Automatic Detection of High Temperature Hydrogen Attack Defects from Ultrasonic A-scan Signals. by Yamani, Ahmed

“…To test how adequate and representative these sets of A-scan signals are, a basic feature extraction method, coupled with a primitive classifier is shown to distinguish accurately the hydrogen attack from geometrically similar defects.…”
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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization by Majdi Mansouri (16869885)

“…The main idea behind the use of the PSO algorithm is to remove irrelevant features and extract only the most significant ones from raw data in order to improve the classification task using a neural networks classifier. …”

Automatic White Blood Cell Differential Classification by Al-Muhairy, Juma A. Bin Darwish

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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. …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…Results from SAR feature extraction and geospatial analyses showed detection of the areas on the site that were already under excavation and predicted new, hitherto unexplored archaeological areas. …”
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Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system by Ali Farhat (1461478)

“…The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. …”

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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Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …”

Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben-Romdhane, Haïfa

“…Results from SAR feature extraction and geospatial analyses showed detection of the areas on the site that were already under excavation and predicted new, hitherto unexplored archaeological areas. …”
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Arabic Hotel Reviews Sentiment Analysis Using Deep Learning by ALMANSOORI, MOHAMMAD

“…Our models utilized advanced text preprocessing, feature extraction, and classification algorithms to accurately predict sentiment polarity in Arabic hotel reviews. …”
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Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

“…However, the original edRVFL is not designed for online learning, and the randomized nature of the features is harmful to extracting meaningful temporal features. …”

Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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A Navigation and Control System for a Robot in Indoor/Outdoor Environments by Al Khatib, Ehab

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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …”
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Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik, Rafikiran

“…Fuel cell-based power generation is the most utilized renewable energy source in the automotive industry because of its features clean energy, and less environmental pollution. …”
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Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik Rafikiran (15838929)

“…<p>Fuel cell-based power generation is the most utilized renewable energy source in the automotive industry because of its features clean energy, and less environmental pollution. …”

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.…”

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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