Integration of data science with the intelligent IoT (IIoT): Current challenges and future perspectives by Inam Ullah, Deepak Adhikari, Xin Su, Francesco Palmieri, Celimuge Wu, Chang Choi

“…The Intelligent Internet of Things (IIoT) involves real-world things that communicate or interact with each other through networking technologies by collecting data from these “things” and using intelligent approaches, such as Artificial Intelligence (AI) and machine learning, to make accurate decisions. …”
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Global trends of big data analytics in health research: a bibliometric study by Li Yao, Li Yao, Yan Liu, Tingrui Wang, Chunyan Han, Qiaoxing Li, Qinqin Li, Xiaoli You, Tingting Ren, Yinhua Wang

“…Co-occurrence word analysis identified six key research areas: (1) the application of big data analytics in health decision-making; (2) challenges in the technological management of health and medical big data; (3) integration of machine learning with health monitoring; (4) privacy and ethical issues in health and medical big data; (5) data integration in precision medicine; and (6) the use of big data in disease management and risk assessment. …”
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Islam, Big Data, and Digital Ethics: Challenges in Religious Life in the Digital Age by Agung Saputra, Erni Asneli Asbi

“…These technologies offer opportunities to enhance the efficiency of religious practices, such as prayer reminders, Quran recitation, and zakat distribution, but they also present ethical challenges related to privacy, data misuse, and the erosion of deep spiritual experiences. …”
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Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions by Elias Dritsas, Maria Trigka

“…We review current strategies for responsible AI deployment, including regulatory frameworks, human-centered design principles, and privacy-preserving methods. By synthesizing methodological advances and cross-cutting challenges, this study provides a focused and interdisciplinary roadmap for the rigorous and equitable use of AI in social science research.…”
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The application of distributed autonomous organization governance mechanisms to civic medical data management by James Cunningham, Nigel Davies, Sarah Devaney, Søren Holm, Mike Harding, Victoria Neumann, John Ainsworth

“…The mechanisms employed by DAOs has the potential to be generalized beyond their core financial domain to a wide range of use cases. In the medical field the use of blockchain and DAOs can provide secure and transparent access to medical data, while ensuring patient privacy. …”
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Harnessing digital health data for suicide prevention and care: A rapid review by Laura Bennett-Poynter, Sridevi Kundurthi, Reena Besa, Dan W. Joyce, Andrey Kormilitzin, Nelson Shen, James Sunwoo, Patrycja Szkudlarek, Lydia Sequiera, Laura Sikstrom

“…The primary aim of this study is to identify considerations for the collection and use of digital health data for suicide prevention and care. …”
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Data Mining Techniques for Predictive Maintenance in Manufacturing Industries a Comprehensive Review by Chinthamu Narender, Ashish, P Mathiyalagan, B Devananda Rao, S Kannadhasan, M Suganya

“…Predictive maintenance (PdM) is one of the major methods used in modern manufacturing to realize downtime minimization, lower the cost of maintenance and maximize machine service life by analyzing the collected data using data mining methodologies. …”
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CHALLENGES AND OPPORTUNITIES IN THE IMPLEMENTATION OF BIG DATA ANALYTICS IN MANAGEMENT INFORMATION SYSTEMS IN BANGLADESH by Golam Mustafa, MD. Nurullah Rabbani, Avishek Nath, Md Mehedi Hasan Emon

“…The findings reveal that organizations in Bangladesh encounter challenges related to limited technological infrastructure, data security and privacy concerns, skill shortages, and regulatory complexities. …”
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Big data applications in intelligent transport systems: a bibliometric analysis and review by Mahbub Hassan, Hridoy Deb Mahin, Abdullah Al Nafees, Arpita Paul, Saikat Sarkar Shraban

“…We found that ethical, privacy, and security concerns related to the use of Big Data in ITS have received limited attention. …”
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Blockchain-based and verifiable multidimensional data aggregation and sharing scheme for smart grid by Jianwei CHEN, Shuyu WANG, Meiping ZHANG, Zhenping ZHANG

“…Aiming at the problem that how to support lightweight multi-dimensional data aggregation, achieve double-end integrity verification of multi-dimensional data in the overall process of the system, and deal with the centralization of cloud servers, a blockchain-based and verifiable multidimensional data aggregation and sharing scheme for smart grid was proposed.Firstly, in order to meet the demand for fine-grained analysis of power data in smart grid, privacy-preserving multidimensional data aggregation was achieved by using masked values and Horner’s rule.On this basis, for the data integrity verification problem of the existing data aggregation scheme in the sharing of cloud storage data with the third party, a new signature algorithm was designed by borrowing the RSA-based multiplicative homomorphic commitment scheme and homomorphic hash function homomorphism, which enabled the cloud server to verify the integrity of aggregated data and be used for integrity verification in the data sharing phase, i.e., it achieved double-end verifiability of cloud storage data and was resistant to internal attacks.Meanwhile, an aggregated data sharing architecture based on federated chain multichain was proposed to effectively avoid centralisation problems such as single-machine processing bottleneck and vulnerability to attacks.The theoretical analysis proves the security of the scheme.Performance experiments show that the proposed scheme has lower computation and communication costs compared with existing schemes.…”
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Blockchain-based and verifiable multidimensional data aggregation and sharing scheme for smart grid by Jianwei CHEN, Shuyu WANG, Meiping ZHANG, Zhenping ZHANG

