Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

“…One of the well-known designs of RDH is the difference expansion (DE) method. In the DE-based RDH method, finding spaces that create less distortion in the marked image is a significant challenge, and has a high insertion capacity. …”
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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. …”
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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models by Asan G. A. Muthalif (16888818)

Arithmetic optimization algorithm: a review and analysis by Abualigah, Laith

“…A metaheuristic algorithm called arithmetic optimization algorithm (AOA) is developed to solve various optimization problems. …”
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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar by Sankaran, Rajendran

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A matrix-based damage assessment and recovery algorithm by Haraty, Ramzi A.

“…In this work we present efficient damage assessment and recovery algorithms to recover from malicious transactions in a database based on the concept of the matrix. …”
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A comparative study of five regression testing algorithms by Mansour, N.

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An explicit finite-difference scheme for wave propagation in nonlinear optical structures by Al-Sunaidi, M. A.

“…In this paper, we present an algorithm that solves a time-domain nonlinear coupled system arising in nonlinear optics. …”

How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

“…We found researchers employing 46 different algorithms and 14 different evaluation metrics. …”

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

“…<h3>Background</h3><p dir="ltr">Restriction site analysis involves determining the locations of restriction sites after the process of digestion by reconstructing their positions based on the lengths of the cut DNA. Using different reaction times with a single enzyme to cut DNA is a technique known as a partial digestion. …”

A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality by KARAM, ZAINAB HAMDAN

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Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem by Abido, M. A.

“…In addition, the results demonstrate the superiority of the SPEA as a promising multiobjective evolutionary algorithm to solve different power system multiobjective optimization problems.…”
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Multiobjective evolutionary algorithms for electric power dispatch problem by Abido, M.A.

“…In addition, the results demonstrate the superiority of the SPEA as a promising multiobjective evolutionary algorithm to solve different power system multiobjective optimization problems.…”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…Distributed clustering algorithms, however, can fulfil this gap. They extract a classification model from the distributed objects even when they are in different sites and locations. …”
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A Modular Reconfigurable Architecture for Asymmetric and Symmetric-key Cryptographic Algorithms by Zaidi, Ali Mustafa

“…Numerous such algorithms have been devised, and many have found popularity in different domains. …”
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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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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

“…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”