Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy حسب Haitao Xu (435549)

"…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …"

Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar حسب Sankaran, Rajendran

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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization حسب Yassine Himeur (14158821)

"…DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …"

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations حسب Md Mosarrof Hossen (21399056)

"…To address this challenge, this study aims to optimize household energy consumption while preserving data privacy by proposing an innovative two-stage Federated Learning (FL) framework that delivers real-time micro-moment-based recommendations. …"

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …"

Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …"

The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis حسب Ghada Al-Hussain (18295426)

"…Both methods have limited standardized tests, which are affected by the clinician’s experience and subjective judgment. Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. …"

Large-scale annotation dataset for fetal head biometry in ultrasound images حسب Mahmood Alzubaidi (15740693)

"…Its detailed annotations, broad compatibility, and ethical compliance make it a highly reusable and adaptable tool for the development of algorithms aimed at improving maternal and Fetal health.…"

A Deployment Optimization Model for Wimax Base-Stations حسب Aboualmal, Abdulhadi Mahmoud

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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network حسب KHAN, FIROZ

"…The data is finally classified as either ransomware or goodware using the learning methodologies. …"
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Severity-Based Prioritized Processing of Packets with Application in VANETs حسب Ala Al-Fuqaha (4434340)

"…In this study, we propose a generic prioritization and resource management algorithm that can be used to prioritize processing of received packets in vehicular networks. …"

Improving Rule Set Based Software Quality Prediction حسب Azar, Danielle

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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper حسب Mutaz I. Othman (21186827)

"…<h3>Background</h3><p dir="ltr">Machine learning (ML) models can enhance patient–nurse assignments in healthcare organisations by learning from real data and identifying key capabilities. …"

Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis حسب Navadon Khunlertgit (3480926)

"…<p>Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. …"

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends حسب Abdellatif M. Sadeq (16931841)

"…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …"

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks حسب Haris M. Khalid (17017743)

"…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …"

Neural network-based decision feedback equaliser with latticestructure حسب Shafi, A.

"…It is shown from computer simulations that whitening of the received data employing adaptive lattice channel equalisation algorithms improves the convergence rate and bit error rate performances of multilayer perceptron-based DFEs…"
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Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura, Habiba

"…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …"
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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features حسب Mariam Bahameish (19255789)

"…<p dir="ltr">Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. …"