Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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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). …”

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

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Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…To overcome these challenges we developed LNCRI (Long Non-Coding RNA Identifier), a novel machine learning (ML)-based tool for the identification of lncRNA transcripts. …”

Low Cost Autopilot Design Using Fuzzy Supervisory Control by Hadi, Mahmoud

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Conceptual Design and Analysis of Concentrated Photovoltaic Thermal (CPVT) Solar Collectors with Different Configurations by Sharaf, Omar Z.

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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. In this paper, we proposed a novel technique in steganography within the digital images such is RGB, Gray Scale, Texture, Aerial images to achieve higher security, imperceptibility, capacity, and robustness as compared with existing methods. …”

Reconfigured Photovoltaic Model to Facilitate Maximum Power Point Tracking for Micro and Nano-Grid Systems by J. Prasanth Ram (19499062)

“…This enables the use of a simple Perturb and Observe (P&O) algorithm to easily track GMPP. For reconfiguration, a simple 5 × 5 PV array is considered, and a new physical relocation procedure based on the position square method is proposed. …”

Advancing Data Center Networks: A Focus on Energy and Cost Efficiency by Zina Chkirbene (16869987)

“…<p dir="ltr">Data centers serve as the backbone for cloud computing, enterprise services, and infrastructure-based offerings. One area of ongoing research in data center networking focuses on innovating new topologies for large-scale node connectivity. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…<p dir="ltr">Recently, electrochemical reduction of CO₂ into value-added fuels has been noticed as a promising process to decrease CO₂ emissions. The development of such technology is strongly depended upon tuning the surface properties of the applied electrocatalysts. …”

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced <u>machine learning</u> (ML) models to assess city performance comprehensively. …”

Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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DASSI: differential architecture search for splice identification from DNA sequences by Shabir Moosa (14153316)

“…This has been fueled through the development of new DL architectures. Yet genomics possesses unique challenges that requires customization and development of new DL models.…”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”

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. …”

Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring by Aya Nabil Sayed (17317006)

“…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”

A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…This leads to the second step, which involves formulating the multivariate time series CO₂ emissions forecasting challenges considering its influential factors. Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”