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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.…”
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation
Published 2000“…Therefore, the second proposal suggests a standard compliance implementation with mixed 32116-bit precision and rounding. …”
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A review article on software effort estimation in agile methodology
Published 2021“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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A review article on software effort estimation in agile methodology
Published 2021“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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Artificial neural network (ANN) as post-processing stage for chemically selective field effect transistor (CHEMFET) sensor selectivity based-on ion concentration / Nurhakimah Abd A...
Published 2016“…Other than developing supervised learning, this study also was focusing on exploration of unsupervised learning mainly in blind source separation (BSS) algorithm to separate the interface signal. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Application of machine learning and artificial intelligence in detecting SQL injection attacks
Published 2024“…The main aim of this work is focusing on solving the IT-related challenge lack-of-adequate knowledge bases and tools for security practitioners to monitor and mitigate SQL Injection attacks with AI/ML techniques. The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Artificial Intelligence as A Common Heritage of Mankind
Published 2023“…Artificial intelligence technologies today employ techniques known as machine learning and deep learning, which apply datasets to a suitable mathematical or statistical technique known as an algorithm. …”
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School
Published 2021“…The study aims to identify the effective pedagogical approaches in learning Computational Thinking skills and address the needs and challenges faced in implementing Computational Thinking in a rural primary school in Sarawak. …”
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Digital media-enhanced cultural brand development: creative strategies for urban identity construction
Published 2025“…This study investigates digital media-enhanced cultural brand development through creative strategies for urban identity construction, aiming to develop a comprehensive framework that extends integrated marketing communication theory while preserving cultural authenticity and enabling community participation. A mixed-methods approach incorporated stakeholder surveys (n=420) across four participant groups, systematic analysis of 800 social media posts, examination of 35 institutional platforms, and comparative analysis of 12 international cities, utilizing an AI-enhanced analytical pipeline with natural language processing, computer vision, and machine learning algorithms. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2021“…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2021“…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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