State of the Art Review of Wearable Devices for Respiratory Monitoring by Zhiyu Jia, Hannah Huth, Wen Qi Teoh, Sheng Xu, Bradford Wood, Zion Tsz Ho Tse

“…This review identifies major challenges, including power efficiency, ergonomic design, data accuracy, and data privacy concerns. It also introduces innovative solutions proposed in recent research. …”
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FFL-IDS: A Fog-Enabled Federated Learning-Based Intrusion Detection System to Counter Jamming and Spoofing Attacks for the Industrial Internet of Things by Tayyab Rehman, Noshina Tariq, Farrukh Aslam Khan, Shafqat Ur Rehman

“…This framework allows multiple parties in IIoT networks to train deep learning models with data privacy preserved and low-latency detection ensured using fog computing. …”
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A Comparative Analysis of Blockchain in Enhancing the Drug Traceability in Edible Foods Using Multiple Regression Analysis by K. Suresh Kumar, Vinay Kumar Nassa, Dipesh Uike, Ashima kalra, Ajay Kumar Sahu, Vijay Anant Athavale, V. Saravanan

“…The emergence of Blockchain technology enables centralized tracking of information support in enhancing the data privacy and increasing transparency and support in eradicating the tampered food products in the supply chain system. …”
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Improving Telemedicine through IoT and Cloud Computing: Opportunities and Challenges by M. Sunil Kumar, D. Ganesh

“…The study also discusses the benefits of cloud-based telemedicine platforms, including scalability, accessibility, cost-effectiveness, and the implementation of security measures to address data privacy concerns. The combination of IoT and cloud methods indicates various advantages, such as improving patient outcomes, expanding healthcare accessibility, and enabling data-driven decision-making for medical professionals. …”
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Global Education Development Plan to Build Sustainable Education Based on Artificial Intelligence by Siti Marisa, Gunawan Gunawan, Evi Susilawati

“…Ethical aspects, student data privacy, and fairness in access and use of AI technology should be key concerns in designing sustainable global education development. …”
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Utilizing Artificial neural networks (ANN) to regulate Smart cities for sustainable Urban Development and Safeguarding Citizen rights by Zhen Kuang, Junyu Su, Ahmad Latifian, Sanli Eshraghi, Alireza Ghafari

“…However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced. …”
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Evaluating Machine Unlearning: Applications, Approaches, and Accuracy by Zulfiqar Ali, Asif Muhammad, Rubina Adnan, Tamim Alkhalifah, Sheraz Aslam

“…In many cases, ML models may memorize sensitive or personal data, raising concerns about data privacy and security. Machine unlearning (MU) techniques offer a solution to these concerns by selectively removing sensitive data from trained models without significantly compromising their performance. …”
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Public awareness, attitudes, and motivation toward biobanks: a survey of China by Mingtao Huang, Lanyi Yu, Xiaonan Wang, Kun Li, Jichao Wang, Xinrui Cheng, Xiaomei Zhai

“…The respondents raised concerns about the commercialization of biobanks (56.66%) and data privacy (55.84%). Notably, only 37.01% of the respondents were concerned about the risk of discrimination in biobanks, where this was lower compared with the results for populations in Western countries. …”
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The Impact of Digitalization in Inheritance Law by Akmaljon A. Akramov, Nilufar Kh. Rakhmonkulova, Odilbek T. Khazratkulov, Elnora E. Inamdjanova, Diyora I. Imamalieva, Shakhzoda R. Tuychieva, Sayidkomil B. Ibodullaev, Azamat E. Ergashev, Shokhrukh Khamidov, Nodira R. Rustamova

“…The study proposes a comprehensive digital trust framework encompassing ownership rights, trustee roles, jurisdictional considerations, data privacy, and liability limitations. Recommendations include new regulations for digital executors, formalized digital asset estate planning, and mechanisms to protect ownership interest’s post-mortem. …”
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System-Level Digital Twin Modeling for Underwater Wireless IoT Networks by Lei Wang, Lei Yan, Xinbin Li, Song Han

“…Employing FL for DT modeling (FLDTM) is particularly valuable, as it allows for the enhancement of model accuracy without explicitly sharing local data, thereby preserving data privacy under challenging aquatic conditions. In this article, we propose a secure and efficient multi-server FL framework tailored for underwater wireless systems. …”
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Cross-Chain Identity Authentication Method Based on Relay Chain by Qipeng Huang, Minsheng Tan, Wenlong Tian

