Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines by Haddad, Abdul Rahim

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Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines by Saleh, Ayat

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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …”

Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. …”
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

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

“…The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. …”

Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

“…The proposed algorithm (Ls-AOA) was tested against unimodal and multimodal benchmark functions and demonstrated better capability comparatively using other efficient metaheuristic algorithms reported in the literature. …”

Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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