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

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

"…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …"

A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) حسب Wehbe, Gioia Wahib

"…Our algorithm first performs a feature selection step to define differentiable SNPs. …"
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Sentiment Mining of Arabic Twitter Data حسب Ahmed, Soha Galalaldin Khider

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Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

"…Conformance checking compares a process model and recorded executions of a process, i.e., a log of traces. …"
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Sentiment analysis for Arabizi in social media. (c2015) حسب Tobaili, Taha

"…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …"
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems حسب Wali Khan Mashwani (14590504)

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

"…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …"

Fetal ECG Signal Enhancement حسب Ahmadi, Maryam

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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE حسب SHWEDEH, FATEN

"…Educational Data Mining (EDM) is the process of discovering information and relationships from educational data for better understanding of students’ performance, and characteristics of their education providers. …"
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Load Partitioning for Matrix-Matrix Multiplication on a Cluster of CPUGPU Nodes Using the Divisible Load Paradigm حسب Elhiny, Lamees

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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. …"

Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب Ali Jassim Lari (22597940)

"…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. …"

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

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RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. حسب Sebastian Kruse (18595195)

Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب Odat, Alhaj-Saleh A.

"…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…"
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Parallel implementation of clique partitioning using artificial neural networks. (c2000) حسب Hajj, Hisham

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Parallel processing حسب Mansour, Nashat

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Sentiment visualization of correlation of loneliness mapped through social intelligence analysis حسب Hurmat Ali Shah (18192889)

"…</p><h3>Methods</h3><p dir="ltr">This study consists of two parts. In the first part, we employ NLP techniques and machine learning algorithms to extract and analyze tweets containing keywords related to loneliness. …"

Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing حسب Jincheng Zhou (1887307)

"…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …"