Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

“…The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. …”

Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”

Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

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Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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Sentiment visualization of correlation of loneliness mapped through social intelligence analysis by Hurmat Ali Shah (18192889)

“…Social media platforms have become a valuable source of data to study this phenomenon.</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. …”

A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…Aiming to tackle these obstacles, we have derived a new computational method in order to identify conserved regions of Single Nucleotide Polymorphisms (SNPs) on autosomal chromosomes that are differentiable in different populations. Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

“…To address these objectives, our proposed approach incorporates deep reinforcement learning (RL-DQN) techniques to optimize UAV deployment, minimizing the number of UAVs while maximizing the number of successfully collected SNs with non-redundant data. The model considers VoI and energy constraints of the SNs, enhancing both efficiency and sustainability. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…Exploratory Data Analysis (EDA) highlights the class imbalance problem in detecting fake jobs, which tends the model to act aggressively toward the minority class. …”

WiMAX Models for the Smart Grid by Al-Omar, Ban Abdul Elah

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…”

Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem by Assaker, Guy

“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. The research note is presented in two parts: Part A presents an overview of REBUS, including its development, algorithm, and its primary functions. …”
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Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

“…It was found that when solving the Mean-CVaR model with evolutionary algorithms, the risk decreased. …”

A Comprehensive Review of Digital Twin Technology in Building Energy Consumption Forecasting by Maissa Boukaf (22282279)

“…The digitalization of building energy forecasting systems, enhanced by Energy Digital Twin technology alongside IoT devices and advanced data-driven algorithms, offers substantial improvements in energy management and optimization, servicing, maintenance, and energy-efficient design. …”

Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”

A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

Hardware Model of an Expandable RSA Cryptographic System by Gutub, Adnan

“…Data security is an important aspect of information transmission and storage in an electronic form. …”
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A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)