Impact of Sampling Technique on the Performance of Surrogate Models Generated with Artificial Neural Network (ANN): A Case Study for a Natural Gas Stabilization Unit by Mohamed Ibrahim (3465677)

“…<div><p>Data-driven models are essential tools for the development of surrogate models that can be used for the design, operation, and optimization of industrial processes. …”

Biomechanically Regularized Deep Deformable Registration for CT and US Fusion by Snigdha Mohanty (16904919)

“…Our approach leverages deep learning to model complex deformation fields while incorporating biomechanical priors derived from liver anatomy and tissue properties to enhance the physical plausibility and robustness of the registration process. We utilize a convolutional neural network to predict the deformation field between the CT and US images, guided by a biomechanical regularization term that penalizes unrealistic deformations. …”

Non-Linear Profile Monitoring Using Artificial Neural Network Fault Detection by Mohamed, Ahmed Fares

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Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model by Dabeeruddin Syed (16864260)

“…The proposed framework consists of two stages, namely, data cleaning, and model building. The data cleaning phase applies pre-processing techniques to the raw data and adds additional features of lag values. …”

Traffic Transformer: Transformer-based framework for temporal traffic accident prediction by Mansoor G. Al-Thani (19237204)

“…This significant shift enhances the model's ability to capture long-range dependencies within time series data. Moreover, it facilitates a more flexible and comprehensive learning of diverse hidden patterns within the sequences. …”

DDoS Detection Mechanism Using Trust-Based Evaluation System in VANET by M. Poongodi (14158869)

“…The major trust elements in the evaluation of trust are frequency value statistics, trust hypothesis statistics, residual energy, trust policy, and data factor. …”

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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High frequency volatility forecasting and risk assessment using neural networks-based heteroscedasticity model by Aryan, Bhambu

“…The computational results demonstrate the proposed model’s superior performance over sixteen forecasting methods in three error metrics, Value-at-risk, and statistical tests for high frequency volatility forecasting and risk assessment tasks.…”
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Modeling of Tool Wear when Turning of TI-6AL-4V Titanium Alloy by Al Hassani, Azza Rashed

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Artificial Intelligence in the Fight Against COVID-19: Scoping Review by Alaa Abd-Alrazaq (17430900)

Indoor Positioning Techniques and Approaches for WI-FI Based Systems by Abusara, Ayah Mahmoud

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Experimental Verification of Low-Pressure Kinetics Model for Direct Synthesis of Dimethyl Carbonate Over CeO₂ Catalyst by G. Ibrahim (7601063)

“…<p dir="ltr">Dimethyl carbonate (DMC) has emerged as a promising candidate for sustainable chemical processes due to its remarkable versatility and low toxicity. …”

Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

MicroCrystalNet: An Efficient and Explainable Convolutional Neural Network for Microcrystal Classification Using Scanning Electron Microscope Petrography by Mohammed Yaqoob (344668)

“…<p dir="ltr">Morphological characterization of microcrystalline rock textures typically relies upon the visual interpretation and manual measurement of scanning electron microscopy (SEM) imagery: a practice fraught with subjectivity, inefficiency, sampling bias, and data loss. We introduce a state-of-the-art computer vision pipeline, built on deep learning architectures, for segmenting and classifying individual microcrystals from SEM images. …”

High frequency volatility forecasting and risk assessment using neural networks-based heteroscedasticity model by Aryan Bhambu (18767731)

“…The computational results demonstrate the proposed model’s superior performance over sixteen forecasting methods in three error metrics, Value-at-risk, and statistical tests for high frequency volatility forecasting and risk assessment tasks.…”

IoT platforms assessment methodology for COVID-19 vaccine logistics and transportation: a multi-methods decision making model by Yasir Ali (799969)

“…<p dir="ltr">The supply chain management (SCM) of COVID-19 vaccine is the most daunting task for logistics and supply managers due to temperature sensitivity and complex logistics process. Therefore, several technologies have been applied but the complexity of COVID-19 vaccine makes the Internet of Things (IoT) a strong use case due to its multiple features support like excursion notification, data sharing, connectivity management, secure shipping, real-time tracking and monitoring etc. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …”

Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks by Mohamed Massaoudi (16888710)

“…The proposed TCN-GWO uses both synchronously sampled values and synthetic values from various bus systems. …”

Ensemble Learning for Precise State-of-Charge Estimation in Electric Vehicles Lithium-Ion Batteries Considering Uncertainty by Aya Haraz (22225036)

“…A well-structured ML pipeline was developed to integrate these processes, optimizing the entire model development cycle for efficiency and practical implementation. …”

Living Materials: Preserving Student Innovation in Art and Science through Digital Twins and AI in Partnership with Qatar National Library : What Happens To Your Work After You Gra... by Arif Shaon (13761784)

“…</p><p dir="ltr">The presentation introduces key concepts in long-term digital curation, including the value of preserving process data alongside final outputs, the limitations of commercial cloud storage, and the role of trusted research repositories in ensuring long-term access, attribution, and reuse. …”