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

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Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique حسب Iqbal Hassan (22155274)

"…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). The primary objective of this study is to estimate the CL index through an innovative approach that employs a hybrid, cluster-based, unsupervised learning technique seamlessly integrated with a 1D Convolutional Neural Network (CNN) architecture tailored for automated feature extraction, rather than conventional supervised algorithms, which facilitated in the acquisition of latent complex patterns without the need for manual categorization. …"

Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine حسب Debendra Muduli (20748758)

"…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …"

On the exact recovery of the FFT of noisy signals using a non-subtractively dither-quantized input channel حسب Cheded, L.

"…This paper proposes a new theory that resolves this conflict for any quantization resolution used. This theory, tested with a 1-bit quantization scheme and under very noisy environments is very well supported by our simulation results. …"
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Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control حسب Farhat Mahmood (15468854)

"…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …"

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach حسب Muhammad Adeel Asghar (6724982)

"…A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. …"

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network حسب Monzure-Khoda Kazi (17191207)

"…Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …"

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features حسب Mariam Bahameish (19255789)

"…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …"

Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review حسب Rehaan Hussain (22302742)

"…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …"

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE حسب SHWEDEH, FATEN

"…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …"
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

"…To evaluate the generalizability of the algorithms, the agents are tested across various velocities, tire–road friction coefficients, and additional scenarios implemented in IPG CarMaker, a high-fidelity vehicle dynamics simulator. …"

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition حسب Hanif Heidari (22467148)

"…Using three statistical measures Lyapunov exponents (LE), Correlation Dimension (CD), and approximate entropy (AE), we evaluated the performance of machine learning algorithms over different data lengths. …"

Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan حسب AL RAWASHDEH, HANEEN MOHAMMAD

"…Different classification algorithms were applied to the dataset using the Rapidminer tool. …"
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Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier حسب Yassine Himeur (14158821)

"…An accuracy of up to 99.65% and 98.51% has been achieved on GREEND and UK-DALE data sets, respectively. While an accuracy of more than 96% has been attained on both WHITED and PLAID data sets. …"

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment حسب Zakaria Tolba (16904718)

"…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"

Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier حسب Abhishek Raj (7245425)

"…<p dir="ltr">This article presents a wavelet analysis-singular value decomposition (WA-SVD) based method for precise fault localization in recent power distribution networks using k-NN Classifier. The WA-SVD leverages the slime mould algorithm (SMA) and graph theory (GT) in enhancing the overall accuracy of fault localization. …"

Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems حسب Majdi Mansouri (16869885)

"…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …"

A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance حسب Krishnamoorthy Natarajan (22047464)

"…Chest X-rays, MRI scans, CT scans, and skin lesions are used to diagnose the mentioned diseases. Transfer learning algorithms, such as VGG16, VGG19, ResNet, InceptionV3, and EfficientNetB4, are utilized to categorize various diseases. …"

Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks حسب Ioannis A. Tsalafoutas (14776939)

"…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…"

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models حسب Osama Bassam J. Rabie (21323741)

"…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. Here, the proposed DRF-DBRF security model's performance is validated and tested using five different and popular IoT benchmarking datasets. …"