[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120128-en":3,"doc-seo-120128-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120128,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","The Potential of Machine Learning in Computer Aided Geometric Design - Siti Sarah Raseli and Assoc. Pr.","The work presents the potential of machine learning as a branch of artificial intelligence for extracting information from data and improving performance through experience. It highlights how machine learning techniques can enhance efficiency, accuracy, and productivity in computer aided geometric design. Examples include genetic-algorithm-based parameterization for non-uniform B-spline curve construction, machine-learning-supported facial expression recognition using Bezier curves, and extreme machine learning for improved nonlinear curve fitting and parameterization.","Phone: +603-5544 2004 | E-mail: [tncpi@uitm.edu.my | Web:](tncpi@uitm.edu.my | Web:) [https://tncpi.uitm.edu.my/](https://tncpi.uitm.edu.my/)  \nFacebook: tncpi. uitm | Youtube: TNCPI UiTM  \nInstagram: tncpi_uitm | Twitter: tncpi_uitm  \nADMINISTRATION  \nPROF. TS. DR NORAZAH ABD RAHMAN  \nDeputy Vice-Chancellor (Research & Innovation) Office of Deputy Vice-Chancellor (Research & Innovation)  \n[noraz695@uitm.edu.my](noraz695@uitm.edu.my)[ ](noraz695@uitm.edu.my)+603 – 5544 2004  \nASSOC. PROF. DR MOHD MUZAMIR MAHAT  \nHead of Research Communication & Visibility Unit (UKPV) [mmuzamir@uitm.edu.my](mmuzamir@uitm.edu.my)  \n+603 – 5544 3097  \nABOUT THE MAGAZINE  \nRISE Magazine is published by Office of the Deputy Vice-Chancellor (Research and Innovation) with aims to highlight a research and innovation on multidisciplinary expert of fields in UiTM. It serves as a platform for researcher to showcase their high quality and impactful findings, activities and innovative solution through publication. Contribution of these ideas come from academicians, researchers, graduates and universities professionals who will enhance the visibility of research and stride to elevate Universiti Teknologi MARA to global standards. This is an effort to promote research as a culture that is accepted by all expertise.  \nABOUT UiTM  \nUniversiti Teknologi MARA (UiTM) is a public university based primarily in Shah Alam , Malaysia. It has grown into the largest institution of higher education in Malaysia as measured by physical infrastructure, faculty and staff, and student enrollment. UiTM is the largest public university in Malaysia with numerous campuses throughout all 13 states in Malaysia. There is a mixture of research, coursework and programmes offered to the students. The Office of the Deputy Vice-Chancellor (Research and Innovation) also known as PTNCPI (Pejabat Timbalan Naib Canselor (Penyelidikan dan Inovasi)) serves as a Pusat Tanggungjawab (PTJ) for navigating the research and innovation agenda of the university to achieve UiTM’s goals.The PTNCPI office strives to mobilize faculty and campuses, fostering collaboration among researchers, with the aim of transforming the University into a Globally Renowned University by 2025  \nThe Potential of  \nMachine Learning in  \nCOMPUTER AIDED  \nGEOMETRIC  \nDESIGN  \nrtificial Intelligence (AI) is a leading technology that is capable of simulating human intelligence and decision making (Song et al. , 2022) . Artificial intelligence is an advanced  \ntechnology that is widely applied in various fields such as mathematics, statistics, and computer science across a wide range of industries.  \nMachine learning is a part of AI that enables the extraction of information from data to improve its ability by studying from experience (Bertolini [et.al](et.al), 2021) . Machine learning is the development of computational algorithms that aim to imitate human intelligence through environmental education (El Naqa & Murphy, 2015) .  \nMachine learning is a generally accepted application that can be applied in various studies. The techniques proposed from machine learning are widely used to solve problems that arise in many fields and industries. In addition, machine learning applications can improve efficiency, accuracy and increase performance and productivity.  \nA  \n87  \nVarious special features of machine learning have attracted researchers to make use of the technology in their research field, including in computer aided geometric design. For instance, [Kumar et.al](Kumar et.al), (2003) proposed a parameterization model with genetic algorithms to improve the accuracy of the curve construction. The construction of non-uniform Bspline curve is implemented by using parameterization from genetic algorithm. The parameterization is based on the primary parameterization. The parameter is optimized, and the knot values are optimized by using iterative optimization procedures from the available solution in genetic algorithm.  \nIn addition","cbCailsVoSpZfTQ8","https://ap.wps.com/l/cbCailsVoSpZfTQ8","pdf",5606151,1,4,"English","en",105,"# About the magazine\n## UiTM and PTNCPI background\n# The potential of machine learning in computer aided geometric design\n## Core concepts: AI and machine learning\n## Applications and studies\n## Conclusions","[{\"question\":\"How does the document describe the relationship between AI and machine learning?\",\"answer\":\"Machine learning is presented as a part of AI that learns from data to improve capability. It uses computational algorithms to imitate human intelligence in decision making and problem solving.\"},{\"question\":\"What role does machine learning play in computer aided geometric design?\",\"answer\":\"It is described as an advanced approach that supports solving geometric design problems with improved efficiency and result quality. The document emphasizes its significant potential based on prior studies.\"},{\"question\":\"What example methods are used to improve curve construction and fitting?\",\"answer\":\"Genetic algorithms are used for parameterization to optimize knot values and curve construction for non-uniform B-splines. Extreme machine learning is also used for training a network to address nonlinear curve fitting problems.\"}]","The Potential of Machine Learning in Computer Aided Geometric Design - Siti Sarah Raseli and Assoc. 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It uses computational algorithms to imitate human intelligence in decision making and problem solving.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What role does machine learning play in computer aided geometric design?",{"text":79,"@type":75},"It is described as an advanced approach that supports solving geometric design problems with improved efficiency and result quality. The document emphasizes its significant potential based on prior studies.",{"name":81,"@type":72,"acceptedAnswer":82},"What example methods are used to improve curve construction and fitting?",{"text":83,"@type":75},"Genetic algorithms are used for parameterization to optimize knot values and curve construction for non-uniform B-splines. 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