Substation Inspection Safety Risk Identification Based on Synthetic Data and Spatiotemporal Action Detection by Chengcheng Liu, Weihua Zhang, Weijin Xu, Bo Lu, Weijie Li, Xuefeng Zhao

“…Model training is conducted using three datasets: a real dataset, a synthetic dataset generated via a VWP, and a mixed dataset comprising both real and synthetic data. …”
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SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine by Jacob Blindenbach, Jiayi Kang, Seungwan Hong, Caline Karam, Thomas Lehner, Gamze Gürsoy

“…Due to the sensitive nature of this data and varied laws and regulations, additional security measures are needed to ensure data privacy. …”
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Data Sovereignty and Open Sharing: Reconceiving Benefit-Sharing and Governance of Digital Sequence Information by Masanori Arita

“…Using the example of the COVID-19 pandemic, the tension between open science principles and data control rights is explained. …”
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Achieving Secure and Efficient Data Access Control for Cloud-Integrated Body Sensor Networks by Zhitao Guan, Tingting Yang, Xiaojiang Du

“…An authorization certificate composed of the signature and related privilege items is constructed which is used to grant privileges to data receivers. To ensure security, a unique value is chosen to mask the certificate for each data receiver. …”
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Multimodal Face Data Sets—A Survey of Technologies, Applications, and Contents by Kamela Al-Mannai, Khaled Al-Thelaya, Jens Schneider, Spiridon Bakiras

“…Biometric verification for controlling access to digital devices has become ubiquitous for its ease-of-use but often relies on notoriously data-hungry supervised machine learning. …”
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Health equity innovation in precision medicine: data stewardship and agency to expand representation in clinicogenomics by Patrick J. Silva, Vasiliki Rahimzadeh, Reid Powell, Junaid Husain, Scott Grossman, Adam Hansen, Jennifer Hinkel, Rafael Rosengarten, Marcia G. Ory, Kenneth S. Ramos

“…Digital tools that preserve privacy, document provenance, and enable the management of data as intellectual property have great promise. …”
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Enhancing tourism management through big data: Design and implementation of an integrated information system by Lulu Wang

“…The system combines data from several sources, including booking systems, social media platforms, and tracking devices, and addresses issues related to data privacy, quality, and integration. …”
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Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control by PENG Lihui, ZHANG Qiong, LI Tianyi

“…To address this issue, this study proposed a series of targeted prevention and control measures, including clarifying the principle of algorithmic fairness, formulating industry norms and standards, improving the accountability mechanism and regulatory system, and optimizing the data collection and processing environment, so as to effectively curb the phenomenon of algorithmic discrimination while making full use of the advantages of AI technology, so that AI technology in government data governance can truly benefit the people, and promote social fairness and justice.…”
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Empathy, bias, and data responsibility: evaluating AI chatbots for gender-based violence support by Borja Sanz Urquijo, María López Belloso, Ainhoa Izaguirre-Choperena

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Perlindungan Data Pribadi Konsumen Oleh Penyelenggara Sistem Elektronik Dalam Transaksi Digital by Rista Maharani, Andria Luhur Prakoso

“…In the field of digital economic transactions, the significance of personal data is increasing, driven by the widespread use of big data. …”
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Verifiable Blockchain-Empowered Federated Learning for Secure Data Sharing in the Internet of Medical Things by Ping Guo, Shuilong Xu, Wenfeng Liang

“…This paper proposes a verifiable blockchain-empowered federated learning framework to address privacy and aggregation verification challenges in data sharing. …”
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Implementing Blockchain Technology for Secure Data Transactions in Cloud Computing Environments Challenges and Solutions by Dandu Varalakshmi, N Shirisha, K Suresh, Saidhbi Shaik, V Venkatesh, C F Theresa Cenate

