AI-Driven Ensemble Classifier for Jamming Attack Detection in VANETs to Enhance Security in Smart Cities by Walid El-Shafai, Ahmad Taher Azar, Saim Ahmed

“…This emerging threat highlights a critical research gap in the development of sophisticated, AI-driven security solutions for VANETs. In response to this challenge, our study introduces an innovative artificial intelligence (AI) model, meticulously engineered to detect jamming attacks in VANETs. …”
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A hybrid approach to conangtent generation based on user experience using generative AI elements by Mohammad Javad Shayegan, Hossein Hosseinpour

“…The content was evaluated using the Perplexity metric, with three AI models—BERT, GPT-2, and DistilBERT. Results show that the enhanced K-means algorithm paired with GPT-3.5 Turbo achieved the best performance, yielding a Perplexity score of 3.476. …”
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From algorithms to negotiations: Why health diplomacy must adapt. by Brian Li Han Wong, Garry Aslanyan, Warisa Panichkriangkrai, Ricardo Baptista Leite, Jemilah Mahmood, Anders Nordström

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A Proposed Vision for Using Artificial Intelligence in Enhancing Strategic Value of Human Resources by Nadera Hourani

“…Artificial intelligence (AI) has been integrated into human resource management (HRM), enabling the transformation of the field through routine job automation, decision-making enhancement, and evidence-based strategies. …”
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CropsDisNet: An AI-Based Platform for Disease Detection and Advancing On-Farm Privacy Solutions by Mohammad Badhruddouza Khan, Salwa Tamkin, Jinat Ara, Mobashwer Alam, Hanif Bhuiyan

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Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review by Fan YUAN, Jia LI

“…However, the study also identifies several critical challenges, including concerns about data accuracy concerns, inherent algorithmic biases, risks to academic integrity, and the potential weakening of independent thinking skills due to over-reliance on AI systems. …”
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Evaluation of AI-Powered Routine Screening of Clinically Acquired cMRIs for Incidental Intracranial Aneurysms by Christina Carina Schmidt, Robert Stahl, Franziska Mueller, Thomas David Fischer, Robert Forbrig, Christian Brem, Hakan Isik, Klaus Seelos, Niklas Thon, Sophia Stoecklein, Thomas Liebig, Johannes Rueckel

“…<b>Objectives</b>: To quantify the clinical value of integrating a commercially available artificial intelligence (AI) algorithm for intracranial aneurysm detection in a screening setting that utilizes cranial magnetic resonance imaging (cMRI) scans acquired primarily for other clinical purposes. …”
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Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry by Valeria Di Stefano, Martina D’Angelo, Francesco Monaco, Annarita Vignapiano, Vassilis Martiadis, Eugenia Barone, Michele Fornaro, Luca Steardo, Marco Solmi, Mirko Manchia, Luca Steardo

“…Moreover, ethical considerations surrounding data integrity, algorithmic transparency, and patient individuality must guide AI’s integration into psychiatry. …”
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Multimodal Fusion and Cutting-Edge AI-Based Smart Vending Machines for Electronic Component Management by M. Karthiga, Syarifah Bahiyah Rahayu, E. Suganya, S. Sankarananth, S. Sountharrajan, K. Venkatesan

“…These challenges stem from the diversity of electronic components, which can range from small passive components like resistors and capacitors to large integrated circuits. This research presents a groundbreaking system for managing electronic components in smart vending machines, leveraging advanced AI and innovative techniques. …”
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Development of AI-based smart box trap system for capturing a harmful wild boar by Francis Ifaso Besala, Ryunosuke Niimoto, Jae Hoon Lee, Shingo Okamoto

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Exploring the Potential of the Bicameral Mind Theory in Reinforcement Learning Algorithms by Munavvarkhon Mukhitdinova, Mariana Petrova

“…This study explores the potential of Julian Jaynes’ bicameral mind theory in enhancing reinforcement learning (RL) algorithms and large language models (LLMs) for artificial intelligence (AI) systems. …”
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Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models by Sami Naouali, Oussama El Othmani

“…Against baseline classifiers without feature selection and MLVarianceThreshold, our framework delivers significant improvements, establishing RST as a vital tool for explainable AI (XAI) in healthcare diagnostics and IoT systems. …”
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The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding by Yi Ma, Mingyang Chen

“…Qualitative findings highlighted teacher scaffolding’s pivotal role in contextualizing AI feedback, mitigating algorithmic rigidity, and fostering a “novice-to-self-regulated learner” trajectory. …”
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AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
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SHapley Additive exPlanations (SHAP) for Landslide Susceptibility Models: Shedding Light on Explainable AI by H. Al-Najjar, B. Kalantar, B. Pradhan, G. Beydoun, N. Ueda

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AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects by Soha G. Ahmed, Katrien Verbert, Nazar Zaki, Ashraf Khalil, Hamad Aljassmi, Fady Alnajjar

“…The review underscores the potential of AI-enhanced camera systems to improve road safety, emphasizing the need for diverse, multimodal data integration for comprehensive monitoring.…”
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Exploring Generative AI for YOLO-Based Object Detection to Enhance Flood Disaster Response in Malaysia by Jiehan Teoh, Zuliani Binti Zulkoffli, Kian Meng Yap, Huang Shen Chua

“…By adopting a systematic approach with the You Only Look Once (YOLO) algorithm, the model is trained on gen-AI-produced synthetic images and tested using real drone-captured images from past flood events. …”
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Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members by Nataly Buslón, Davide Cirillo, Oriol Rios, Simón Perera del Rosario

“…ResultsAnalysis of the focus group discussions revealed several critical barriers impacting the integration of AI in personalized medicine for trans people, including concerns around data privacy, biases in algorithmic decision-making, and the lack of tailored health care data reflective of trans experiences. …”
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GeoAI Dataset for Training a Deep Learning-based GEMS Snow Detection Model by Jin-Woo Yu, Jun-Hyeok Jung, Kyoung-Hee Kang, Yong-Mi Lee, Hyung-Sup Jung

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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…The novelty of this work lies in the integration of explainable AI with robust preprocessing and age-specific modeling across multiple ASD datasets, addressing both diagnostic accuracy and clinical interpretability. …”
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