“…Aiming at the problem that how to support lightweight multi-dimensional data aggregation, achieve double-end integrity verification of multi-dimensional data in the overall process of the system, and deal with the centralization of cloud servers, a blockchain-based and verifiable multidimensional data aggregation and sharing scheme for smart grid was proposed.Firstly, in order to meet the demand for fine-grained analysis of power data in smart grid, privacy-preserving multidimensional data aggregation was achieved by using masked values and Horner’s rule.On this basis, for the data integrity verification problem of the existing data aggregation scheme in the sharing of cloud storage data with the third party, a new signature algorithm was designed by borrowing the RSA-based multiplicative homomorphic commitment scheme and homomorphic hash function homomorphism, which enabled the cloud server to verify the integrity of aggregated data and be used for integrity verification in the data sharing phase, i.e., it achieved double-end verifiability of cloud storage data and was resistant to internal attacks.Meanwhile, an aggregated data sharing architecture based on federated chain multichain was proposed to effectively avoid centralisation problems such as single-machine processing bottleneck and vulnerability to attacks.The theoretical analysis proves the security of the scheme.Performance experiments show that the proposed scheme has lower computation and communication costs compared with existing schemes.…”
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Highly Secure and Adaptive Multisecret Sharing for Reversible Data Hiding in Encrypted Images by Jiang-Yi Lin, Ching-Chun Chang, Chin-Chen Chang, Chin-Feng Lee

“…Reversible data hiding in encrypted images (RDHEI) is a technique that not only allows the cover images can be fully restored without any loss of information after the embedded data has been extracted but also ensures the confidentiality within the cover images. …”
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A smart grid data sharing scheme supporting policy update and traceability by Xiaodong Yang, Ke Yao, Songyu Li, Xiaoni Du, Caifen Wang

“…Finally, the analysis results show that this scheme can protect the privacy of smart grid data, verify the integrity of smart grid data, resist collusion attacks and track the identity of malicious users who leak private keys, and its efficiency is better than similar data sharing schemes.…”
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Gradual Geometry-Guided Knowledge Distillation for Source-Data-Free Domain Adaptation by Yangkuiyi Zhang, Song Tang

“…Due to access to the source data during the transfer phase, conventional domain adaptation works have recently raised safety and privacy concerns. …”
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Bibliometric mapping of data science in education: Trends, benefits, challenges, and future directions by Muhammad Aizri Fadillah, Syafrijon, Sulandari, Febry Azmiana Siregar, Usmeldi

“…Co-occurrence analysis reveals three main clusters: DS approaches, student interactions with learning, and data analysis techniques. This study identifies key research trends and challenges, including limited infrastructure, skills gaps among educators, and privacy concerns, while addressing gaps in the literature regarding the long-term impact and contextualization of DS in education. …”
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The Adoption of Virtual Fitting Rooms in Iranian Sportswear Industries: A Mixed-Methods Study Based on TAM Model by Seyyed Iman Ghaffarisadr, Farzad Nobakht Sareban

“…Structural equation modelling was used to test the hypotheses. SMART PLS and SPSS 23 software were used for data analysis.Findings: The results supported the positive effect of the factors perceived ease of use, perceived usefulness, perceived enjoyment, and fashion leadership, as well as the negative impact of technology anxiety on adopting this technology. …”
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A DLP Module Design Based on Plug-in for MS Word by Hussein Al-sanabani, Murat İskefiyeli

“…This model uses security measures such as data encryption and access control to prevent accidental leakage of the classified files by the insiders. …”
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A decentralised architecture for secure exchange of assets in data spaces: The case of SEDIMARKGitHub by Erika Duriakova, Diarmuid O’Reilly-Morgan, Maroua Bahri, Maxime Costalonga, Gabriel Danciu, Septimiu Nechifor, Stefan-Cristian Jarcau, Tarek Elsaleh, Peipei Wu, Franck Le Gall, Grigorios Koutantos, Panagiotis Vlacheas, Luis Sánchez, Juan Ramón Santana, Pablo Sotres, Elias Tragos

“…Together the technologies used in SEDIMARK ensure privacy, trust and data quality for secure management, sharing, and monetisation of assets in data spaces.…”
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Mitigating Malicious Insider Threats to Common Data Environments in the Architecture, Engineering, and Construction Industry: An Incomplete Information Game Approach by KC Lalropuia, Sanjeev Goyal, Borja García de Soto, Dongchi Yao, Muammer Semih Sonkor

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Attitudes and preferences toward the adoption of voice-controlled intelligent personal assistants: Evidence from Croatia by Antun Biloš, Bruno Budimir, Borna Kraljević

“…This paper provides an examination of the differences between IPA users and non-users as well as an overview of (non-)user perception related to privacy and security issues associated with IPA and trust in companies' appropriate use of IPA-generated data. …”
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