Foreground-Driven Contrastive Learning for Unsupervised Human Keypoint Detection by Shuxian Li, Hui Luo, Zhengwei Miao, Zhixing Wang, Qiliang Bao, Jianlin Zhang

“…Recently, unsupervised human keypoint detection has become prevalent due to concerns about data privacy. Most existing methods are based on a reconstruction process that extracts appearance and pose information from transformed image pairs and spatially aligns them to obtain a reconstructed image for detection. …”
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B5G Applications and Emerging Services in Smart IoT Environments by Hani Attar, Mohammed Alghanim, Jafar Ababneh, Khosro Rezaee, Ayat Alrosan, Mohanad A. Deif

“…Furthermore, the proposed study examines the techniques employed for data transmission in B5G applications, such as Vehicle-to-Vehicle (V2V), Device-to-Device (D2D), and Machine to Machine (M2M) transmissions. …”
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Smart cities and electrical and electronic waste management: a review of challenges and opportunities by Deividson Sá Fernandes de Souza, Simone Sehnem, Patricia Guarnieri, Thyago Celso Cavalcante Nepomuceno, Fernando Henrique Taques, Lucio Camara e Silva

“…Key challenges include information security, privacy, interoperability, costs and sustainability. …”
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Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning by Won June Choi, Jin HwangBo, Quan Anh Duong, Jae-Hyeok Lee, Jin Kyu Gahm

“…However, the models typically require extensively labeled training datasets, which are costly and pose patient privacy risks. To address the issue of limited training datasets, we propose a novel few-shot learning framework for classifying multiple system atrophy parkinsonian (MSA-P) and progressive supranuclear palsy (PSP) within the APS category using fewer data items. …”
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A Multi-Criteria Decision-Making Framework for Blockchain Technology Adoption in Smart Healthcare by Deepika Gaur, Shivani Bali, Angappa Gunasekaran, Nitish Joshi, Kuldeep Chaudhary, Vikram Bali

“…Among the three blockchain platforms evaluated, the results indicate that permissioned blockchain technology is the most suitable for the healthcare sector, primarily due to its strengths in regulatory compliance, data privacy, and system integration. The study’s findings would help practitioners identify and choose the best blockchain platform, thus contributing to a transition in the healthcare industry called “Smart Healthcare 5.0”.…”
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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. …”
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Inpatient satisfaction with nursing care in a backward region: a cross-sectional study from northwestern China by Xiaoying Wang, Juxia Zhang, Limei Yang, Jiao Dai, Wenjing Shan, Jiancheng Wang

“…Objectives The aim of the study was to examine the level of patient satisfaction with nursing care and identify the factors affecting satisfaction from the inpatient’s perspective in a backward region of China.Design This was a cross-sectional study.Setting The study was conducted at a tertiary hospital located in northwest China.Participants Patients admitted to the ward for at least 48 hours were chosen to participate in the survey.Primary outcome measure The Newcastle Satisfaction with Nursing Care Scale was used. Data were collected from 219 patients.Results The overall inpatient satisfaction with nursing care was 78.15±4.74. …”
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Intrusion Detection Framework for Internet of Things with Rule Induction for Model Explanation by Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson

“…As the proliferation of Internet of Things (IoT) devices grows, challenges in security, privacy, and interoperability become increasingly significant. …”
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A Trusted Batch Authentication Mechanism Based on Tree for Power Internet of Things by Baohua ZHAO, Zhihao WANG, Liandong CHEN, Chunhui REN, Fajiang YU, Qing XU

“…The structure of unbalanced hash tree generates less verification information during device verification and protects privacy. The sparse Merkel tree multiproofs method is used to generate the verification information to implement the batch authentication of devices. …”
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A "Quıet" need ın the dısaster of the century: a qualıtatıve study on menstrual hygıene management by Ayşe Aydın, Meltem Şirin Gok, Bahar Çiftçi

“…The interviews were analyzed using content analysis, and themes and sub-themes reflecting the women's experiences were identified. …”
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Rapid Whole-Genome Sequencing in Critically Ill Infants and Children with Suspected, Undiagnosed Genetic Diseases: Evolution to a First-Tier Clinical Laboratory Test in the Era of... by Rina Kansal