“…Nonetheless, it continues to encounter numerous challenges regarding data privacy, security, and issues of heterogeneity. …”
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Leveraging LLMs and wearables to provide personalized recommendations for enhancing student well-being and academic performance through a proof of concept by Arfan Ahmed, Sarah Aziz, Alaa Abd-alrazaq, Rawan AlSaad, Javaid Sheikh

“…As this technology evolves, ensuring ethical considerations and data privacy remains essential.…”
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Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine by Kuo Zhang, Xiangbin Meng, Xiangyu Yan, Jiaming Ji, Jingqian Liu, Hua Xu, Heng Zhang, Da Liu, Jingjia Wang, Xuliang Wang, Jun Gao, Yuan-geng-shuo Wang, Chunli Shao, Wenyao Wang, Jiarong Li, Ming-Qi Zheng, Yaodong Yang, Yi-Da Tang

“…Challenges include ensuring their empirical reliability, addressing ethical and societal implications, especially data privacy, and mitigating biases while maintaining privacy and accountability. …”
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Race to the Moon or the Bottom? Applications, Performance, and Ethical Considerations of Artificial Intelligence in Prosthodontics and Implant Dentistry by Amal Alfaraj, Toshiki Nagai, Hawra AlQallaf, Wei-Shao Lin

“…Regarding ethical issues, five studies identified concerns such as data privacy, system bias, and the potential replacement of human roles by AI. …”
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A review of quantum communication and information networks with advanced cryptographic applications using machine learning, deep learning techniques by R. Ramya, P. Kumar, D. Dhanasekaran, R. Satheesh Kumar, S. Amithesh Sharavan

“…Quantum-secured networks enhance urban security, smart management, and infrastructure protection by providing data privacy and facilitating secure data transmission, thereby facilitating robust infrastructure and technological development.…”
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Data Overlay Mesh in Distributed Clouds Allowing Collaborative Applications by Milos Simic, Jovana Dedeic, Milan Stojkov, Ivan Prokic

“…This architectural decision does not come without additional costs when managing isolation and data privacy between tenants. That is a known challenge in cloud computing that translates to systems closer to the users, namely edge computing and micro clouds. …”
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<i>VFL-Cafe</i>: Communication-Efficient Vertical Federated Learning via Dynamic Caching and Feature Selection by Jiahui Zhou, Han Liang, Tian Wu, Xiaoxi Zhang, Yu Jiang, Chee Wei Tan

“…Vertical Federated Learning (VFL) is a promising category of Federated Learning that enables collaborative model training among distributed parties with data privacy protection. Due to its unique training architecture, a key challenge of VFL is high communication cost due to transmitting intermediate results between the Active Party and Passive Parties. …”
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Harnessing AI for sustainable higher education: ethical considerations, operational efficiency, and future directions by Sunawar Khan, Tehseen Mazhar, Tariq Shahzad, Muhammad Amir Khan, Ateeq Ur Rehman, Mamoon M. Saeed, Habib Hamam

“…The document discusses AI ethics, including data privacy, algorithmic prejudice, and the digital divide. …”
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REVOLUTIONIZING LUXURY: THE ROLE OF AI AND MACHINE LEARNING IN ENHANCING MARKETING STRATEGIES WITHIN THE TOURISM AND HOSPITALITY LUXURY SECTORS by Maria Nascimento CUNHA, Manuel PEREIRA, António CARDOSO, Jorge FIGUEIREDO, Isabel OLIVEIRA

“…While the industry benefits from technological advancements, there are ongoing challenges such as concerns over data privacy and the need for constant updates to algorithms to keep pace with evolving market conditions.…”
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A reliable and privacy-preserved federated learning framework for real-time smoking prediction in healthcare by Siddhesh Fuladi, D. Ruby, N. Manikandan, Animesh Verma, M. K. Nallakaruppan, Shitharth Selvarajan, Shitharth Selvarajan, Shitharth Selvarajan, Preeti Meena, V. P. Meena, Ibrahim A. Hameed

“…This research also discusses the benefits of federated learning, including efficient time management, parallel processing, secure model updates, and enhanced data privacy, while addressing limitations such as computational overhead. …”
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