Evaluation of Virtual Commerce Applications for the Metaverse Using Spherical Linear Diophantine-Based Modeling Approach by Ghazala Bilquise, Khaled Shaalan, Manar AlKhatib

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Employing convolutional neural networks and explainable artificial intelligence for the detection of seizures from electroencephalogram signal by Tamilarasi Kathirvel Murugan, Anush Kameswaran

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Evaluating the quality of medical content on YouTube using large language models by Mahmoud Khalil, Fatma Mohamed, Abdulhadi Shoufan

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Optimizing sustainability: information aggregation in smart factories for energy efficiency enhancement by Mohd Anjum, Naoufel Kraiem, Hong Min, Yousef Ibrahim Daradkeh, Ashit Kumar Dutta, Sana Shahab

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Towards transparency in AI: Explainable bird species image classification for ecological research by Samparthi V.S. Kumar, Hari Kishan Kondaveeti

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Evaluation of TOPSIS Algorithm for Multi-Criteria Handover in LEO Satellite Networks: A Sensitivity Analysis by Pascal Buhinyori Ngango, Marie-Line Lufua Binda, Michel Matalatala Tamasala, Pierre Sedi Nzakuna, Vincenzo Paciello, Angelo Kuti Lusala

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Human Trajectory Imputation Model: A Hybrid Deep Learning Approach for Pedestrian Trajectory Imputation by Deb Kanti Barua, Mithun Halder, Shayanta Shopnil, Md. Motaharul Islam

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Enhanced Semantic Retrieval with Structured Prompt and Dimensionality Reduction for Big Data by Donghyeon Kim, Minki Park, Jungsun Lee, Inho Lee, Jeonghyeon Jin, Yunsick Sung

“…After generating prompts utilizing two methods, silhouette scores were computed to assess the quality of embedding clusters. …”
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Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration by Sunawar Khan, Tehseen Mazhar, Tariq Shahzad, Muhammad Amir Khan, Sghaier Guizani, Habib Hamam

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Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques by Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani

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Counterfactual and Prototypical Explanations for Tabular Data via Interpretable Latent Space by Simone Piaggesi, Francesco Bodria, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi

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Explainability of a Deep Learning-Based Classification Model for Antineutrophil Cytoplasmic Autoantibody–Associated Glomerulonephritis by Maria A.C. Wester Trejo, Maryam Sadeghi, Shivam Singh, Naghmeh Mahmoodian, Samir Sharifli, Zdenka Hruskova, Vladimír Tesař, Xavier Puéchal, Jan Anthonie Bruijn, Georg Göbel, Ingeborg M. Bajema, Andreas Kronbichler

“…These maps were analyzed by pathologists to compare the decision-making criteria of humans and the DL model and assess the impact of different training settings. …”
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Structured reporting of neuroendocrine tumors in PET/CT using [18F]SiTATE - impact on interdisciplinary communication by Anna Hinterberger, Lukas Trupka, Sophia Kortbein, Ricarda Ebner, Nicola Fink, Matthias F. Froelich, Dominik Nörenberg, Carmen Wängler, Björn Wängler, Ralf Schirrmacher, Adrien Holzgreve, Matthias Brendel, Stefanie Corradini, Christoph Auernhammer, Johannes Rübenthaler, Freba Grawe

“…All reports were evaluated by a radiologist and a surgeon through a questionnaire to determine their contribution to facilitating clinical decision-making and to assess their completeness, linguistic quality, and overall quality. …”
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Survey of Navigational Perception Sensors’ Security in Autonomous Vehicles by Abhijeet Solanki, Wesam Al Amiri, Marim Mahmoud, Blaine Swieder, Syed Rafay Hasan, Terry N. Guo

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A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets by Ciaran O’Connor, Mohamed Bahloul, Steven Prestwich, Andrea Visentin

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A fair and interpretable deep learning approach for healthcare access prediction in underserved communities by Akash Saxena, Saurabh Sharma, Punit Kumar Johari, Ankur Pandey, Sunil Kumar

“…Moreover, we conduct extensive simulations to assess the trade-offs between model complexity, fairness, and computational efficiency. …”
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Modeling radiologists’ cognitive processes using a digital gaze twin to enhance radiology training by Akash Awasthi, Anh Mai Vu, Ngan Le, Zhigang Deng, Supratik Maulik, Rishi Agrawal, Carol C. Wu, Hien Van Nguyen

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AI-Driven Innovations in Software Engineering: A Review of Current Practices and Future Directions by Mamdouh Alenezi, Mohammed Akour

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Hybrid Machine Learning-Based Fault-Tolerant Sensor Data Fusion and Anomaly Detection for Fire Risk Mitigation in IIoT Environment by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Shashi Bhushan, Vinay Rishiwal, Manish Kumar

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Enhancing consistency of AHP-based expert judgements: A new approach and its implementation in an interactive tool by Shimon Frish, Irit Talmor, Omer Hadar, Maxim Shoshany, Aviad Shapira

“…The proposed tool has broad potential applications in various complex decision-making scenarios. In future developments, the tool could also be adapted to incorporate clustering techniques for managing complex criteria sets, or extended to support group decision making by assessing consensus levels and recommending minimal adjustments. • AHP-based pairwise comparisons of n criteria by experts are recorded in an n × n reiprocal preference matrix whose eigenvalu λmax is used to compute the consistency ratio (CR) of the resulting priority vector. • An iterative greedy algorithm developed to enhance the consistency of the solution in case CR>10% enforces minimal intervention by limiting the adjustment to single-step modifications on unaltered pairwise comparisons only. • The algorithm is implemented in an interactive, user-friendly software tool, ensuring transparency and expert engagement through real-time, traceable consistency refinement.…”
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