“…Factors that will help to develop rWGS as a clinical test in critically ill infants and the limitations are briefly discussed, including an evaluation of the clinical utility and accessibility of genetic testing, education for parents and providers, cost-effectiveness, ethical challenges, consent issues, secondary findings, data privacy concerns, false-positive and false-negative results, challenges in variant interpretation, costs and reimbursement, the limited availability of genetic counselors, and the development of evidence-based guidelines, which would all need to be addressed to facilitate the implementation of pediatric genomic sequencing in an effective widespread manner in the era of precision medicine.…”
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The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce by Jiwang Yin, Xiaodong Qiu, Ya Wang

“…AI-personalized recommendation technology offers more accurate and diverse choices to consumers and increases click-through rates and sales on e-commerce platforms. Yet, data on consumers’ experiences of AI-personalized recommendations and their impact path on clicking intention are scarce. …”
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The Role of Evidence-Based Design in Enhancing Architectural Design Process of Healthcare Buildings: A Case Study of General Hospitals in Sulaimani City by Zhekaf Sulaiman Mustafa Hassan 1, a, *, Dr. Fouad Jalal Mahmood 2, a

“…The investigation includes correlations between participants' prioritization of hospital design aspects such as circulation, accessibility, wayfinding, visibility, and privacy and their professional background, experience, and considerations in EBD. …”
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Transformations in academic work and faculty perceptions of artificial intelligence in higher education by Jorge Buele, Leonel Llerena-Aguirre

“…Additionally, ethical debates are emerging around algorithmic transparency, data privacy, and institutional responsibility. Effective integration in higher education demands not only technical proficiency but also ethical grounding, regulatory support, and critical pedagogical development. …”
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FedHSP: A Robust Federated Learning Framework Coherently Addressing Heterogeneity, Security, and Performance Challenges by Divya G. Nair, C. V. Aswartha Narayana, K. Jaideep Reddy, Jyothisha J. Nair

“…Federated Learning (FL) is a machine learning training method that leverages local model gradients instead of accessing private data from individual clients, ensuring privacy. However, the practical implementation of FL faces significant challenges. …”
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Integrating Artificial Intelligence into Service Innovation, Business Development, and Legal Compliance: Insights from the Hainan Free Trade Port Era by Yincheng Li, Shumin Wang, Muhammad Bilawal Khaskheli

“…Hypothesis 3 state that HFTP enterprises comply with these laws while systemically assuring, in theory, and practice, the legal risks of artificial intelligence and its implications for legal regulation, which is a significant aspect of research, addressing legal risks related to data privacy, security, and algorithmic bias with many strategies being proposed. …”
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Class-Hidden Client-Side Watermarking in Federated Learning by Weitong Chen, Chi Zhang, Wei Zhang, Jie Cai

“…Federated learning consists of a central aggregator and multiple clients, forming a distributed structure that effectively protects data privacy. However, since all participants can access the global model, the risk of model leakage increases, especially when unreliable participants are involved. …”
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Machine Learning for Resilient and Sustainable Cities: A Bibliometric Analysis of Smart Urban Technologies by Bin Luan, Xinqun Feng

“…A hotspot analysis revealed that research topics are increasingly diverse and dynamically evolving. Issues such as data privacy, cybersecurity, sustainable development, and intelligent transportation have gradually become focal points, reflecting the dual demand of smart city development for technological innovation and green growth. …”
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Multimodal Cancellable Biometric Template Protection and Person Verification in Transformed Domain by Devendra Reddy Rachapalli, Venkatesulu Dondeti, Hemantha Kumar Kalluri

“…Combining biometric features increases system reliability, safety, and user privacy. We used a colorization technique to generate three separate colors Quick Response (QR) codes from a user-defined Red, Green, Blue (RGB) tuple random seed, which we then combined to create a one-way cancellable template. …”
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Image-based food monitoring and dietary management for patients living with diabetes: a scoping review of calorie counting applications by Asal Rouhafzay, Asal Rouhafzay, Ghazal Rouhafzay, Jalila Jbilou, Jalila Jbilou

“…However, challenges such as standardization, validation across diverse populations, and data privacy concerns need to be addressed. This review focuses on the role of computer science in dietary intake estimation, specifically food segmentation, classification, and volume estimation for calorie calculation. …”
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