Blockchain and signcryption enabled asynchronous federated learning framework in fog computing by Zhou Zhou, Youliang Tian, Jinbo Xiong, Changgen Peng, Jing Li, Nan Yang

“…Federated learning combines with fog computing to transform data sharing into model sharing, which solves the issues of data isolation and privacy disclosure in fog computing. …”
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User experience with pregnancy tracker mobile apps: Findings from comment-based qualitative study. by Md Alamgir Hossain, Janet Perkins, Md Tanvir Hasan, Sharon Low Bee Lian, Ribica Chowdhury, Md Tanzirul Alam, Anisuddin Ahmed, Mohammad Sohel Shomik, Shams El Arifeen, Ahmed Ehsanur Rahman, Aniqa Tasnim Hossain, M Shafiqur Rahman

“…This study aimed to explore the user experience (UX) of pregnancy tracker mobile apps used by pregnant women.<h4>Methods</h4>This study explored the dynamics between users' experiences and multifaceted dimensions of advanced features, high-quality materials and information, strict privacy policies, problem-solving abilities, and the usefulness of app features and contents. …”
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PERCEPTIONS AND EXPERIENCES OF M-HEALTH TECHNOLOGIES AND SOCIAL MEDIA: A QUALITATIVE STUDY IN PATIENTS WITH SCHIZOPHRENIA by Pasquale Caponnetto, Maria Salvina Signorelli, Jennifer Tiralongo, Alessandro Rodolico, Carmen Concerto, Antonino Petralia, Lucio Inguscio

“…The qualitative methodology used consists of an individual structured interview and the data were subjected to thematic analysis. …”
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Optimization of Cross-Border e-Commerce Logistics Supervision System Based on Internet of Things Technology by Pingping Sun, Lingang Gu

“…Then, functions such as swarm intelligence contract, legal anonymous identity authentication, intelligent transaction matching, abnormal data analysis and detection, privacy protection, and traceability are realized under the framework of the supervision system. …”
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Toward Culturally and Linguistically Responsive E-Learning in Post-COVID-19 Higher Education: Perspectives from the United Arab Emirates by Sarah Hopkyns

“…In the Gulf, cultural, religious, and sociolinguistic dynamics can present additional challenges for teaching and learning online. Reluctance to use cameras due to modesty, privacy, and E-safety concerns, amongst others, affects interaction and rapport. …”
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Federated learning applications in soil spectroscopy by Giannis Gallios, Nikolaos Tsakiridis, Nikolaos Tziolas

“…Convolutional neural networks were used to estimate key soil attributes such as soil organic carbon, texture, pH, cation exchange, and total nitrogen using VNIR or MIR spectral data from the Kellogg Soil Survey Laboratory. …”
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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review by Xi Wang, Yujia Zhou, Guangyu Zhou

“…On the basis of these findings, we proposed an integrative ethical framework, GenAI4MH, comprising 4 core dimensions—data privacy and security, information integrity and fairness, user safety, and ethical governance and oversight—to guide the responsible use of GenAI in mental health contexts. …”
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An explainable and federated deep learning framework for skin cancer diagnosis. by Shuvo Biswas, Sajeeb Saha, Muhammad Shahin Uddin, Rafid Mostafiz

“…However, protecting patient data privacy is a major concern in medical research. …”
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The Role of Artificial Intelligence in Medical Imaging: From Diagnosis to Ethical Frontiers by Nouf Abuhadi

“…The challenges AI encounters in radiography include the ‘black box’ issue, accuracy of data, technological and infrastructural complexity, ethical issues such as patient privacy and data security, overreliance on AI, and bias. …”
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Distributed Training Techniques for Intelligent Model in Space-Based Information Networks by LI Yuanjun, YANG Dewei, LI Jianing, FENG Xiao

“…In addressing the issues of data distribution heterogeneity, outdated models, and data privacy and security in distributed training of intelligent models, a federated learning architecture of intelligent models was designed based on blockchain technology and applied to space-based information networks. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Because of the privacy concerns about the transaction data, it is essential not to leak it when training prediction models for credit card fraud analysis. …”
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Ethical Considerations in Carbamazepine Pharmacogenomics Testing by Madeline Yuzwa, Rachel Bracken

“…We propose an updated framework for ethical implementation of pharmacogenomic testing, emphasizing four key areas: ensuring consistent and equitable access to testing, comprehensive patient education and informed consent, robust patient privacy and data management practices, and culturally aware approaches to genetic counseling. …”
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Developing a youth-friendly internet-enabled HIV risk calculator: A collaborative approach with young key populations, living in Soweto, South Africa. by Mamakiri Mulaudzi, Gugulethu Tshabalala, Stefanie Hornschuh, Kofi Ebenezer Okyere-Dede, Minjue Wu, Oluwatobi Ifeloluwa Ariyo, Janan J Dietrich

“…Framework analysis was used to analyse qualitative data through a qualitative data analysis software called NVivo. …”
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Evaluating GPT models for clinical note de-identification by Bayan Altalla’, Sameera Abdalla, Ahmad Altamimi, Layla Bitar, Amal Al Omari, Ramiz Kardan, Iyad Sultan

“…Abstract The rapid digitalization of healthcare has created a pressing need for solutions that manage clinical data securely while ensuring patient privacy. This study evaluates the capabilities of GPT-3.5 and GPT-4 models in de-identifying clinical notes and generating synthetic data, using API access and zero-shot prompt engineering to optimize computational efficiency. …”
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Model interpretability on private-safe oriented student dropout prediction. by Helai Liu, Mao Mao, Xia Li, Jia Gao

“…With well-explained features from both quantitative and qualitative aspects, our approach enhances the feasibility and reasonableness of dropout predictions using machine learning techniques. We believe our approach represents a novel end-to-end framework of artificial intelligence application in the field of sustainable education management from the view of decision-makers, as it addresses privacy leakage protection and enhances model credibility for practical management implementations.…”
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Encrypted traffic classification method based on convolutional neural network by Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

“…Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.…”
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Bridging the Gap: Leveraging AI to Address Talent Shortages in Organizations by Muhammad ZEESHAN, Umar ALI, Sameer ALI

“…However, it also reveals ongoing challenges with AI biases, ethical concerns, and data privacy. These issues necessitate transparency, regular audits, and comprehensive training for HR professionals to ensure the responsible and effective use of AI. …”
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brain2print AI powered web tool for creating 3D printable brain models by Christopher Rorden, Matthew McCormick, Taylor Hanayik, Mohamed Masoud, Sergey M. Plis

“…This approach not only simplifies the process but also safeguards user privacy by keeping all data on local hardware.…”
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Exploring the influence of cognitive factors among Chinese parents on the sustainability of children’s digital education by Tingyu Zhang, Qianling Jiang, Wenjing Zhang

“…Findings Perceived playability, usefulness, social influence, and satisfaction significantly predict continuance intention. …”
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Multi-level high utility-itemset hiding. by Loan T T Nguyen, Hoa Duong, An Mai, Bay Vo

“…Privacy is as a critical issue in the age of data. …”
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