Artificial Intelligence in Geography Teaching: Potentialities, Applications, And Challenges by Cennet Şanlı

“…Therefore, the study recommends developing in-service teacher training programs, implementing AI-supported instructional scenarios, creating culturally responsive and localized content, and promoting ethical data use awareness. It also emphasizes the need for experimental research using quantitative and qualitative methods to evaluate AI's pedagogical value in enhancing students' mapping skills, spatial thinking, and conceptual understanding. …”
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Wearable Devices for Training and Patient Monitoring: A Comprehensive Review by Magdalena Kajzar

“…However, challenges such as data accuracy, privacy concerns, and integration with healthcare systems must be addressed and present opportunities for future advancements. …”
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Hybrid AI for Predictive Cyber Risk Assessment: Federated Graph-Transformer Architecture With Explainability by Jaime Govea, Rommel Gutierrez, William Villegas-Ch, Alexandra Maldonado Navarro

“…This paper proposes a hybrid model for predictive cyber risk assessment that integrates Graph Neural Networks (GNNs) for relational pattern modeling, a Transformer-based language model (CyberBERT) for semantic representation of logs and traffic data, and a Federated Learning framework to preserve data privacy during training. …”
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A Blockchain-Based E-Participation Framework Utilizing Zero-Knowledge Proofs With Guaranteed Sampling and Differential Reward Mechanisms by Jungwon Seo, Juhui Lee, Yunjae Joo, Kangho Lee, Vijayan Sugumaran, Sooyong Park

“…Blockchain-based E-participation systems significantly enhance transparency, data integrity, and security compared to traditional E-participation methods. …”
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Iman di Era Digital: Praktik Konseling Pastoral Berbasis Teknologi Digital by Andreas Fredriko Simatupang, Gunawan Yuli Agung Suprabowo

“…However, there are also shortcomings such as a lack of mastery of digital technology among companions, data privacy and security issues, formal legitimacy from church authorities, as well as a potential reduction in the depth of interpersonal relationships. …”
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Towards trustworthy AI-driven leukemia diagnosis: A hybrid Hierarchical Federated Learning and explainable AI framework by Khadija Pervez, Syed Irfan Sohail, Faiza Parwez, Muhammad Abdullah Zia

“…Hierarchical federated learning reduced communication costs by 15% while maintaining data privacy. The integration of explainable artificial intelligence improved the transparency of model decisions, with a high area under the ROC curve (AUC) of 0.98 for the classification of leukemia cells. …”
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From Capturing a Moment to New Insights: A Methodological Reflection on Reflexive Photo-Elicitation Interviews to Understand Visitor Experiences in Cultural Institutions by Tesfaye Fentaw Nigatu, Alexander Trupp, Pek Yen Teh, Elangkovan Narayanan Alagas

“…Innovative qualitative methods like photo-elicitation interviews are gaining traction for their ability to produce data through negotiation and reflexivity. Reflective Photo-Elicitation Interviews (RPIs) are commonly used in nature and community-based tourism research, but their application in cultural institutions remains limited. …”
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From Centralization to Decentralization: Blockchain’s Role in Transforming Social Media Platforms by Bidita Sarkar Diba, Jayonto Dutta Plabon, Nishat Tasnim, Mehjabin Hossain, Durjoy Mistry, Sourav Sarker, M. F. Mridha, Yuichi Okuyama, Jungpil Shin

“…Conventionally, social media systems are based on central architectures that may indirectly solve the problems of data privacy and platform responsibility since there are increased threats, including identity theft and fake news spread across such systems. …”
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Economic and social benefits of socially responsible actions towards employees in agribusiness enterprises by Matejun Marek, Ratajczak Marcin

“…Key socially responsible actions towards employees include employee satisfaction surveys as well as data protection and protection of employee privacy. …”
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A novel blockchain-based surveillance and early-warning technology for infectious diseases by Liwei OUYANG, Yong YUAN, Xinhu ZHENG, Jun ZHANG, Fei-Yue WANG

“…The key of early prevention and control of infectious diseases is to use the early warning technology and system to monitor the abnormal occurrence and trend of infectious diseases.There are still some problems in the existing infectious diseases automated-alert and response systems,such as lack of intelligence,poor efficiency in exchange of key information,as well as difficulties in distributed decision-making.Based on the distributed blockchain architecture,a novel blockchain-based surveillance and early-warning technology for infectious diseases was proposed,leveraging emerging information technologies including artificial intelligence,big data and smart contract.The technology could aggregate monitoring forces from multiple parties efficiently,integrate various early warning technologies flexibly,and establish a distributed and collaborative monitoring environment for knowledge integration and intelligent interconnection with guaranteed security and privacy protection.In this framework,smart contract was served as a “software-defined agent” to fuse decisions,monitor the outbreak,and issue warnings in an automatic and real-time fashion,so as to meet the key requirements of accuracy and timeliness,and avoid the decision bias of single evidence.…”
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The streetlights are watching you: A historical perspective on value change and public lighting by Taylor Stone

