Federated learning for sustainable IoT appliance load monitoring at the edge devices by Gitanjali Wadhwa, Yuvaraj Natarajan, K. R. Sri Preethaa, M. P. Gopinath, M. Shyamala Devi

“…Using our federated learning-based load monitoring model, we can minimize energy consumption while maintaining high learning performance and preserving user privacy. …”
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Addressing 6 challenges in generative AI for digital health: A scoping review. by Tara Templin, Monika W Perez, Sean Sylvia, Jeff Leek, Nasa Sinnott-Armstrong

“…Generative artificial intelligence (AI) can exhibit biases, compromise data privacy, misinterpret prompts that are adversarial attacks, and produce hallucinations. …”
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Hybrid quantum enhanced federated learning for cyber attack detection by G. Subramanian, M. Chinnadurai

“…The novel STAN used in the proposed work captures the spatio-temporal patterns in the network traffic data. …”
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FedNDA: Enhancing Federated Learning with Noisy Client Detection and Robust Aggregation by Tuan Dung Kieu, Charles Fonbonne, Trung-Kien Tran, Thi-Lan Le, Hai Vu, Huu-Thanh Nguyen, Thanh-Hai Tran

“… Federated Learning is a novel decentralized methodology that enables multiple clients to collaboratively train a global model while preserving the privacy of their local data. Although federated learning enhances data privacy, it faces challenges related to data quality and client behavior. …”
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OpenTrack: a Sensor for Monitoring the Usage of Territory by D. Strigaro, A. Rollandi, M. Cannata

“…In the Mendrisio district (Switzerland), we deployed a low-cost, AI-powered sensor to monitor pedestrian and vehicle flows in different seasons. The sensor uses camera-based image recognition to detect and classify objects in real time while preserving privacy by avoiding biometric or identity-related data capture, in full compliance with GDPR. …”
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From Capturing a Moment to New Insights: A Methodological Reflection on Reflexive Photo-Elicitation Interviews to Understand Visitor Experiences in Cultural Institutions by Tesfaye Fentaw Nigatu, Alexander Trupp, Pek Yen Teh, Elangkovan Narayanan Alagas

“…Innovative qualitative methods like photo-elicitation interviews are gaining traction for their ability to produce data through negotiation and reflexivity. Reflective Photo-Elicitation Interviews (RPIs) are commonly used in nature and community-based tourism research, but their application in cultural institutions remains limited. …”
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Effective Skin Cancer Diagnosis Through Federated Learning and Deep Convolutional Neural Networks by Mabrook S. Al-Rakhami, Salman A. AlQahtani, Abdulaziz Alawwad

“…However, achieving high accuracy results requires large volumes of data for training these DCNNs. Since medical organizations and institutions, individually, do not usually have such amounts of information available, and due to the current regulations regarding intellectual property and privacy of medical patient data, it is difficult to share data in a direct way. …”
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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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Collection and sharing of health information in mental health and related systems in Australia: perspectives of people who access mental health services by Anne Honey, Nicola Hancock, Helen Glover, Justin Newton Scanlan, Yidan Cao, Andrew Povolny, Mark Orr, Grenville Rose, Sumathi Govindasamy, Lorraine Smith, Naseem Ahmadapour

“…Focused group activities were conducted in which participants were asked to discuss and create a visual map to describe their collective experiences of sharing information relating to mental health and recovery. The data were analysed using qualitative content analysis and the coding techniques of constant comparative analysis. …”
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Exploring the application of ChatGPT in ESL/EFL education and related research issues: a systematic review of empirical studies by Chung Kwan Lo, Philip Leung Ho Yu, Simin Xu, Davy Tsz Kit Ng, Morris Siu-yung Jong

“…The included studies collectively provide solid evidence regarding the affordances (e.g., increased learning opportunities, personalised learning, and teacher support) and potential drawbacks (e.g., incorrect information, privacy leakage, and academic dishonesty) of ChatGPT use in ESL/EFL education. …”
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Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study by Katie Ryan, Justin Hogg, Max Kasun, Jane Paik Kim

