Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”

A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…This study aims to bridge this gap by comprehensively reviewing ML concepts, approach, and algorithms in the <u>membrane separation</u> sector. …”

Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques by Amith Khandakar (14151981)

“…Classical machine learning algorithms with feature engineering and the convolutional neural network (CNN) with image enhancement techniques were extensively investigated to identify the best performing network for classifying thermograms. …”

Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation by Maymouna Ez Eddin (21633650)

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

“…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”

A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications by Danya A. Saifaldeen (19498705)

“…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. …”

Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

“…Our study also reveals that ensemble machine learning algorithms are more reliable and outperform standard algorithms.…”
Get full text

An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network by Tawfik Beghriche (19563184)

“…A performance comparison between the DNN algorithm and some well‐known machine learning techniques as well as the state‐of‐the‐art methods is presented. …”

A machine learning model for early detection of diabetic foot using thermogram images by Amith Khandakar (14151981)

“…We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. …”

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by 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. …”

ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification by Md. Iqbal Hossain (723299)

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…A spamicity score was awarded to each of the IoT devices by the algorithm, based on the feature importance and the root mean square error score of the machine learning models to determine the trustworthiness of the device in the home network. …”

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

Get full text

Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System by B. Rouabah (17947820)

“…Meanwhile, the serial connection and redundant topology of multicellular converters render the system more vulnerable to failure. fault diagnosis-based machine learning approach and fault tolerant control (FTC) are proposed for multicellular power converters. …”

Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties by AbdulGhafour, Husaen

Get full text

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

“…<p dir="ltr">The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). …”

Adaptive Federated Learning Architecture To Mitigate Non-IID Through Multi-Objective GA-Based Efficient Client Selection by Ajaj, Mohamad

Get full text
Get full text
Get full text

DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

“…Therefore, we proposed a Deep Reinforcement Learning (DRL) solution based on Deep Deterministic Policy Gradient (DDPG) algorithm to solve the highly complex SC problem by adjusting the BF weights and mirror orientations. …”