{"id":3172,"date":"2024-10-04T19:18:12","date_gmt":"2024-10-04T19:18:12","guid":{"rendered":"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172"},"modified":"2026-02-12T17:49:35","modified_gmt":"2026-02-12T17:49:35","slug":"natt-leelawat-2","status":"publish","type":"page","link":"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172&lang=en","title":{"rendered":"Natt Leelawat"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"3172\" class=\"elementor elementor-3172\" data-elementor-post-type=\"page\">\n\t\t\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-5442381 e-flex e-con-boxed e-con e-parent\" data-id=\"5442381\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2df925d elementor-widget elementor-widget-html\" data-id=\"2df925d\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t<!-- Flexy Breadcrumb -->\r\n\t\t\t<div class=\"fbc fbc-page\">\r\n\r\n\t\t\t\t<!-- Breadcrumb wrapper -->\r\n\t\t\t\t<div class=\"fbc-wrap\">\r\n\r\n\t\t\t\t\t<!-- Ordered list-->\r\n\t\t\t\t\t<ol class=\"fbc-items\" itemscope itemtype=\"https:\/\/schema.org\/BreadcrumbList\">\r\n\t\t\t\t\t\t            <li itemprop=\"itemListElement\" itemscope itemtype=\"https:\/\/schema.org\/ListItem\">\r\n                <span itemprop=\"name\">\r\n                    <!-- Home Link -->\r\n                    <a itemprop=\"item\" href=\"https:\/\/ienext.eng.chula.ac.th\">\r\n                    \r\n                                                    <i class=\"fa fa-home\" aria-hidden=\"true\"><\/i>Home                    <\/a>\r\n                <\/span>\r\n                <meta itemprop=\"position\" content=\"1\" \/><!-- Meta Position-->\r\n             <\/li><li><span class=\"fbc-separator\">\/<\/span><\/li><li class=\"active\" itemprop=\"itemListElement\" itemscope itemtype=\"https:\/\/schema.org\/ListItem\"><span itemprop=\"name\" title=\"Natt Leelawat\">Natt Leelawat<\/span><meta itemprop=\"position\" content=\"2\" \/><\/li>\t\t\t\t\t<\/ol>\r\n\t\t\t\t\t<div class=\"clearfix\"><\/div>\r\n\t\t\t\t<\/div>\r\n\t\t\t<\/div>\r\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-76dc323 e-flex e-con-boxed e-con e-parent\" data-id=\"76dc323\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-492e764 e-con-full e-flex e-con e-child\" data-id=\"492e764\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1a880c1 elementor-widget elementor-widget-image\" data-id=\"1a880c1\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! 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Prof. Natt Leelawat, D.Eng.<\/span>\n\t\t\t\t<textarea style=\"display: none;\" class=\"ctc-inline-copy-textarea\" readonly=\"readonly\">Assoc. 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17.9l-10.7 7.2s-5.5-12.5-19.7-12.5c-7.9 0-19.7 7.3-19.7 19.7v26.8c0 13.4 6.6 23.3 17.9 23.3 14.1 0 21.5-10.9 21.5-26.8h-17.9v-10.7h30.4c0 20.5 4.7 49.9-34 49.9zm-116.5 44.7c-9.4 0-13.6-.3-20-.8v-69.7c6.4-.6 15-.6 22.5-.6 23.3 0 37.2 12.2 37.2 34.5 0 21.9-15 36.6-39.7 36.6z\"><\/path><\/svg>\t\t\t\t\t<\/a>\n\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<span class=\"elementor-grid-item\">\n\t\t\t\t\t<a class=\"elementor-icon elementor-social-icon elementor-social-icon-external-link-alt elementor-repeater-item-74f2357\" href=\"https:\/\/sites.google.com\/site\/nattleelawat\" target=\"_blank\">\n\t\t\t\t\t\t<span class=\"elementor-screen-only\">External-link-alt<\/span>\n\t\t\t\t\t\t<svg class=\"e-font-icon-svg e-fas-external-link-alt\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M432,320H400a16,16,0,0,0-16,16V448H64V128H208a16,16,0,0,0,16-16V80a16,16,0,0,0-16-16H48A48,48,0,0,0,0,112V464a48,48,0,0,0,48,48H400a48,48,0,0,0,48-48V336A16,16,0,0,0,432,320ZM488,0h-128c-21.37,0-32.05,25.91-17,41l35.73,35.73L135,320.37a24,24,0,0,0,0,34L157.67,377a24,24,0,0,0,34,0L435.28,133.32,471,169c15,15,41,4.5,41-17V24A24,24,0,0,0,488,0Z\"><\/path><\/svg>\t\t\t\t\t<\/a>\n\t\t\t\t<\/span>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-9396753 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"9396753\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-82bd76a elementor-widget elementor-widget-text-editor\" data-id=\"82bd76a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.22.0 - 26-06-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Overview <\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-39c869e elementor-widget elementor-widget-text-editor\" data-id=\"39c869e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Dr. Natt Leelawat is an Associate Professor in Industrial Engineering at the Faculty of Engineering, Chulalongkorn University. He is also the Assistant Dean (International Affairs) of the Faculty of Engineering and the Head of the Center of Excellence in Disaster and Risk Management Information Systems (DRMIS). He is also a lecturer in the M.Sc. Program in Risk and Disaster Management and the M.Sc. Program in Innovative Engineering for Sustainability.