[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117409-en":3,"doc-seo-117409-105":30,"detail-sidebar-cat-0-en-105":91},{"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},117409,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine learning for ultraviolet spectral prediction - 2023 - dissertation","Machine learning has broad impact in material science, spanning dielectric polymers, superconducting materials, and drug property prediction. Data-driven methods are increasingly used to forecast Vacuum Ultraviolet (VUV) spectra by encoding molecular structure, reducing reliance on expensive wet-lab measurements. This dissertation investigates feature representations for molecular structure that improve VUV spectral prediction performance. The study compares interpretable machine learning approaches with deep learning models, aiming for accurate predictions and practical insight into molecular-structure–spectra relationships.","University of Texas at Arlington  \nMavMatrix  \n\n| Industrial, Manufacturing, and Systems Engineering Dissertations | Industrial, Manufacturing, and Systems Engineering Department |\n| --- | --- |\n| 2023\u003Cbr>Machine learning for ultraviolet spectral prediction Linh Ho Manh\u003Cbr>Follow this and additional works at: [https://mavmatrix.uta.edu/industrialmanusys_dissertations](https://mavmatrix.uta.edu/industrialmanusys_dissertations)[ ](https://mavmatrix.uta.edu/industrialmanusys_dissertations) Part of the Operations Research, Systems Engineering and Industrial Engineering Commons |  |\n\nRecommended Citation  \nHo Manh, Linh, \"Machine learning for ultraviolet spectral prediction\" (2023) . Industrial, Manufacturing, and Systems Engineering Dissertations. 143.  \n[https://mavmatrix.uta.edu/industrialmanusys_dissertations/143](https://mavmatrix.uta.edu/industrialmanusys_dissertations/143)  \nThis Dissertation is brought to you for free and open access by the Industrial, Manufacturing, and Systems Engineering Department at MavMatrix. It has been accepted for inclusion in Industrial, Manufacturing, and Systems Engineering Dissertations by an authorized administrator of MavMatrix. For more information, please contact [leah.mccurdy@uta.edu](leah.mccurdy@uta.edu), [erica.rousseau@uta.edu](erica.rousseau@uta.edu), [vanessa.garrett@uta.edu](vanessa.garrett@uta.edu).  \nMACHINE LEARNING FOR ULTRAVIOLET SPECTRAL PREDICTION  \nby  \nLINH HO MANH  \nPresented to the Faculty of the Graduate School of The University of Texas at Arlington in Partial Fulfillment of the Requirements  \nfor the Degree of  \nDOCTOR OF PHILOSOPHY  \nTHE UNIVERSITY OF TEXAS AT ARLINGTON  \nMay 2023  \nCopyright © by Linh Ho Manh 2023 All Rights Reserved  \nTo my father Lam Ho and my mother Bac Nguyen Minh who set the example and made me who I am.  \nACKNOWLEDGEMENTS  \nI would like to thank my supervising professor Dr. Victoria Chen for constantly motivating and encouraging me and for her invaluable advice during the course of my doctoral studies. In particular, Dr. Chen encouraged me to think critically about the practical aspects of my research, including interpretability vs. more popular complex approaches.  \nI would also like to thank my dissertation committee members, Dr. Kevin Schug, Dr. Jay Rosenberger, and Dr. Bill Corley, for their support of my research and for taking their precious time to review my thesis and provide thoughtful comments. I wish to give a special thanks to Dr. Kevin Schug. He officially served as one of my dissertation committee members, but in many ways, he was a supervising professor. He proposed my dissertation topic and has provided continual guidance on all things chemistry-related.  \nI would like to acknowledge National Science Foundation grant CHEM-2108767 for providing financial support for my doctoral studies. I especially want to thank Dr. Kevin Schug, his colleagues, and VUV Analytics company for their interest in my research, their helpful discussions, and their patience in explaining chemical intuition to me. Their input allowed me to incorporate those ideas into machine learning models and achieve several interpretable results.  \nI am thankful to Dr. Shouyi Wang and Dr. Yi Zhang at the University of Texas at Arlington and Dr. Huihui Zhang at the United States Department of Agriculture for their support and encouragement. Through working on projects with them, I have improved my machine learning knowledge and programming ability. I would  \nlike to thank Dr. Bill Corley, Dr. Jay Rosenberger, and Dr. Aera LeBoulluec for their engaging instruction in my courses, and I would like to thank all academic and technical staff in the Department of Industrial, Manufacturing, & Systems Engineering, especially Ms. Ann Hoang, Mr. Richard Zercher, and Ms. Cindy Royster for their support from my first day here.  \nI would like to thank all the teachers who taught me during the years I spent in school, first in Vietnam, then in Italy, and finally in the United States","cbCaivwT4Ubvk3wz","https://ap.wps.com/l/cbCaivwT4Ubvk3wz","pdf",3207212,1,124,"English","en",105,"# Abstract\n## Chapter 1: Overview of VUV/UV spectra retrieval\n## Chapter 2: Review of machine learning models and conventional molecular techniques\n## Chapter 3: Main contribution and new feature representations","[{\"question\":\"What problem does the dissertation address?\",\"answer\":\"It studies how to predict Vacuum Ultraviolet (VUV) spectra using machine learning by encoding molecular structure, reducing the need for costly wet-lab experiments.\"},{\"question\":\"What main research goal is targeted?\",\"answer\":\"To develop feature representations of molecular structure that enhance prediction accuracy for VUV spectra.\"},{\"question\":\"Which modeling approaches are compared?\",\"answer\":\"Both interpretable machine learning methods and deep learning models are examined to evaluate their predictive capability and usefulness.\"}]","Machine learning for ultraviolet spectral prediction - 2023 - dissertation | PDF",1785675718,312,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-for-ultraviolet-spectral-prediction-2023-dissertation","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-for-ultraviolet-spectral-prediction-2023-dissertation/117409/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the dissertation address?","Question",{"text":75,"@type":76},"It studies how to predict Vacuum Ultraviolet (VUV) spectra using machine learning by encoding molecular structure, reducing the need for costly wet-lab experiments.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What main research goal is targeted?",{"text":80,"@type":76},"To develop feature representations of molecular structure that enhance prediction accuracy for VUV spectra.",{"name":82,"@type":73,"acceptedAnswer":83},"Which modeling approaches are compared?",{"text":84,"@type":76},"Both interpretable machine learning methods and deep learning models are examined to evaluate their predictive capability and usefulness.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]