Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…The first is a comprehensive ML framework for the construction of diagnostic binary classification high accuracy models to predict T2DM in the United Arab Emirates based on STEPS style National Health Survey. …”
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VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Approximation and heuristic algorithms for computing backbones in asymmetric ad-hoc networks by Abu-Khzam, Faisal N.

“…We consider the problem of dominating set-based virtual backbone used for routing in asymmetric wireless ad-hoc networks. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²), were used to assess the prediction accuracy of the models. The results of the correlation matrices showed that the blueberry yield and losses (leaf loss, blower loss) had medium to strong correlations accessed based on the correlation coefficient (r) range 0.37–0.79. …”

On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”

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

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The computational cost and performance estimations are improved, and the metrics are clearly visualized on this paper based on improved beamforming procedures as well as the proposed approach of DDN based Multi-Resolution Code Book performance metrics are estimated clearly with proper mathematical model investigations. …”

Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

“…In certain situations, the requirement for clusters to be cliques was deemed excessively stringent, leading to the proposal of alternative relaxed clique models for dense subgraphs, such as s-club. In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams by Raun, Kristo

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Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle by Wadi, Ali H M

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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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A new family of multi-step quasi-Newton algorithms for unconstrained optimization by Obeid, Samir

“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

Optimizing Energy Consumption In Cloud Datacenters by Khan, Mueez Ahmad

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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …”