A comparative study of replacement algorithms used in the scalable asynchronous cache consistency scheme حسب Haraty, Ramzi A.

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Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems حسب Shehabeldin, Menatalla Diaaeldin

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AI-based remaining useful life prediction and modelling of seawater desalination membranes حسب Al Ali, Fajer

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Cortical EEG Source Localization of Focal Epilepsy حسب Siyam, Wisal Elfatih Mohamed

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

"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …"

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

الموضوعات: "…Model Based Testing…"
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Data damage assessment and recovery algorithm from malicious attacks in healthcare data sharing systems حسب Haraty, Ramzi A.

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Public health utility of cause of death data: applying empirical algorithms to improve data quality حسب Sarah Charlotte Johnson (9715415)

A Parallel Neural Networks Algorithm for the Clique Partitioning Problem حسب Harmanani, Haidar M.

"…Our model uses a large number of simple processing elements or neurons, based on the McCulloch-Pitts binary neuron. …"
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A Hash-Based Assessment and Recovery Algorithm for Distributed Healthcare Systems Using Blockchain Technology حسب Jaber, Mohammad

"…Numerous damage assessment and recovery algorithms have been proposed in the literature. In this work, we present a distributed algorithm that uses blockchain technology and hash tables to solve the information warfare problem in healthcare systems. …"
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm حسب Nasser, Youssef

"…Hundreds of such labeled graphs were used to train the model to predict the location of centroids. …"
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques حسب Abdul Karim (417009)

"…This conclusion was achieved after preprocessing a number of data values from these data sets.</p><h2>Other Information</h2><p dir="ltr">Published in: Algorithms<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/a13080202" target="_blank">https://dx.doi.org/10.3390/a13080202</a></p>…"

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System حسب Ameema Zainab (16864263)

Damage assessment & recovery from malicious transactions using data dependency for deffensive information warfare. (c2006) حسب Zeitunlian, Arda

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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing حسب Al Sadawi, Alia

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Fault-Tolerant Network Topologies for Datacenters حسب Attia, Heba Mahmoud Helal

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Web Based Online Hybrid Teaching Method of Network Music Course حسب Abu Zitar, Raed

"…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …"
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers حسب Mansour, Nashat

"…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …"
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General applicability of genetic and simulated annealing algorithms for data mapping حسب Mansour, Nashat

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Correlation Clustering via s-Club Cluster Edge Deletion حسب 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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