“…Smart city trends are spurring a new generation of streetlights, with lampposts being fitted with sensors, cameras and a host of other technologies aimed at monitoring and data collection. This has raised concerns about privacy, surveillance and power relations, arguably creating a changing value landscape for streetlights. …”
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Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain by Ming YANG, Xuexian HU, Qihui ZHANG, Jianghong WEI, Wenfen LIU

“…Federated learning is a new distributed machine learning technology, where training tasks are deployed on user side and training model parameters are sent to the server side.In the whole process, participants do not need to share their own data directly, which greatly avoids privacy issues.However, the trust relationship between mobile users in the learning model has not been established in advance, there is hidden safety when users perform cooperative train with each other.In view of the above problems, a federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain was proposed.The scheme allowed the server side to use subjective logic models to evaluate the reputation of participating mobile users and provided them with credible reputation opinions sharing environment and dynamic access strategy interface based on the technique of smart contract of blockchain.Theoretical and experimental analys is results show that the scheme can enable the server side to select reliable users for training.And it can achieve more fair and effective reputation calculations, which improves the accuracy of federated learning.…”
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Detecting Emerging DGA Malware in Federated Environments via Variational Autoencoder-Based Clustering and Resource-Aware Client Selection by Ma Viet Duc, Pham Minh Dang, Tran Thu Phuong, Truong Duc Truong, Vu Hai, Nguyen Huu Thanh

“…Detecting such evolving threats is especially challenging in decentralized environments where raw traffic data cannot be aggregated due to privacy or policy constraints. …”
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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. …”
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Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform by Zulqarnain Rashid, Amos A Folarin, Yuezhou Zhang, Yatharth Ranjan, Pauline Conde, Heet Sankesara, Shaoxiong Sun, Callum Stewart, Petroula Laiou, Richard J B Dobson

“…Digital biomarkers developed through collected data are providing useful insights into different diseases. …”
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Blockchain Enabled Federated Learning for Detection of Malicious Internet of Things Nodes by Rachid Alami, Anjanava Biswas, Varun Shinde, Ahmad Almogren, Ateeq Ur Rehman, Tahseen Shaikh

“…This will not only enhance the accuracy of the unified federated learning model but also preserve the privacy of each cluster because no actual data is sent to fog layer for central model training. …”
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TriagE-NLU: A Natural Language Understanding System for Clinical Triage and Intervention in Multilingual Emergency Dialogues by Béatrix-May Balaban, Ioan Sacală, Alina-Claudia Petrescu-Niţă

“…The system is built on a federated learning architecture to ensure data privacy and adaptability across regions and is trained using TriageX, a synthetic, clinically grounded dataset covering five languages (English, Spanish, Romanian, Arabic, and Mandarin). …”
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"If my husband was in the labor ward with me, my baby wouldn't have died"; experiences on birth companionship from a tertiary health facility, Tanzania. by Michael Obed Mwakyusa, Ali Said, Shekha Selemani, Musa Kakiziba, Judica Christopher, Nathanael Shauri Sirili, Fadhlun M Alwy Al-Beity

“…Braun and Clarke's six-step thematic analysis approach was used to analyze the data.<h4>Results</h4>Three major themes emerged: "Bonding and Learning with Spouse/Partner," "Assurance of Maternal Safety," and "Fear of Blame and Breach of Confidentiality." …”
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An Industry Application of Secure Augmentation and Gen-AI for Transforming Engineering Design and Manufacturing by Dulana Rupanetti, Corissa Uberecken, Adam King, Hassan Salamy, Cheol-Hong Min, Samantha Schmidgall

“…Built on an LLM framework enhanced by RAG, the system performs similarity-based retrieval and part recommendations while preserving data privacy through selective obfuscation using the ROT13 algorithm. …”
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FL-TENB4: A Federated-Learning-Enhanced Tiny EfficientNetB4-Lite Approach for Deepfake Detection in CCTV Environments by Jimin Ha, Abir El Azzaoui, Jong Hyuk Park

“…The TinyML-based local model ensures real-time deepfake detection with minimal latency, while FL enables privacy-preserving training by aggregating model updates without transferring sensitive video data to centralized servers. …”
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