Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Our study aimed to use data mining classification techniques, in order to classify the individual into two categories: user or non-user. …”
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The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques by DOULEH, HANI ABDULLAH YOSEF ABU

“…The purpose of this study is to diagnose acute coronary syndrome using the widely available respiratory diagnosing tools and laboratory test results using data mining classification techniques (Decision tree, Gradient boosted tree, Neural Network, and Naïve Bias). …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by Zainab Akhtar (15192184)

“…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …”

Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems by Khaled Dhibi (16891524)

Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem by Nezir Aydin (8355378)

“…To manage uncertainty and decide effectively, stochastic programming (SP) methods are often employed. Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). …”

Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

“…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. Tuning of the consequent part parameters are accomplished using extreme learning machine. …”

Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm by Abraham Marquez Alcaide (18582451)

“…The performance of the EMA-based SHM is presented showing experimental results considering a reduced number of switching angles applied to a specific three-level converter, but the method can be extrapolated to any other three-level converter topology.…”

Forecasting the Direction of GCC Stock Indexes Using Support Vector Machine (SVM) Algorithm by Zeino, Yaser Abdullah

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Assessment of Drug-Induced QTc Prolongation in Mental Health Practice: Validation of an Evidence-Based Algorithm by Monica Zolezzi (10115698)

“…</p></h3><h3>Methods</h3><h3><p dir="ltr">Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). …”

Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

“…In order to address this issue, in this paper, we propose a novel hybrid approach with both convolutional and recurrent neural networks combined, which is based on the long short-term memory module. Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”

Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

“…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms by Tekli, Joe

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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

“…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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A Review of the Genetic Algorithm and JAYA Algorithm Applications by Abu Zitar, Raed

“…On the other a well-known and somewhat older evolutionary based method called the Genetic Algorithm with applications is also presented here. …”
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Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

“…To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
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FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”

Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by Sakib Mahmud (15302404)

“…TTR-GAN comprises cascaded dual-stage 1D Cycle Generative Adversarial Networks (1D-CycleGANs) constructed using Super-ONNs. In the first phase, corrupted wPPG waveforms are blindly restored using a 1D-CycleGAN-based restoration framework. …”