Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…We trained the model on 80% of the expert reviewed variants by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium and tested its performance on the remaining 20%, as well as on an independent set of variants of uncertain significance with experimentally determined functional scores.…”

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

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Effects of Dunn and Dunn learning styles model on achievement and motivation. (c2013) by Daouk, Carma

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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation by Iman M. Hosseini Naveh (16891482)

“…The obtained analysis emphasizes how the tuned SMPID can significantly increase the capability of tracking control on the proposed AC/HVDC interconnected model.…”

Recurring Multi-layer Moving Window Approach to Forecast Day-ahead and Week-ahead Load Demand Considering Weather Conditions by Dao H. Vu (19517236)

“…The multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance, which creates more flexibility and adaptability thereby improving the overall performance of the proposed approach. …”

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

“…Additionally, the mean power spectral density of the EMG signal decreased notably post-training. ConclusionThis study presents a structured approach for hypospadias training and highlights the effectiveness of wearable sensor technology for objective skill assessment. …”
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Traffic Transformer: Transformer-based framework for temporal traffic accident prediction by Mansoor G. Al-Thani (19237204)

“…Existing neural network-based models generally suffer from a limited field of perception and poor long-term dependency capturing abilities, which severely restrict their performance. …”

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

“…Additionally, the mean power spectral density of the EMG signal decreased notably post-training. </p><h3>Conclusion</h3><p dir="ltr">This study presents a structured approach for hypospadias training and highlights the effectiveness of wearable sensor technology for objective skill assessment. …”

Analyzing the efficiency of intellectual capital: anewapproach based on DEA-MPI technology by Mohamed Habib, Ahmed

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A Blockchain-Based Scalability Solution with Microgrids Peer-to-Peer Trade by Ameni Boumaiza (19160734)

“…The results of this study demonstrate that the suggested technique outperforms base-layer models in terms of scalability while still maintaining the essential elements of security and decentralization. …”

Cloud-based deep learning-assisted system for diagnosis of sports injuries by Xiaoe Wu (17541951)

Assessing the eco-environmental aspects of fossil fuels-based units substitution of Point Aconi thermal power plant by green-based energies: a case study of Canada by Nima Amiri (21842687)

“…This paper presents a model that replaces fossil fuels used in a proposed thermal power plant in Point Aconi, Nova Scotia, with photovoltaic and wind turbine units based on the region’s climate conditions. …”

Feeder protection challenges with high penetration of inverter based distributed generation by Margossian, Haraj

“…The increasing proportion of inverter based distributed generation (DG) in the power system may limit the short circuit power available at distribution substations and consequently cause significant troubles for the protection of distribution feeders where DG are connected. …”
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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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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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Anomaly Detection on Smart Grids With Optimized Convolutional Long Short-Term Memory Model by Ahmad N. Alkuwari (22392226)

“…The evaluated machine learning models include traditional shallow detectors, deep learning-based detectors, and hybrid models that employ both horizontal and vertical detection strategies. …”

PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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Validating a Structural Model of Destination Image, Satisfaction, and Loyalty Across Gender and Age by Assaker, Guy

“…We confirm that DI predicts satisfaction and has a significant direct and indirect effect on loyalty. After examining the validated structural model across different groups of respondents based on gender, age, and the gender by age interaction, we found that the model constructs differ across some of the groups. …”
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A Decision Modelling Approach for Perceived and Engaged Immersive Visual Interactive Applications on the Metaverse by IBRAHIM, SAMAR

“…The new extended IVFN-FWZIC method weighs the criteria for benchmarking the optimal applications based on experts’ judgments. The results illustrate the effectiveness of the modelling approach and indicate that "spatial" and “haptics” are the most significant criteria in evaluating immersive visual interactive applications. …”
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Sulfur oxidative coupling of methane process development and its modeling via machine learning by Giovanni Scabbia (13751501)

“…The outcomes of the simulated process were used to design a data-driven modeling approach, based on machine learning methods, and to evaluate its interpolation accuracy. …”