Fracture and stability of strain-softening materials and structures by Tabbara, Mazen

“…For direct tension specimens, the model predicts a development of asymmetric response after the peak load. …”
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Energy conversion of heat from abandoned oil wells to mechanical refrigeration - Transient analysis and optimization by Mohammed Al-Khawaja (17093017)

“…Among 43 investigated refrigerants, R1234ze(E) has higher efficiency, lower Pumping Work Ratio (PWR), and requires a smaller size of the heat exchangers. Using the genetic algorithm optimization method with R1234ze(E) as working fluid in both power and cooling loops, a maximum power loop efficiency of 6.3% and COP of 5.3 were obtained at a high pressure of 29 bar (in the power loop) with minimal expander diameter of 64, compressor diameter of 171 mm, and 18 expander-compressor units.…”

Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…The Grey Wolf Optimization (GWO) algorithm, which directs the system's optimization process, demonstrates a competitive trade-off between exergy efficiency, freshwater production, costs, NPV, and environmental impact. …”

An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication by Syed Muhammad Amrr (16855557)

“…The control law is developed using a state-dependent single feedback vector, which further assists in obeying the constrained network. …”

Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

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Automated quantification of penile curvature using artificial intelligence by Tariq O. Abbas (11247771)

“…<h3>Objective</h3><p dir="ltr">To develop and validate an artificial intelligence (AI)-based algorithm for capturing automated measurements of Penile curvature (PC) based on 2-dimensional images.…”

Net energy–cost optimization of STPV–PDRC integrated greenhouses: Balancing energy production and cooling demand under crop-specific DLI constraints by Mohammadreza Gholami (17032317)

“…This study developed a multi-objective optimization framework integrating passive daytime radiative cooling (PDRC) materials and semi-transparent photovoltaics (STPV) to enhance greenhouse performance under varying daily light integral (DLI) constraints. …”

Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS by Iman Faridmehr (14150616)

“…After 150 days, the average creep deflection of RC beams containing 20, 40, and 60% GGBFS was 30, 70, and 100% higher than the ones for conventional concrete beams, respectively. A hybrid artificial neural network coupled with a metaheuristic Whale optimization algorithm has been developed to estimate the overall deflection of concrete beams due to creep and shrinkage. …”

AI-based remaining useful life prediction and modelling of seawater desalination membranes by Al Ali, Fajer

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Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

“…In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes mellitus (T2DM). Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …”

Optimizing ADWIN for Steady Streams by Moharram, Hassan

“…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …”
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

“…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …”

Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”

Communication-Based Adaptive Overcurrent Protection for Distribution Systems with DistributedGenerators by Sulaiman, Mohamad

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Virtual Inertia Support in Power Systems for High Penetration of Renewables—Overview of Categorization, Comparison, and Evaluation of Control Techniques by Naruttam Kumar Roy (16904544)

“…As a result, multiple inertia augmentation control strategies were developed to increase frequency stability and maximize power usage in the grid-integrated renewable energy systems. …”

Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone by Saeed Ullah Jan (9079260)

“…This issue of security risk can be minimized conspicuously by developing a robust authentication scheme for IoD deployment military drones. …”

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…Our main insight was that rather than interpreting the attribution of individual visits to the predicted outcome, we could instead attribute a model’s prediction to a group of visits.</p><h3>Conclusion</h3><p dir="ltr">We presented a quantitative and qualitative evidence that CD interpretations can explain patient-specific predictions using CD attributions of individual visits or a group of visits.…”