Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …”
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…The feature selection uses Grey Wolf Optimisation and Binary Search algorithms for choosing the best features out of the dataset. …”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. …”

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by 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. …”

On the exact recovery of the FFT of noisy signals using a non-subtractively dither-quantized input channel by 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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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by 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. …”

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

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

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

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by 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. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…It was tested using historical data, and the next step will to involve usability testing with end users.…”

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by 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. …”

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

“…The evaluation of testing methods has been conceptualized as a regression task in which neural networks are supervised using a variety of parameters such as variations between input and output, number of iterations, and P-box generation patterns. …”

A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by 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. …”

Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by 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. …”

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”

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

“…</p><h3>Conclusions</h3><p dir="ltr">Though theoretically d′ values should be calculated using raw images, clinical images can be also used, at least for constancy tests.…”

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by 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. …”

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

“…All the eleven deep CNN models are trained and tested using a single-channel benchmark EEG dataset containing 23 sets of motion-corrupted and reference ground truth EEG signals from PhysioNet. …”

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…The accuracy of the proposed modeling is tested on a 1,000-transformer substation subset of the Spanish distribution electrical network data containing more than 24 million load records. …”