A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai حسب ALGHANEM, HANI SUBHI MOHD

"…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …"
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Identifying Regional Trends in Avatar Customization حسب Peter Mawhorter (18602944)

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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A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model حسب Md. Nazmul Islam Shuzan (16888827)

"…Gaussian Process Regression (GPR) with Fit a Gaussian process regression model (Fitrgp) feature selection algorithm outperformed all other combinations and exhibits a root mean squared error (RMSE), mean absolute error (MAE), and two-standard deviation (2SD) of 2.63, 1.97, and 5.25 breaths per minute, respectively. …"

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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Virtual topologies for massively parallel computations. (c2015) حسب Jahed, Karim A.

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

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A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization حسب Yamout, Youssef

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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)

Multi-Objective Task Allocation Via Multi-Agent Coalition Formation حسب Amer, Noha Tarek

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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.…"