Decreased Analgesic Requirements in Super Morbidly Versus Morbidly Obese Patients Undergoing Laparoscopic Sleeve Gastrectomy by Hamed Elgendy (14148846)

Dispatchable capacity optimization strategy for battery swapping and charging station aggregators to participate in grid operations by Mingze, Zhang

“…Taking the aggregator as a unit, battery swapping and charging stations (BSCSs) for electric vehicles (EVs) can be aggregated and dispatched by grid operators, to realize the demand-side resource regulation. Considering the characteristics of an aggregator’s multilateral services, in this study, BSCSs need to ensure the quality of swapping service for EV users and participate in the demand-side regulation response. …”
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Optimizing the number of players and training bout durations in soccer small‐sided games: Effects on mood balance and technical performance by Zouhaier Farhani (22330693)

“…<h3>Abstract</h3><p dir="ltr">This study aimed to determine the effects of different bout durations (1 × 12 min, 2 × 6 min and 3 × 4 min) of three‐a‐side (3vs3) and four‐a‐side (4vs4) small sided games (SSGs) with goalkeepers, on the profile of mood state (POMS) scores, and technical performance (percentage of successful passes, percentage of successful tackles, percentage of successful duels, and percentage of ball loss) in soccer players. …”

Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

“…Our experimental results show a possible decrease in data perturbation error by 51.7% and 61.2% for smart meters and fog-computing data aggregators perturbed data, respectively, compared to the commonly used Gaussian mechanism.…”

Dispatchable capacity optimization strategy for battery swapping and charging station aggregators to participate in grid operations by Mingze Zhang (9947863)

“…<p>Taking the aggregator as a unit, battery swapping and charging stations (BSCSs) for electric vehicles (EVs) can be aggregated and dispatched by grid operators, to realize the demand-side resource regulation. Considering the characteristics of an aggregator’s multilateral services, in this study, BSCSs need to ensure the quality of swapping service for EV users and participate in the demand-side regulation response. …”

Influence of temperature on tire-pavement noise in hot climates: Qatar case by Okan, Sirin

“…There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. …”
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The Effect of Number of Corrugation on Crashworthiness of Aluminum Corrugated Tube under Lateral Loading by Hozhabr Mozafari (18891892)

“…The results show that tubes with corrugations have a higher mean crushing force which is directly proportional to the number of corrugations. …”

Influence of temperature on tire-pavement noise in hot climates: Qatar case by Okan Sirin (14603304)

“…There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. …”

Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA by Muhammad Shehab (16904880)

“…Driven by the rising deployment of deep reinforcement learning (DRL) techniques that are capable of coping with solving non-convex optimization problems, we employ DRL to predict and optimally tune the IRS phase shift matrices. …”

Deep Learning for Dynamic Wildlife Monitoring: A Real-Time Approach by Abdul Basit Mughal (22929001)

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation by Mostafa M., Shibl

“…Deep RL is utilized to model the EV chargers and the EV users. …”
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation by Mostafa M. Shibl (17821382)

“…Deep RL is utilized to model the EV chargers and the EV users. …”

FLACON: A Deep Federated Transfer Learning-Enabled Transient Stability Assessment During Symmetrical and Asymmetrical Grid Faults by Mohamed Massaoudi (16888710)

“…In practice, TSA based on deep learning is preferable for its high accuracy but often overlooks challenges in maintaining data privacy while coping with network topology changes. …”

Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030) by Khaled F. Alkaraki (22051967)

Data-Efficient Wheat Disease Detection Using Shifted Window Transformer: Enhancing Accuracy, Sustainability, and Global Food Security by Muhammad Khubaib (22927822)

“…This research presents a deep learning technique based on the Shifted Window (Swin) Transformer, a powerful attention-based model that effectively captures both local and global information for enhanced classification output. …”

Improving pediatric trauma care: an automated system for wrist trauma detection using GELAN by Promit Basak (22997776)

“…The results of our study highlight the capacity of deep learning to improve the diagnosis of pediatric trauma, decrease the burden on radiologists, and boost patient outcomes.…”

A decision support system for automating document retrieval and citation screening by Raymon van Dinter (10521952)

YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

Energy-Efficient Cell Association and Load Balancing for Low Battery Users in Heterogeneous Cellular Networks by Abdul Qadeer Khan (22502168)

“…This paper proposes improved cell association schemes based on the battery levels of UE and Deep Q-learning (DQL) to achieve load balancing and to decrease the power consumption of Low Battery Users (LBUs). …”