A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…The preprocessing of data includes remove missing value records and remove columns that have a negligible impact. The feature selection uses Grey Wolf Optimisation and Binary Search algorithms for choosing the best features out of the dataset. …”
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

“…However, NNGE algorithm tends to produce rules that test a large number of input features. …”

Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements by Katicha, Samer W.

“…The algorithm minimizes the classification error of features in the wavelet transform domain by adaptively selecting the level at which to control the false discovery rate. …”
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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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The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The most prominent ML algorithm was a support vector machine, and the DL algorithm was a convolutional neural network. …”

A Multi-Channel Convolutional Neural Network approach to automate the citation screening process by Raymon van Dinter (10521952)

“…The citation screening process aims to identify the relevant primary studies fairly and with high rigor using selection criteria. Through the study selection criteria, reviewers determine whether an article should be included or excluded from the SLR. …”

Analysis of the Performance Impact of Fine-Tuned Machine Learning Model for Phishing URL Detection by Abdul Samad, Saleem Raja

“…The result demonstrates that data balance improves accuracy marginally, whereas hyperparameter adjustment and feature selection improve accuracy significantly. …”
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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. …”

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. …”

Perceived Information Assurance in Conversational Systems by Alghannam, Bareeq

“…Feature selection demonstrated that comparable performance (96.76% accuracy) could be maintained with only 19 optimally selected features, representing an 83.8% reduction in model complexity. …”
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Regression Testing of Database Applications by Haraty, Ramzi A.

“…In phase 2, further reduction in the regression test cases is performed by using reduction algorithms. We present two such algorithms. The Graph Walk algorithm walks through the control flow graph of database modules and selects a safe set of test cases to retest. …”
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…A 2-stage process was followed for study selection: reading abstracts and titles followed by full-text screening. …”

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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Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

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

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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review by Alaa Abd-alrazaq (17058018)

“…The most commonly used algorithm was random forest, followed by support vector machine.…”

A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques by SALLOUM, SAID

“…The findings include that the main research area in phishing detection studies is feature extraction and selection, followed by methods for classifying and optimizing the detection of phishing emails. …”
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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. …”