Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization by Abrar, Shafayat

“…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …”
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Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks by Yaacoub, Elias

“…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …”
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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A machine learning approach for localization in cellular environments by Abdallah, Ali A.

“…A machine learning approach is developed for localization based on received signal strength (RSS) from cellular towers. …”
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Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output by Kaif Ahmed Lodi (16855518)

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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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)

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by Abhishek Raj (7245425)

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”

Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…The increase in imagery data has in turn created a demand for automated detection and classification using deep neural network-based techniques. This study reviews the current deep-learning techniques used for monitoring and classification of the seagrass. …”

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”

Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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