Performance Prediction Using Classification by MOOLIYIL, GITA

“…A comprehensive evaluation requires that multiple models with different algorithms were analyzed using key performance measures. …”
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Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Overall, studies that used smaller data sets reported higher accuracy.</p><h3>Conclusions</h3><p dir="ltr">This paper examined multiple AI-based skin cancer detection models. …”

Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”

Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…This review synthesizes evidence from more than 500 peer-reviewed studies published between 2020 and 2026, mapping DRL applications across distributed generation, transmission, distribution, energy storage systems, energy markets, local energy management, grid security, and data privacy. We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”
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Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone by Saeed Ullah Jan (9079260)

“…Nonetheless, the performance analysis section will be executed using the algorithmic big-O notation. The results show that these protocols are verifiably protected in the ROM and ROR model using the CDHP.…”

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…Leveraging FL enables efficient model training across diverse end-user applications while preserving data privacy. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”

Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants by Hamad Al Shamsi, Jawaher

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Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System by Sahawneh, Laith Rasmi

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Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

“…Ethical considerations, such as safeguarding patient privacy, ensuring data security, and mitigating algorithmic bias, underscore the importance of responsible AI integration. …”

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

Humanizing AI in medical training: ethical framework for responsible design by Mohammed Tahri Sqalli (18420840)

“…The transparency pillar highlights the crucial role of maintaining the explainabilty of AI algorithms, while the fairness and justice pillar emphasizes on addressing biases in healthcare data and designing models that prioritize equitable medical training outcomes. …”

An XML Document Comparison Framework by Tekli, Joe

“…As the Web continues to grow and evolve, more and more information is being placed in structurally rich documents, XML documents in particular, so as to improve the efficiency of similarity clustering, information retrieval and data management applications. Various algorithms for comparing hierarchically structured data, e.g., XML documents, have been proposed in the literature. …”
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