Search Results - (( developing human prioritization algorithm ) OR ( java implication based algorithm ))

A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Towards a unified image quality assessment technique for cross-content image processing applications by Baqar, Mohtashim *

“…Additionally, these methods often don’t consider visual perception, even though human vision is crucial in most applications. The study aims to develop methods for reconstructing distorted images while prioritizing visually important areas. …”
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From Jurisprudence to Algorithms: The Role of Artificial Intelligence in Contemporary Sharia Financial Decision-Making by Edi Mulyono, Mahmoud Mohamed Ali Mahmoud Edris

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Flood management system: geo based information and monitoring module by Lim, Soo Yi

“…Moreover, FloodGuard employs an innovative approach to human-scale water level measurement wherein users input their height and mark the water level on their body to generate more accurate flood depth data. …”
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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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A Hybrid Machine Learning and Optimisation-Based Model for Predicting the Success of Business-To-Consumer Software Development Projects in Indonesia by Setiawan, Rudi

“…Building on these findings, a predictive framework is constructed by integrating machine learning algorithms with advanced optimization and data handling strategies. …”
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