“…We note that while existing security frameworks such as security standards may be useful: they fail to deal with limitations in areas such as privacy, authentication, and secure transactions across multiple cloud platforms. …”
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Analysis of Model Merging Methods for Continual Updating of Foundation Models in Distributed Data Settings by Kenta Kubota, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…To address these issues, we propose a novel framework that integrates model merging with federated learning to enable continual foundation model updates without centralizing sensitive data. In this framework, each client fine-tunes a local model, and the server merges these models using multiple merging strategies. …”
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Adaptive integrated weight unsupervised multi-source domain adaptation without source data by Zhirui Wang, Liu Yang, Yahong Han

“…Existing methods assume that all source domain data can be accessed directly. However, such an assumption is unrealistic and causes data privacy concerns, especially when the source domain labels include personal information. …”
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Big Data Meets Social Networks: A Survey of Analytical Strategies and Research Challenges by Shashank Sheshar Singh, Shashank Singh, Kuldeep Singh, Vishal Srivastava, Harish Kumar Shakya

“…In addition, it covers issues of scalability, data quality, privacy, and real-time analysis. SN analytics can be useful for researchers from across domains like business and marketing, healthcare and biomedicine, social sciences and psychology, politics and governance, cybersecurity and fraud detection, recommendation systems, crisis management, and disaster response to extract crucial information from vast datasets and formulate domain-specific strategies.…”
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Enhancing cybersecurity through autonomous knowledge graph construction by integrating heterogeneous data sources by Hatoon Alharbi, Ali Hur, Hasan Alkahtani, Hafiz Farooq Ahmad

“…In our research, we construct a cybersecurity knowledge graph (CKG) autonomously using heterogeneous data sources. We further enhance the CKG by applying logical rules and employing graph analytic algorithms. …”
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Big Data–Driven Health Portraits for Personalized Management in Noncommunicable Diseases: Scoping Review by Haoyang Du, Jianing Yu, Dandan Chen, Jingjie Wu, Erxu Xue, Yufeng Zhou, Xiaohua Pan, Jing Shao, Zhihong Ye

“…In terms of volume, structured data were widely used (64.29%-100% depending on portrait type), while unstructured data usage varied significantly (19.05%-93.33%). …”
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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…Using BERTopic modeling, a machine learning technique, this research systematically analyzes literature from 2013 to 2024, providing an overview of AI and big data applications mapped to SDGs which is a first. …”
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Contribution and legacy: a qualitative study of older people’s attitudes about sharing their routinely collected health data for research purposes in New Zealand by Engelina Groenewald, Jasmine Appleton, Brendan Hallam, Cristian Gonzalez-Prieto, Susan Yates, Daniel Wilson, Gillian Dobbie, Rosie Dobson, Sarah Cullum

“…Data were analysed using thematic analysis. Results Themes identified were: 1) Benefits: participants believed that there were benefits to sharing their health data such as helping others, improving health services, advancing scientific knowledge, and giving back to the health system; sharing health data was also seen as a reflection of good character, and people felt that their pre-existing views about whether they wished to share health data should be respected even if they were no longer able to consent. 2) Concerns: participants had concerns about sharing data with private companies, the use of inaccurate data, and the potential personal and societal consequences of sharing health data. 3) Expectations: participants encouraged collaboration between institutions in New Zealand, but expected data privacy to be maintained, processes to be transparent and cultural values around data to be respected; there was an expectation those sharing health data (patients or institutions) should benefit from any private sector gains. …”
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Barriers impeding research data sharing on chronic disease prevention among the older adults in low-and middle-income countries: a systematic review by Neema Florence Vincent Mosha, Patrick Ngulube

“…A PRISMA flow chart was used to map out the number of studies that were identified, included, and excluded.ResultsFive main barriers were consistently highlighted, including a lack of necessary resources (9, 69%), dealing with complex and sensitive research data (2,15%), lack of policies, procedures, guidelines (5,38%), medical big data processing and integration (2,15%), and inadequate ethical considerations, legal compliance, and privacy protection (6,46%). …”
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