Hybrid sorption thermal–battery storage in photovoltaic greenhouses: Toward net-zero energy and reduced battery stress by Mohammadreza Gholami (17032317)

“…A comprehensive mathematical model was developed for solar irradiance distribution, STPV output, BESS operation, and SoTES performance, embedded within a multi-objective optimization framework using the Tribe Intelligence Evolutionary Optimizer (TIEO) to balance reductions in energy dependency (ED) and improvements in net present value (NPV). …”

B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core by Yahuza Bello (19645930)

“…Our findings show the superiority of container-based model over VM-based model in terms of resource utilization. …”

The Effect of the Variation of the Modulus of Subgrade Reaction on the Design of Large Shallow Foundations by Al Kaaby Al Zoaby, Hassan

“…With the use of variable coefficient across the mat foundation, a significant decrease in the steel reinforcement is witnessed and an optimized/ more adapted steel distribution is observed.…”
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ECP: Error-Aware, Cost-Effective and Proactive Network Slicing Framework by Amr E. Aboeleneen (19237135)

Reactions, Adsorption and Diffusion in FCC Catalysts by Mahaly, Wafa

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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail (22457644)

“…The comparative analysis of model complexity confirmed that increasing the sophistication of the LSTM model significantly enhances predictive accuracy and generalization capabilities. …”

Glass Selection for High-Rise Residential Buildings in the United Arab Emirates based on Life Cycle Cost Analysis by Mokhtar, Ahmed

“…The architect's decision to select a glass type for a high rise building has significant impact on both the initial and the running cost of a building. …”
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PneuX-Net: An Enhanced Feature Extraction and Transformation Approach for Pneumonia Detection in X-Ray Images by Kashif Munir (6182237)

“…The ensemble methodology harnesses the complementary strengths of these models, improving feature representation and mitigating overfitting, a prevalent issue in white-box models. …”

A customised fetal growth and birthweight standard for Qatar: a population-based cohort study by Thomas Farrell (3933833)

“…</p><h3>Methods</h3><p dir="ltr">The PEARL registry data on women delivering in Qatar (2017–2018) was used to develop a multivariable linear regression model predicting optimal birthweight. …”

A Novel Transformer-Based Approach for Adult’s Facial Emotion Recognition by Uzma Nawaz (21980708)

“…An ablation study further validates the contribution of each model component, and comparisons with CNN-based and transformer-based approaches confirm the effectiveness of the model. …”

Improving the performance of a commercial absorption cooling system by using ejector: A theoretical study by Hamza K. Mukhtar (17821004)

“…Nevertheless, ACS offers a green alternative to typical DX systems. In this study, a numerical model was developed for the commercial low-capacity Robur® absorption cooling system (RACS). …”

Fixing a heart valve by Nature Research (16552612)

“…All of these factors significantly increase the rate of complications following valve replacement, so valve repair is a more viable option in these parts of the world. …”

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas by Marwan Dhuheir (19170898)

“…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …”

Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

“…Cluster Editing, a known model for correlation clustering, has garnered significant consideration in the parameterized complexity area and has been utilized in a range of practical contexts. …”
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A clustering metaheuristic for large orienteering problems by Almiqdad Elzein (13141038)

“…The metaheuristic aims to dramatically improve the computation time of a given Orienteering Problem algorithm without a significant decrease in the solution quality of that algorithm, especially for large Orienteering Problems. …”

When Should a Brain MRI Be Performed in Children with New-Onset Seizures? Results of a Large Prospective Trial by Hourani, R.

“…Univariate analysis showed a significant increase in the frequency of epileptogenic lesions with decreasing age, the presence of developmental delay, and the number and types of seizures at presentation. …”
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Prehospital plasma transfusion versus standard of care following traumatic injury: a review of the systematic reviews and a meta-analysis by Ayman El-Menyar (440103)

“…PHP did not significantly decrease vasopressor use or late mortality; however, it may reduce the total use of RBCs in the first 24 h. …”

Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach by Ahmad Abujaber (9100064)

“…We aimed to build a machine learning predictive model to predict the in-hospital mortality for patients who sustained Traumatic Brain Injury (TBI).…”

Impact of the fear of Covid-19 infection on intent to breastfeed; a cross sectional survey of a perinatal population in Qatar by Shuja Mohd Reagu (12051406)

“…</p><h3>Conclusions</h3><p dir="ltr">The rates of Obsessive–compulsive symptoms were increased and the rates of intent to breastfeed were decreased when compared with pre pandemic rates. The obsessive–compulsive symptoms and the intent to not breastfeed were significantly associated with fear of infection to the new-born. …”

Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges by Haseeb Javed (18576340)

“…By systematically reviewing literature and case studies from the past decade, we explore how these advanced computational methods improve diagnostic accuracy, personalize treatment plans, and optimize patient monitoring. Dynamic ensemble techniques, which leverage multiple predictive models to improve outcome accuracy, offer significant promise in addressing the complexities of patient data and disease manifestations. …”