Modelling the Impact of Bottlenecks on Arterial Travel Time Using Neural Networks by Abdallah, Azza

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Transfer learning for genotype–phenotype prediction using deep learning models by Feng, Samuel

“…If the large population data is extensive compared to small population data, expect transfer learning results to improve significantly. We show that Transfer learning is capable to create powerful models for genotype-phenotype predictions in large, well-studied populations and fine-tune these models to populations were data is sparse.…”
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Use of Animal Models for Investigating Cardioprotective Roles of SGLT2 Inhibitors by Najlaa A. Al Thani (17788493)

“…In this review, we summarize the animal models constructed to study the cardioprotective mechanisms of SGLT2is to help deliver a more comprehensive understanding of the in vivo work that has been done in this field and to help select the most optimal animal model to use when studying the different cardioprotective effects of SGLT2is.…”

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

Binary-NeRV: Hybrid-Precision Weights Binarization for Efficient Neural Video Representation by Shanableh, Tamer

“…In this work, we propose Binary-NeRV, a hybrid-precision extension of NeRV that integrates XNOR-based binary convolutions into the decoding pipeline to significantly reduce model size, bitrate, and computational complexity while reasonably preserving reconstruction fidelity. …”
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Edge-Optimized Deep Learning Architectures for Classification of Agricultural Insects with Mobile Deployment by Akhtar, Muhammad Hannan

“…The best quantized model, produced through Post-Training Quantization, was able to maintain a classification accuracy of 77.8% while significantly reducing the model size from 33 MB to 9.6 MB. …”
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Application and comparison of dynamic routing models for unsteady flow in simple and compound channels by Chatila, Jean Georges

“…The first, which viewed the composite flow field as a single hydraulic unit without storage, produced significant differences between simulated and observed stage and discharge hydrographs. …”
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Hypospadias Reconstruction Training: Development of an Ex-Vivo Model for Objective Evaluation of Surgical Skills by Abbas, Tariq

“…Video evaluations did not reveal significant differences due to short-term training. …”
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study by Mutasim Baba, Fuad

“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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Ownership type, bank models, and bank performance: the case of the Yemeni banking sector by Fekri Ali Mohammed Shawtari (18069346)

“…</p><h3>Findings</h3><p dir="ltr">The findings of the paper substantiate that the banking models are significant performance indicators. However, the results are contingent on the GDP growth of the country. …”

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

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Hypospadias Reconstruction Training: Development of an Ex-Vivo Model for Objective Evaluation of Surgical Skills by Tariq Abbas (368053)

“…</p><h3>Methods</h3><p dir="ltr">We combined subjective video evaluations with objective electromyography (EMG) measurements in a hands-on hypospadias training course. …”

Development of Seed Variables Prediction Models for Use in Dynamic Backcalculation of FWD Data by Nasr, Cynthia

“…This involves (1) calculating theoretical surface deflections through a finite element model that simulates different pavement structures and properties, (2) calculating FWD parameters and indices for each structure and (3) using those parameters to build Random Forest models that predict the seed variables with low OOB-error and high accuracy. …”
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State-of-the-art review of occupant behavior modeling and implementation in building performance simulation by Omar Ahmed (530933)

“…The main applications, advantages, and limitations of each model are discussed. The available literature on the influence of different OB patterns and occupants’ interaction with building systems, such as cooling, lighting, shading, and appliances, on building energy performance is evaluated. …”

Competition vs cooperation: An agent based model for sustainable tomatoes’ import system by Sarah Namany (17268922)

“…Interactions between trade partners are modeled using two game theoretic approaches counting<u> Cournot</u><u> competition</u> and <u>Cartel</u> collusion. …”

Deep Models for Stroke Segmentation: Do Complex Architectures Always Perform Better? by Ahmed Soliman (4591621)

“…These findings suggest that proposed complex architectures may be task-specific and simpler models with appropriate pre-/post-processing pipeline can be equally or more effective in generalization across different tasks in medical image segmentation.…”

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis by Md Arifuzzaman (11471123)

“…<p>The modification by polymers and nanomaterials can significantly improve different properties of asphalt. …”

A Comprehensive Review on Membrane Fouling: Mathematical Modelling, Prediction, Diagnosis, and Mitigation by AlSawaftah, Nour Majdi

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Circuit-Averaged Modeling of Non-Ideal Low-Power DC-AC Inverters by Ghizzawi, Farouk

“…The proposed model significantly reduces simulation times by using circuit-averaging and accurately anticipates the AC signal response by modeling the circuit behavior at different harmonics. …”
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