Brain Source Localization in the Presence of Leadfield Perturbations حسب Momin, Rabiya Nakhat

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Phased Array Technique for Brain Source Localization حسب Zarghami, Tahereh

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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization حسب Abu Zitar, Raed

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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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Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

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Cyberbullying Detection Model for Arabic Text Using Deep Learning حسب Albayari, Reem

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

"…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"

PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits حسب Hind Almerekhi (7434776)

"…Therefore, in this study, we find the turning points (i.e., toxicity triggers) making conversations toxic. …"

Developing a UAE-Based Disputes Prediction Model using Machine Learning حسب Abu Laila, Ibrahim Wasef Subhi

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Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"

Correlation Clustering with Overlaps حسب Fakhereldine, Amin

"…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …"
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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey حسب Faria Nawshin (21841598)

The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

"…One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …"

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV حسب Zulkifli, Muhammad

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

"…This study not only examines the well-known challenges such as limited availability of data but provides a novel, structured taxonomy of deep learning techniques tailored for the monitoring of seagrass, highlighting their unique advantages and limitations within diverse marine environments. By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…"

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

"…A second study on larger database of credit scoring confirms these findings, showing that the online classifier achieves an F1-score of 96.40% and an accuracy of 93.08%, closely matching the performance of neural networks (96.46%, 93.22%) and boosting (96.51%, 93.31%). …"

Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach حسب Haitham Osman (11737057)

"…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. Considering optimum conditions, the system attains an exergetic efficiency of 30.13 % and a power generation of 7.24 MW, with a cost rate of 232.06 $/h and a payback period of 4.09 years. …"

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

"…In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. …"

Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces حسب Uzair Sajjad (19646296)

"…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …"

Multidimensional Gains for Stochastic Approximation حسب Saab, Samer S.

"…Necessary and sufficient conditions for M≥ N algorithms are presented pertaining to algorithm stability and convergence of the estimate error covariance matrix. …"
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