Autonomous Vehicles Delivery Systems: Analyzing Vehicle Routing Problems with a Moving Depot by Madani, Batool Mezar

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Turbo-charging dominating set with an FPT subroutine by Abu-Khzam, Faisal N.

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Mechanical perturbation control of cardiac alternans by Hazim, Azzam

“…Electrical activity is represented in two detailed ionic models, the Luo-Rudy 1 and the Fox models, while two active contractile tension models, namely a smooth variant of the Nash-Panfilov model and the Niederer-Hunter-Smith model, are used to represent mechanical activity in the heart. …”
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Indoor Localization Schemes for Mobile Robots by Al-Jarrah, Islam Mohammad-Amin

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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. …”

Cross entropy error function in neural networks by Nasr, G.E.

“…The ANN is implemented using the cross entropy error function in the training stage. …”
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Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction by Ramesh, Jayroop

“…Digital phantom and clinical datasets are used to evaluate the performance of the models. Results: The results show that the Real-Time Intermediate Flow Estimation (RIFE) algorithm outperforms the others in terms of the Structural Similarity Index Method (SSIM): 0.986 ± 0.010, Peak Signal to Noise Ratio (PSNR): 44.13 ± 2.76, and Mean Square Error (MSE): 18.86 ± 206.90 across all datasets. …”
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Exploring Digital Competitiveness through Bayesian Belief Networks by Qazi, Abroon

“…The methodology involves constructing BBN models using data from the IMD Digital Competitiveness Ranking 2023 for 64 countries. …”
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FAILURE RATE ANALYSIS OF BOEING 737 BRAKES EMPLOYING NEURAL NETWORK by Al-Garni, Ahmed Z.

“…One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

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Predicting stability of classes in an object-oriented system by Azar, D.

“…Many metrics have been proposed to assess these software attributes and for this purpose, prediction models have been widely used. However, in almost all cases, these models were not efficient when used to predict the quality characteristics (stability or other) of new unseen software as their prediction accuracy decreases significantly. …”
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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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Enhancement of two-dimensional holographic images by resolutionimprovement through hologram aperture expansion by Abdel-Aal, R.E.

“…Due to the 1-D nature of the algorithm, different predictive models used for rows and columns in the case of 2-point and similar objects; which calls for some prior knowledge of the object geometry. …”
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The Assessment and Allocation of Public Private Partnership Risks in the UAE by Shaban, Mazhd

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DNA Base-Calling Techniques by Odeh, Fadi

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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.…”

Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace by Shahid, Saif Mohammad

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Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…This success rate is determined by the frequency of instances where models performed better when augmented data was used compared to instances with no augmentation. …”

Fuzzy Logic Based Patients' Monitoring System by Al-Dmour, Jumana

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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

“…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”