Energy-aware federated learning for secure edge computing in 5G-enabled IoT networks by Milad Rahmati

“…We evaluate the EAFL framework using benchmark IoT datasets and simulated 5G edge environments, demonstrating a 35.4% reduction in energy consumption while maintaining a high model accuracy of 91.8%. …”
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A framework reforming personalized Internet of Things by federated meta-learning by Linlin You, Zihan Guo, Chau Yuen, Calvin Yu-Chian Chen, Yan Zhang, H. Vincent Poor

“…However, with the introduction of laws and regulations about data security and privacy protection, centralized solutions, which require data to be collected and processed directly on a central server, become impractical for personalized Internet of Things to train Artificial Intelligence models for a variety of domain-specific scenarios. …”
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iScene: An interpretable framework with hierarchical edge services for scene risk identification in 6G internet of vehicles by Wuchang Zhong, Siming Wang, Rong Yu

“…However, the performance of existing risk identification approaches is heavily limited by the imbalanced historical data and the poor model interpretability. Meanwhile, the large processing delay and the potential privacy leakage threat also restrict their application. …”
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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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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…However, challenges related to performance and data privacy often arise when using medical data from patients and healthcare institutions. …”
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Resilience in the Internet of Medical Things: A Review and Case Study by Vikas Tomer, Sachin Sharma, Mark Davis

“…Issues such as latency, bandwidth constraints, and concerns regarding security and privacy are critical in IoMT owing to the sensitive nature of patient data, including patient identity and health status. …”
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Encouraging gender-inclusive acceptance of multipurpose national-identity smart cards. by Yuen Yee Yen, P H P Yeow, Loo Wee Hong

“…The data was collected through five hundred questionnaires from Malaysia (the MNIS pioneer) and analyzed using structural equation modeling.…”
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A systematic review of consumers’ and healthcare professionals’ trust in digital healthcare by Soraia de Camargo Catapan, Hannah Sazon, Sophie Zheng, Victor Gallegos-Rejas, Roshni Mendis, Pedro H. R. Santiago, Jaimon T. Kelly

“…Trust in digital healthcare is complex and, from a consumers’ perspective, can influence digital healthcare use, adoption, acceptance, and usefulness. Consumers’ trust can be affected by the degree of human interaction in automated interventions, perceived risks, privacy concerns, data accuracy, digital literacy, quality of the digital healthcare intervention, satisfaction, education, and income. …”
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FedArtML: A Tool to Facilitate the Generation of Non-IID Datasets in a Controlled Way to Support Federated Learning Research by Daniel Mauricio Jimenez Gutierrez, Aris Anagnostopoulos, Ioannis Chatzigiannakis, Andrea Vitaletti

“…We use the 2) Jensen-Shannon and Hellinger distances for quantifying the degree of IID data. …”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…This study explores the factors influencing college students’ acceptance and resistance toward generative AI technologies by integrating three theoretical frameworks: the Technology Acceptance Model (TAM), Protection Motivation Theory (PMT), and Social Exchange Theory (SET). Using data from 407 respondents collected through a structured survey, the study employed Structural Equation Modeling (SEM) to examine how functional factors (perceived usefulness, ease of use, and reliability), risk factors (privacy concerns, data security, and ethical issues), and sociolegal factors (trust in governance and regulatory frameworks) impact user attitudes. …”
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Artificial intelligence in the tourism business: a systematic review by Alexandra Lorena López-Naranjo, Mariana Isabel Puente-Riofrio, Verónica Adriana Carrasco-Salazar, Juan Diego Erazo-Rodríguez, Pamela Alexandra Buñay-Guisñan

“…The aim of this re-search is to explore the application of AI in the tourism industry, identifying the main AI technologies used in the business, the specific areas or processes, their benefits, and challenges. …”
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The level of male involvement and associated factors in the prevention of mother-to-child transmission of HIV in Lusaka, Zambia by Sheila Mukuni Mutondo, Joseph Lupenga, Chris Mweemba, Oliver Mweemba

“…A 10—item male partner involvement scale was used in the survey, and focus group discussions with both men and women and key informants were used to collect qualitative data. …”
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Sybil Attack Detection Based on Signal Clustering in Vehicular Networks by Halit Bugra Tulay, Can Emre Koksal

“…We conduct extensive real-world experiments using vehicle-to-everything (V2X) data, gathered from dedicated short-range communications (DSRC) in vehicular networks. …”
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Identifying latent mobility as a service preference segments among college students by Willy Kriswardhana, Domokos Esztergár-Kiss

“…The negative precautions regarding MaaS should be decreased by respecting data privacy and providing easy-to-use MaaS applications, while the perceived safety risks should be eliminated by providing emergency features. …”
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Blockchain-Enabled Secure and Decentralized Resource Management for Open Radio Access Network Cellular Networks by Dheyaa Marjan Hussein Almuntifeky, Basim K. J. Al-shammari

“…This study proposes the use of blockchain technology for enhancing the security, privacy, and decentralized decision-making in Open RAN cellular networks. …”
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Frequency of Episiotomy and Perineal Injury in Home Births and Influencing Factors by Emel Ay, Menekşe Nazlı Aker

“…The sample consisted of 159 women. The data were collected by using the Personal Information Form and Satisfaction Scale (Visual Analog Scale-Satisfaction).Results: Participants preferred home birth for reasons such as preserving privacy, avoiding IV oxytocin use, having their spouse present during labor, and preventing episiotomy. …”
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Generating Automatically Print/Scan Textures for Morphing Attack Detection Applications by Juan E. Tapia, Maximilian Russo, Christoph Busch

“…The focus of Morphing Attack Detection (MAD) is to identify unauthorised attempts to use a legitimate identity. One common scenario involves creating altered images and using them in passport applications. …”
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Design of mTCN framework for disaster prediction a fusion of massive machine type communications and temporal convolutional networks by M. Umadevi, J. Arun Kumar, S. Vishnu Priyan, C. Vivek

“…The objective is to develop a scalable, secure, and efficient system for real-time disaster prediction using IoT data streams. Lightweight edge-based TCNs enable localized anomaly detection, while federated learning ensures privacy-preserving collaborative model training across edge devices. …”
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Cybercrime Regulation through Laws and Strategies: a Glimpse into the Indian Experience by Annappa Nagarathna

“…This Act underwent amendment in 2008 to accommodate provisions essential to regulate cybercrimes as well as protect data and privacy on cyber space. In addition to the law, other strategies were designed and adopted to better regulate cyber offences including announcing cyber security policies, constituting institutions to take care of certain concerns including those relating to critical infrastructure information, etc. …”
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A scaling law to model the effectiveness of identification techniques by Luc Rocher, Julien M. Hendrickx, Yves-Alexandre de Montjoye

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