Machine learning approach for the classification of corn seed using hybrid features by Aqib Ali (19680145)

“…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. To build the classification models, Random forest (RF), BayesNet (BN), LogitBoost (LB), and Multilayer Perceptron (MLP) were employed using optimized multi-feature using (10-fold) cross-validation approach. …”

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems by Alimjon, Dadamuxamedov

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

“…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …”
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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

“…We then formulate the problem for UAV trajectory to minimize the maximum outage probability (OP) of directional THz links. Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”

Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

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The political economy of AI: a content analysis of ChatGPT outputs and anti-Palestinian media bias by King, Gretchen

“…Grounded in research-based teaching methods, and employing a mixed-method content and frequency analysis and comparison of ChatGPT outputs in English and Arabic, this article expands research on AI biases, algorithmic oppression and digital divides within the context of digital Orientalism and anti-Palestinianism. …”
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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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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…Mechanistically, targeted depletion of ENO1 and FDPS halted TNBC cell proliferation, colony formation, and organoid tumor growth under 3-dimensional conditions and increased cell death, suggesting their potential use as novel therapeutic targets for TNBC. Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPShigh, while ENO1high was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. …”

Developing a framework for using face recognition in transit payment transactions by HABEH, ORABI MOHAMMAD ABDULLAH

“…A number of combined algorithms and classifiers are proposed to use in this solution based on the encouraging outcomes observed from the systematic literature review and experts’ survey, including Local Binary Pattern descriptor, Haar-Like Descriptor, Ada Boost, Cascade classifiers, Affine Transformation, Histogram Equalization, Gaussian Filter, Principal Component Analysis which are embedded in OpenCV or MATLAB application. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

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

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer by Andrea Remo (447375)

“…Pathway enrichment analysis was used to characterize predicted targets of candidate genes. …”

A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19 by Hibah Shaath (5599658)

“…Herein, we employed iterative clustering and guide-gene selection 2 (ICGS2) as well as uniform manifold approximation and projection (UMAP) dimensionality reduction computational algorithms to decipher the complex immune and cellular composition of BAL, using publicly available datasets from a total of 68,873 single cells derived from two healthy subjects, three patients with mild COVID-19, and five patients with severe COVID-19. …”

The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques by DOULEH, HANI ABDULLAH YOSEF ABU

“…In healthcare world, data science is one of the most important sciences that helps in predicting diseases, and despite the availability of medical data from laboratory tests, most medical institutions in middle east region still do not benefit from these data in diseases analysis and prediction. 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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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)