Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

“…In the first stage, we performed binary classification, grouping SAH severity into “Good Outcome” (class 0), which includes MRS levels 0, 1, 2, and 3, and “Poor Outcome” (class 1), encompassing levels 4, 5, and 6. Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

“…Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”

The Green Sleepers of Tehran Park Bench Semiotics by Hosseinnia, Maryam

“…Therefore, eight-dimensional feature space has been developed. Finally, K-mean clustering algorithm has been implemented based on the extracted features of PD pulse shape and PD current waveform to define their clusters in the feature space. …”
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Separation of Partial Discharge Faults in Metal-clad Switchgear Based on Pulse Shape Analysis by Hussain, Ghulam

“…Therefore, eight-dimensional feature space has been developed. Finally, K-mean clustering algorithm has been implemented based on the extracted features of PD pulse shape and PD current waveform to define their clusters in the feature space. …”
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Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”

Semi-supervised Clustering of Facial Expressions by Jalal, Ahsan

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Performance Prediction Using Classification by MOOLIYIL, GITA

“…Principal component analysis and feature selection by weights using information gain ratio, Gini index, correlation and PCA is used to determine the relevant predictors of the datasets used. …”
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Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Kolmogorov–Arnold Networks for predicting carotid intima-media thickness in cardiovascular risk assessment by Al Bataineh, Ali

“…After a five-stage pre-processing pipeline median/mode imputation, categorical encoding, Min–Max scaling, inter-quartile-range outlier removal and SMOTE-NC balancing we trained a Kolmogorov–Arnold Network (KAN) to assign each patient to one of four CIMT-defined risk tiers mentioned as “No”, “Low”, “Medium”, “High”. Feature-selection tests (Spearman, Pearson, ANOVA and ?…”
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Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

“…PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. …”

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…Due to the complexity of Arabic poetry such as the excessive use of metaphors, figurative language, unlimited imagination, and the diversity of styles from one poet to another and from one poem to another, we tackle these challenges by careful employment of preprocessing steps, feature engineering and selection. We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …”
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Data visualization and pattern discovery in IoT by Bektemirov, Abdukhamid

“…The given method is a combination of nonlinear optimization of features with the help of metaheuristic algorithms and sophisticated dimensionality reduction techniques to preserve the important information with reducing redundancy. …”
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Robust Histogram Signature-Driven Template Matching for Vehicle Tracking in Traffic Videos by Rababaah, Aaron Rasheed

“…Correlation-based template matching (CTM) is widely used for object detection because of its simplicity and effectiveness in scenarios where grayscale features are sufficient. …”
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Social Network Analysis for Precise Friend Suggestion for Twitter by Associating Multiple Networks Using ML by Dharmendra Kumar Singh Singh (19517710)

“…<p dir="ltr">The main aim in this paper is to create a friend suggestion algorithm that can be used to recommend new friends to a user on Twitter when their existing friends and other details are given. …”

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…Statistical analysis showed that the selected features for liquids' and pipe's properties using the BGWOPSO algorithm were adequate to attain superior performance for both models. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Energy-Aware Physical Synthesis of Deep Neural Networks for Edge-AI Applications in Robotics and VLSI Systems by Arulprakash, Enoch

“…This work presents a unified framework that co-optimizes DNN architectural features (including quantization, sparsity, and operator tiling) with physical design choices, such as multi-Vt selection, sizing, placement strategies, activity-driven buffering, and CTS. …”
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Nu—A Marine Life Monitoring and Exploration Submarine System by AlGohary, Abdullah

“…Nu’s functionality was evaluated in a controlled 2.5-m-deep body of water, focusing on connectivity, maneuverability, and fish identification accuracy. The fish detection algorithm achieved an average precision of 60% in identifying fish presence, while the classification model achieved 97% precision in assigning species labels, with unknown species flagged correctly. …”
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Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review by Yasir Ali (799969)

“…In RQ2, we highlighted and discussed the contributions of ANNs approaches for individual security requirement/feature in comprehensive and detailed fashion. In this question, we also determined the various models, frameworks, techniques and algorithms suggested by ANNs for the security advancements of IoT. …”

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

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