Enhancing AES image encryption with a three-dimensional hyperchaotic system for increased security and efficiency. by Mingyi Huo, Yanpei Zheng, Jun Huang

“…Although the Advanced Encryption Standard (AES), a widely used symmetric encryption method, performs excellently in data communication and network security, its efficiency and security face significant challenges when directly applied to image encryption due to the inherent complexity of image data. …”
Get full text

Optimising TinyML with quantization and distillation of transformer and mamba models for indoor localisation on edge devices by Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, Ryan McConville

“…The application of these TinyML models in healthcare has the potential to revolutionize patient monitoring by providing accurate, real-time location data while minimising power consumption, increasing data privacy, improving latency and reducing infrastructure costs.…”
Get full text

PENGAJARAN MISI BAGI JEMAAT KRISTEN DI ERA DIGITAL by Sandy Ariawan

“…The main challenges identified include the limitations of personal interactions that often lack depth in online contexts, as well as security and privacy issues relating to the protection of congregational data and the authenticity of information. …”
Get full text

Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions by Aasim Ayaz Wani

“…Yet widely used methods like principal component analysis, t-distributed stochastic neighbor embedding, uniform manifold approximation and projection, and autoencoders are often applied as “black boxes,” neglecting interpretability, fairness, stability, and privacy. …”
Get full text

Applications of UAV Technologies in Assessment of Transportation Infrastructure Systems by Ahmad Akib Uz Zaman, Ahmed Abdelaty, Mohamed S. Yamany

“…Respondents emphasize the need for longer flight times, better automation, and advanced data tools, underscoring growing adoption and highlighting the need to overcome technical, regulatory, and data privacy challenges for optimal UAV integration within transportation infrastructure systems management.…”
Get full text

Cybersecurity and Major Cyber Threats of Smart Meters: A Systematic Mapping Review by Jones Márcio Nambundo, Otávio de Souza Martins Gomes, Adler Diniz de Souza, Raphael Carlos Santos Machado

“…These gaps include design requirements, software and firmware updates, physical security, the use of big data to detect vulnerabilities, user data privacy, and inconsistencies in machine learning algorithms. …”
Get full text

Exploring artificial intelligence for healthcare from the health professionals’ perspective: The case of limited resource settings by Mulugeta Desalegn Kasaye, Amare Gebrie Getahun, Mulugeta Hayelom Kalayou

“…Conclusions Our study revealed that positive attitude, good knowledge, and formal training are crucial to advance healthcare using AI technologies. In addition, this study identified self-reported AI concerns of the participants such as; privacy and security of data, ethical issues, and accuracy of AI systems. …”
Get full text

The Potential for Large Language Models to Transform Cardiovascular Medicine (Russian Translation) by Quer, G., Topol, E.J.

“…Potential risks, such as loss of data privacy or potential diagnostic errors, should be addressed before use in clinical practice. …”
Get full text

Entrepreneurial strategies for sustainable growth: a deep dive into cloud-native technology and its applications by T. A. Alka, Aswathy Sreenivasan, M. Suresh

“…The policymaker's and enterprises' focus and actionable intervention are necessary for developing mechanisms to solve the barriers of regulatory compliance, lack of skilled manpower, data security, privacy issues, and upfront investment for entrepreneurial success.…”
Get full text

Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection by Peng Luo, Rangjia Cai, Yuanbo Guo

“…The widespread use of the internet has led to frequent cryptographic attack event incidents, which pose various risks, including the leakage of personal information, privacy data, identity theft, and potential legal liabilities. …”
Get full text

Providers' perceptions of implementing standardized postpartum family planning: a qualitative study of midwives and nurses in GhanaAJOG Global Reports at a Glance by Sarita Sonalkar, Ernest Maya, Chris Guure, Arden McAllister, Dzifa Adimle Puplampu, Roseline Dansowaa Doe, Mary Eluned Gaffield, James Kiarie

“…We interpreted data using thematic analysis. Results: Providers indicated that use of one-on-one counseling and the mobile application in hospital-based postpartum care delivery was acceptable, feasible, and appropriate. …”
Get full text