“…Participants described attitudes toward the impact of AI-mHealth on users’ health and personal data (ie, influences on health awareness and management, value for mental vs physical health use cases, and the inevitability of data sharing), influences on their trust in AI-mHealth (ie, endorsements and guidance from health professionals or health or regulatory organizations, attitudes toward technology companies, and reasonable but not necessarily explainable output), and their preferences relating to the amount and type of information that is shared by AI-mHealth apps (ie, the types of data that are collected, future uses of user data, and the accessibility of information). …”
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Advancing student outcome predictions through generative adversarial networks by Helia Farhood, Ibrahim Joudah, Amin Beheshti, Samuel Muller

“…The effectiveness of these predictive models relies on having access to sufficient and accurate data. However, privacy concerns and the lack of student consent often restrict data collection, limiting the applicability of predictive models. …”
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Telehealth for the study of palliative care communication: opportunities, methodological challenges, and recommendations by Elise C. Tarbi, Susanna L. Schuler, Natalie Ambrose, Rebecca N. Hutchinson, Maija Reblin, Katharine L. Cheung

“…Conclusions Overall, our approach demonstrates possibilities for the use of telehealth to study palliative care communication and provides a “how-to” example for unique telehealth considerations from data collection through analysis. …”
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Generative AI as Third Agent: Large Language Models and the Transformation of the Clinician-Patient Relationship by Hugo de O Campos, Daniel Wolfe, Hongzhou Luan, Ida Sim

“…While affirming LLMs as a tool enabling the rise of the “AI patient,” we also explore concerns surrounding data privacy, algorithmic bias, moral injury, and the erosion of human connection. …”
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SEF: A Secure, Efficient, and Flexible Range Query Scheme in Two-Tiered Sensor Networks by Jiajun Bu, Mingjian Yin, Daojing He, Feng Xia, Chun Chen

“…To preserve authenticity and integrity of query results, we propose a novel data structure called Authenticity & Integrity tree. …”
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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care by Diala Haykal

“…However, this manuscript also addresses significant challenges that practitioners face, such as technical constraints, data privacy concerns, algorithmic biases, and financial barriers, which impact the accessibility and efficacy of AI across diverse patient populations. …”
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Cloud Resilience: A Comprehensive Review of Infrastructure-as-a-Service Security Issues by Chopde Nitin, Raut Atul, Chaudhari Shrikant, Shelokar Yogesh, Yawale Pratik

“…The research paper examines IaaS security challenges, including shared responsibility models, data privacy, identity management, and multi-tenancy implications. …”
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Current limitations in technology-based cognitive assessment for severe mental illnesses: a focus on feasibility, reliability, and ecological validity by Edoardo Caporusso, Antonio Melillo, Andrea Perrottelli, Luigi Giuliani, Francesco Flavio Marzocchi, Pasquale Pezzella, Giulia Maria Giordano

“…EMA may capture real-world functioning by increasing the number of evaluations throughout the day, but its use might be hindered by high participant burden and missing data. …”
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Description and utilization of the United States department of defense serum repository: a review of published studies, 1985-2012. by Christopher L Perdue, Angelia A Eick Cost, Mark V Rubertone, Luther E Lindler, Sharon L Ludwig

“…The Armed Forces Health Surveillance Center (AFHSC) information systems and open (online) sites were used as data sources. Through 2012, the repository contained 54,542,658 serum specimens, of which 228,610 (0.42%) have been accessed for any purpose. …”
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Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0 by Emilia Mikołajewska, Dariusz Mikołajewski, Tadeusz Mikołajczyk, Tomasz Paczkowski

“…They create synthetic datasets that improve training quality while addressing data scarcity and data imbalance. The aim of this paper was to present the current state of the art and perspectives for using AI-based generative DTs for fault diagnosis for predictive maintenance in Industry 4.0/5.0. …”
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