Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples by unknown

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

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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by 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. The study results show that Random Forest outperformed all other tested algorithms. …”

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”

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

“…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”

Recent Advances of Chimp Optimization Algorithm: Variants and Applications by Daoud, Mohammad Sh.

“…The applications belong to the domains of economics, image processing, engineering, neural network, power and energy, networks, etc. …”
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

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A genetic algorithm for testable data path synthesis by Harmanani, H.

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A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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Data reductions and combinatorial bounds for improved approximation algorithms by Abu-Khzam, Faisal N.

“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
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Distributed dimension reduction algorithms for widely dispersed data by Abu-Khzam, F.N.

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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review by Chakraborty, Sanjoy

“…It also summarizes the problems solved in image processing by DE and its variants.…”
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A comparative study of replacement algorithms used in the scalable asynchronous cache consistency scheme by Haraty, Ramzi A.

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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by 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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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. …”

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

“…The flags pertaining to 16x16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. …”
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Data damage assessment and recovery algorithm from malicious attacks in healthcare data sharing systems by Haraty, Ramzi A.

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

Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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