Multimodal and Temporal Graph Fusion Framework for Advanced Phishing Website Detection by S. Kavya, D. Sumathi

“…FGCL-Net ensures privacy-preserving learning across decentralized datasets through federated contrastive learning, achieving 93-95% accuracy while safeguarding data privacy. …”
Get full text

Assessment of The Potential Interference and Conflict of Artificial Intelligence With Human Rights and Citizenship: Challenges and Solutions by Hossein Khazaei, Mojtaba Hemmati

“…Therefore, it is necessary to devise solutions to address these challenges, which may include diversifying data, ensuring operational transparency, establishing legal and ethical frameworks, government commitments to balance the use of artificial intelligence with the fulfillment and enforcement of the right to work, data protection, respect for privacy, reducing discrimination, collaborating with stakeholders, establishing international legal standards, and fostering international cooperation for the safe development of artificial intelligence. …”
Get full text

Integrating health equity in artificial intelligence for public health in Canada: a rapid narrative review by Samantha Ghanem, Marielle Moraleja, Danielle Gravesande, Jennifer Rooney

“…After conducting title/abstract and full-text screening of articles, and consensus decision on study inclusion, the data extraction process proceeded using an extraction template. …”
Get full text

Hybrid pre trained model based feature extraction for enhanced indoor scene classification in federated learning environments by Monica Dutta, Deepali Gupta, Vikas Khullar, Sapna Juneja, Roobaea Alroobaea, Pooja Sapra

“…This study proposes and implements a novel MultiData model, which integrates DL with Linear Discriminant Analysis (LDA) and Federated Learning (FL) to enhance classification performance while preserving data privacy. …”
Get full text

FedRecSys: A Federated Learning-Based Recommender System for Concept Drift Adaptation by Anagha Chaudhari, A. A. Hitham Seddig, Roshani Raut, Aliza Sarlan

“…A new field called deep learning can be used to handle large amounts of multidimensional data in different e-commerce platforms. …”
Get full text

Human activity recognition system based on low-cost IoT chip ESP32 by Chao HU, Bangyan LU, Yanbing YANG, Zhe CHEN, Lei ZHANG, Liangyin CHEN

“…Human activity recognition widely exists in applications such as sports management and activity classification.The current human activity recognition applications are mainly divided into three types: camera-based, wearable device-based, and Wi-Fi awareness-based.Among them, the camera-based human activity recognition application has the risk of privacy leakage, and the wearable device-based human activity recognition application has problems such as short battery life and poor accuracy.Human activity recognition based on Wi-Fi sensing generally uses Wi-Fi network cards or software-defined radio devices to identify the rules of channel state information changes, so as to infer user activity.It does not have the problems of privacy leakage and short battery life.But Wi-Fi network cards need to rely on computers and software-defined radio platforms are expensive, which greatly limit the application scenarios of Wi-Fi sensing.Aiming at the above problems, a human activity recognition system based on the low-cost IoT chip ESP32 was proposed.Specifically, the Hampel filter and Gaussian filter were used to preprocess the channel state information obtained by ESP32.Then, the principal component analysis and discrete wavelet transform were utilized to reduce the dimension of the data.Finally, the K-nearest neighbor (KNN) algorithm was applied to classify data.The experimental results show that the system can achieve a recognition accuracy which close to the current mainstream Wi-Fi perception system (Intel 5300 network card) when only two ESP32 nodes are deployed, and the average accuracy rate for the six activities is 98.6%.…”
Get full text

Nurses’ perspectives on AI-Enabled wearable health technologies: opportunities and challenges in clinical practice by Haitham Alzghaibi

“…However, concerns regarding data privacy, accuracy, cost, and reduced human interaction persist. …”
Get full text

Pooled Rideshare in the U.S.: An Exploratory Study of User Preferences by Rakesh Gangadharaiah, Johnell Brooks, Lisa Boor, Kristin Kolodge, Haotian Su, Yunyi Jia

“…The study incorporated 77 actionable items developed from the results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. …”
Get full text