Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

“…We also present a technique for efficient mapping of large data sets. The algorithms include a parallel genetic algorithm (PGA), a parallel neural network algorithm (PNN) and a parallel simulated annealing algorithm (PSA). …”
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Towards Scalable Process Mining Pipelines by Mohamed, Belal

“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…This is suitable for the domain of software quality since the data is very scarce and hence predictive models built from one data set is hard to generalize and reuse on new data.…”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Hardening the ElGamal cryptosystem in the setting of the second group of units. (c2011) by Fanous, Suzan Mohamad

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An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

“…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …”
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Mining airline data for CRM strategies. (c2006) by Maalouf, Lena

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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. In this study, we used twitter as our data source. …”
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Nonlinear analysis of shell structures using image processing and machine learning by 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. …”

Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

“…The data was used as training and testing sets to analyze certain machine learning algorithms in terms of performance (cost / benefit analysis) and accuracy (mean error square and confusion matrix). …”
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

“…Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. …”
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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Fuzzy Logic Based Patients' Monitoring System by Al-Dmour, Jumana

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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

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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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Software defect prediction. (c2019) by Moussa, Rebecca

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An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm by M Baritha Begum (17541483)

Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…Several techniques have been proposed in the literature to add some semblance of balance to the data sets by adding artificial data points. Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …”