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Articles 121 - 150 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki Dec 2026

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

All Works

Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an …


A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah Dec 2026

A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah

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Detecting diseases in olive leaves is crucial for maintaining tree health and ensuring stable olive production. Early signs of infection often appear on the leaves, making them a key indicator for timely disease detection and intervention. Traditionally, farmers rely on visual inspection or laboratory tests to diagnose plant diseases. However, recent advancements in deep learning (DL) have significantly improved the accuracy and efficiency of olive leaf disease diagnosis. Numerous studies in the literature have explored this task using CNN-based architectures and, more recently, Vision Transformers. While these models have shown promising performance on benchmark datasets, they are often trained and …


Fair And Explainable Educational Recommendations With A Hybrid Graph-Gru Framework, Edmund Evangelista, Syed M.Salman Bukhari Dec 2026

Fair And Explainable Educational Recommendations With A Hybrid Graph-Gru Framework, Edmund Evangelista, Syed M.Salman Bukhari

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Artificial Intelligence (AI) recommender systems are increasingly used in education to personalize learning and help students navigate large collections of digital learning resources. However, many existing approaches emphasize predictive accuracy over fairness, robustness, diversity, and transparency. This creates an important educational challenge. The students with limited participation histories may receive less reliable support, while highly popular resources may dominate recommendation lists and limit access to other useful learning materials. To address this challenge, this study aims to develop and evaluate a responsible educational recommender framework that supports personalized learning resource navigation while making recommendation behavior more fair, stable, diverse, and …


A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz Dec 2026

A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz

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Renal cell carcinoma (RCC) is considered the most aggressive and common form of renal cancer. Therefore, early detection is crucial to ensure appropriate and effective treatment planning. In our study, we propose a novel computer-aided diagnostic (CAD) approach which incorporates a deep learning ensemble to differentiate between five renal tumor subtypes, utilising the modality of contrast-enhanced computed tomography (CE-CT). The addressed renal lesions are malignant tumors (chromophobe RCC (chRCC), papillary RCC (pRCC), and clear cell RCC (ccRCC)) and benign tumors (renal oncocytoma (RO) and angiomyolipoma (AML)). Our study includes 280 patients who underwent renal biopsy, 112 patients were diagnosed with …


Radio Frequency Tagging–Enabled Patient Monitoring: Integrating Mobility Tracking With Early Warning Systems For Enhanced Safety, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi Dec 2026

Radio Frequency Tagging–Enabled Patient Monitoring: Integrating Mobility Tracking With Early Warning Systems For Enhanced Safety, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Ensuring patient safety in healthcare environments requires continuous monitoring systems capable of identifying early warning signs of clinical risk. Traditional surveillance methods often fail to capture meaningful patterns in patient movement, limiting their ability to prevent incidents such as falls, prolonged immobility, or unnoticed health deterioration. Radio Frequency Tagging technology has been increasingly adopted for real-time patient tracking; however, existing systems are generally limited to location detection and lack predictive insights into patient behaviour. To overcome these limitations, this study presents a Radio Frequency Tagging-based patient monitoring framework that integrates mobility tracking with an early warning mechanism to enable proactive …


Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil Dec 2026

Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil

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This study presents a novel AI-based framework that leverages Instagram image and metadata analysis to infer Big Five personality traits and deliver personalized career recommendations for high school students in the UAE. Addressing the limitations of traditional recommender systems that rely on self-reported questionnaires or text, the proposed approach uses multimodal visual features—including profile metrics, HSV color patterns, semantic image labels, and texture analysis—to enable a non-intrusive, scalable personalization method. A pilot study involving data from 30 student accounts served as a proof of concept. Correlation analysis identified profile and HSV features as the most predictive, and four machine learning …


Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton Dec 2026

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …


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Mgrre_Thinsections_Mgrre_11_21, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_12, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_11, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_10, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_9, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_8, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_7, Mgrre Nov 2026

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Mgrre_Thinsections_Mgrre_11_4, Mgrre Nov 2026

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