, bibliographic data analysis was performed in order to identify the most influential authors, key topics and future research directions. …”
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Exploring the Knowledge and Utilization of Video-Based Surgical Learning Among Medical Students in a Teaching Hospital in Nigeria: A Mixed-Methods Study by Asogun Daniel, Akhaine Jesu-Oboh Precious, Sulymon A. Saka, Vivian Oghobaghase, Ojeh-Oziegbe Oseyomon, Francis Ufuah, Adomi Solomon

“…Quantitative data were analyzed using SPSS version 21 for descriptive statistics, while thematic coding was applied to qualitative data using NVivo. …”
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Mental Health Professionals’ Views on Artificial Intelligence as an Aide for Children Anticipating or Suffering the Loss of a Parent to Cancer: Helpful or Harmful? by Mary Rose Yockel, Marcelo M. Sleiman, Heather Doherty, Rachel Adams, Kimberly M. Davis, Hunter Groninger, Christina Sharkey, Matthew G. Biel, Muriel R. Statman, Kenneth P. Tercyak

“…<b>Purpose</b>: Assess mental health professionals’ attitudes regarding the timing and characteristics of therapeutic interventions for children whose parents have incurable cancer, and whether professionals would use artificial intelligence (AI) in these interventions. …”
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Exploring Older Adults’ Perspectives and Acceptance of AI-Driven Health Technologies: Qualitative Study by Arkers Kwan Ching Wong, Jessica Hiu Toon Lee, Yue Zhao, Qi Lu, Shulan Yang, Vivian Chi Ching Hui

“…This study aimed to investigate perspectives on and acceptability of the use of AI-led health technologies among older adults and the potential challenges that they face in adopting them. …”
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A Meta-Reinforcement Learning-Based Poisoning Attack Framework Against Federated Learning by Wei Zhou, Donglai Zhang, Hongjie Wang, Jinliang Li, Mingjian Jiang

“…As a distributed machine learning paradigm, federated learning enables clients to collaboratively train a global model without sharing their raw data, thus preserving data privacy while still utilizing the data. …”
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Distributed Photovoltaic Short-Term Power Prediction Based on Personalized Federated Multi-Task Learning by Wenxiang Luo, Yang Shen, Zewen Li, Fangming Deng

“…The federal learning framework is used to enhance the privacy of photovoltaic data and improve the model’s performance in a distributed environment. …”
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Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Adrianna Piszcz

“…Federated learning ensures privacy-preserving data sharing in distributed energy systems, promoting collaboration without compromising security. …”
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A personalized federated learning approach to enhance joint modeling for heterogeneous medical institutions by Hong Ye, Xiangzhou Zhang, Kang Liu, Ziyuan Liu, Weiqi Chen, Bo Liu, Eric WT Ngai, Yong Hu

“…Background Federated Learning (FL) offers a privacy-preserving solution for multi-party data collaboration in smart healthcare. …”
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Survey Influencing Factors on Prenatal Care in mothers referring to health care ‎centers in Rasht city in ‎‏2008‏ by fataneh bakhshi, nasrin mokhtari, shahin jefruodi, jila shekani, moohamad abasi, zahra atrkarruoshan

“…&lrm; Conclusion: In existence of prenatal care in health centers, almost half of women do not use these &lrm;care provided. Among barriers to utilization of care were not knowing the manner and number of &lrm;prenatal care, compliance with the women's privacy in time of providing care and providers manner &lrm;of communication in health centers. …”
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