Realizing the potential of Internet of Things (IoT) in Industrial applications by Bharat Rathi, S. Thapaswi, Meghana Kambhampati, Vineet Jain, P. Akshay, Trilok Nath Pandey, Sunil Kumar Pradhan

“…However, challenges like data privacy, interoperability, and scalability remain critical barriers to widespread adoption. …”
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Blockchain Applications in the Military Domain: A Systematic Review by Nikos Kostopoulos, Yannis C. Stamatiou, Constantinos Halkiopoulos, Hera Antonopoulou

“…It addresses many problems related to data security, privacy, communication, and supply chain management. …”
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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management by David Pérez-Jorge, Miriam Catalina González-Afonso, Anthea Gara Santos-Álvarez, Zeus Plasencia-Carballo, Carmen de los Ángeles Perdomo-López

“…In today’s digitalized educational landscape, the intelligent use of information is essential for personalizing learning, improving assessment accuracy, and supporting data-driven pedagogical decisions. …”
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Metaheuristic-Based Cepstral Sensing Technique for Prolonging Network Lifetime and Mitigating Primary User Emulation Attacks in Cognitive Radio Sensor Network by V. Abilasha, A. Karthikeyan

“…Extensive simulations are used to analyze the proposed algorithm, incorporating important performance parameters including error probability, energy efficiency, residual energy, data gathering efficiency, network longevity, and throughput. …”
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Industry 4.0 in commercial airlines: a bibliometric analysis by Nicholas Omido, Rose Luke, Joash Mageto, Thomas Ombati, Thomas Ombati

“…Commercial airlines face numerous challenges related to operational inefficiencies, poor maintenance practices, overcrowding of airports, supply chain complexity, lack of seamless customer experience, safety issues, data privacy and security issues, increasing fuel prices, and sustainability issues; however, Industry 4.0 technologies are widely regarded as a transformative solution, offering advanced tools and methodologies to address these challenges effectively. …”
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FedDrip: Federated Learning With Diffusion-Generated Synthetic Image by Karin Huangsuwan, Timothy Liu, Simon See, Aik Beng Ng, Peerapon Vateekul

“…In the realm of machine learning in healthcare, federated learning (FL) is often recognized as a practical solution for addressing issues related to data privacy and data distribution. However, many real-world datasets are not identically and independently distributed (non-IID). …”
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Synthetic Patient–Physician Conversations Simulated by Large Language Models: A Multi-Dimensional Evaluation by Syed Ali Haider, Srinivasagam Prabha, Cesar Abraham Gomez-Cabello, Sahar Borna, Ariana Genovese, Maissa Trabilsy, Bernardo G. Collaco, Nadia G. Wood, Sanjay Bagaria, Cui Tao, Antonio Jorge Forte

“…Background: Data accessibility remains a significant barrier in healthcare AI due to privacy constraints and logistical challenges. …”
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AI optimization algorithms enhance higher education management and personalized teaching through empirical analysis by XiWen Xu

“…The research also identifies challenges and limitations, including data privacy issues, algorithmic bias, and the need for human-AI interaction. …”
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Accessible IoT Dashboard Design with AI-Enhanced Descriptions for Visually Impaired Users by George Alex Stelea, Livia Sangeorzan, Nicoleta Enache-David

“…The proliferation of the Internet of Things (IoT) has led to an abundance of data streams and real-time dashboards in domains such as smart cities, healthcare, manufacturing, and agriculture. …”
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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…Furthermore, this study discusses the practical applications of these techniques and reviews commonly used datasets that support AML research. Looking ahead, the advancement of AML technologies in blockchain systems necessitates progress in several critical areas: the construction of AML datasets capable of addressing data imbalance and annotation uncertainty, development of trusted AML algorithms, design of detection mechanisms for covert financial activities, and formulation of privacy-preserving yet regulation-compliant AML solutions. …”
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"I don't see a reason why we should be hidden from view": Views of a convenience sample of people living with HIV on sharing HIV status data in routinely collected health and care... by Elizabeth Ford, Katie Goddard, Michael Smith, Jaime Vera

“…The overarching theme was around trust, both the loss of trust experienced by participants due to previous negative or discriminatory experiences, and the need to slowly build trust in data-sharing initiatives. Further themes showed that participants were supportive of data being used for research and health care improvements, but needed a guarantee that their privacy would be protected. …”
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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

“…Considering the aforementioned, this study suggests an advanced intrusion detection technology (AIDT) to guarantee safe data exchange amongst IoMT devices. The model uses a probabilistic neural network (PNN) to classify whether intrusions are present or not, and particle swarm optimization (PSO) for feature extraction. …”
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Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the... by Dave Klein, Aisha Montgomery, Mark Begale, Scott Sutherland, Sherilyn Sawyer, Jacob L McCauley, Letheshia Husbands, Deepti Joshi, Alan Ashbeck, Marcy Palmer, Praduman Jain

“…Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. …”
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Artificial Intelligence in Healthcare: Innovation and Impact in Medical Practice by Amelia-Maria ISAC, Corina VERNIC

“…Furthermore, federated learning and domain adaptation techniques may help address data privacy concerns and improve model robustness across diverse populations. …”
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Employing combined spatial and frequency domain image features for machine learning-based malware detection by Abul Bashar

“…The ubiquitous adoption of Android devices has unfortunately brought a surge in malware threats, compromising user data, privacy concerns, and financial and device integrity, to name a few. …”
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Deep convolutional neural network based archimedes optimization algorithm for heart disease prediction based on secured IoT enabled health care monitoring system by Sureshkumar S, Santhosh Babu A. V, Joseph James S, Maranco M

“…The existing studies in healthcare IoT met a few shortcomings in terms of privacy, security, higher data dimensionality, higher cost, larger execution time, and so on. …”
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A Distributed Machine Learning-Based Scheme for Real-Time Highway Traffic Flow Prediction in Internet of Vehicles by Hani Alnami, Imad Mahgoub, Hamzah Al-Najada, Easa Alalwany

“…Centralized machine learning methods face a number of challenges due to the sheer volume of traffic data that needs to be processed in real-time. Thus, it is not scalable and lacks fault tolerance and data privacy. …”
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NLP-based removal of personally identifiable information from Hungarian electronic health records by András Berzi, Ervin Berényi, Zita Képes, Barnabás Antal, Ábrahám Gergely Varga, Miklós Emri

“…IntroductionElectronic health records (EHR) in text format serve as crucial resources for data-driven medical research. To safeguard patient confidentiality, under the General Data Protection Regulation (GDPR), strict measures are required to ensure personal data is anonymized or pseudonymized to protect individual privacy. …”
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Enhancing Autism Spectrum Disorder Classification with Lightweight Quantized CNNs and Federated Learning on ABIDE-1 Dataset by Simran Gupta, Md. Rahad Islam Bhuiyan, Sadia Sultana Chowa, Sidratul Montaha, Rashik Rahman, Sk. Tanzir Mehedi, Ziaur Rahman

“…This study aims to improve ASD classification using advanced deep learning techniques applied to neuroimaging data. …”
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A quantum-resilient lattice-based security framework for internet of medical things in healthcare systems by Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda, Badiea Abdulkarem Mohammed, Gharbi Alshammari, Reem alrashdi, Yasser A. Alkhabra, Ibrahim Alreshidi

“…Furthermore, the solution relies on zero-knowledge proofs, homomorphic encryption as well and attribute-based access control to guarantee strong security and privacy. Using the AVISPA tool, the framework is formally verified, showing its resistance against classical and quantum adversaries. …”
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