<\/p><p>Dr. Leelawat is a Guest Associate Professor (Global) at the Graduate School of System Design and Management, Keio University, Japan. Previously, Dr. Leelawat has held various positions in academia and industry, including Director of the Risk and Disaster Management Program at the Graduate School of Chulalongkorn University, Assistant Professor at Tohoku University, Japan; Research Assistant at Tokyo Institute of Technology, Japan; and System Analyst at the Bank of Thailand. He is a member of several professional organizations, including the Association for Computing Machinery, the Association for Information Systems, the Business Continuity Institute (MBCI), IEEE (Senior Member and serving as Chair of IEEE R10 SAC), the Asia Oceania Geosciences Society (serving as Regional Advisory Committee and IG Session Secretary), the Earthquake Research Center of Thailand, and Thailand Network for Disaster Resilience.<\/p><p>Dr. Leelawat has received numerous awards and honors for his academic contributions. He was awarded the SakIntania\u2019s Young Lecturer Award in 2018, the Tokyo Tech Alumni Association (Thailand Chapter)\u2019s Young Outstanding Alumni Award in 2019, and the 2022 Samsenwittayalai Outstanding Alumni Award. He was also selected by Her Royal Highness Princess Maha Chakri Sirindhorn to be a representative from Thailand to join the 6th Global Young Scientists Summit in 2018. Dr. Leelawat has received Best Paper Awards from the 6th International Conference on Sustainable Future for Human Security in 2015, the 2nd International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics in 2021, the 40th Conference of Industrial Engineering Network in 2022, the 23rd International Symposium on Communications and Information Technologies in 2024, respective. Moreover, he and his team won the JDR Award for the Most Cited Paper in 2024.<\/p><p>His research areas include Disaster and Risk Management, Business Continuity Management, Management Information Systems, etc.<\/p><p>Personal Website : <a href=\"https:\/\/sites.google.com\/site\/nattleelawat\">https:\/\/sites.google.com\/site\/nattleelawat<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-e90f508 e-flex e-con-boxed e-con e-parent\" data-id=\"e90f508\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-921b7f0 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"921b7f0\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1bbfa79 elementor-widget elementor-widget-text-editor\" data-id=\"1bbfa79\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Education<\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e26a24 elementor-widget elementor-widget-text-editor\" data-id=\"3e26a24\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span class=\"ant-typography StyledText css-15ni9ka\">D.Eng. Industrial Engineering and Management<br \/><\/span>Tokyo Institute of Technology, Japan, 2016<\/p><p><span class=\"ant-typography StyledText css-15ni9ka\">M.Eng. Industrial Engineering and Management<br \/><\/span>Tokyo Institute of Technology, Japan, 2013<\/p><p>B.Sc. (First Class Honours) Information Technology<br \/>Sirindhorn International Institute of Technology, Thammasat University, Thailand, 2007<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-b43563c e-flex e-con-boxed e-con e-parent\" data-id=\"b43563c\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-2484244 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"2484244\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-85ced04 elementor-widget elementor-widget-text-editor\" data-id=\"85ced04\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Expertise<\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a7004c8 elementor-widget elementor-widget-text-editor\" data-id=\"a7004c8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span class=\"ant-typography StyledText css-1oc51h5\">Information Systems<\/span><\/p><p><span class=\"ant-typography StyledText css-1oc51h5\">Strategic &amp; Risk Management<\/span><\/p><p><span class=\"ant-typography StyledText css-1oc51h5\">Statistics &amp; Data Analysis<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-dd10e04 e-flex e-con-boxed e-con e-parent\" data-id=\"dd10e04\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-f3bff30 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"f3bff30\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-70ddead elementor-widget elementor-widget-text-editor\" data-id=\"70ddead\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Publications<br \/><\/span><\/strong><\/h4><p><div class=\"teachpress_pub_list\"><form name=\"tppublistform\" method=\"get\"><a name=\"tppubs\" id=\"tppubs\"><\/a><\/form><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">79 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 8 <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172&#038;lang=en&amp;limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172&#038;lang=en&amp;limit=8&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"last page\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><div class=\"teachpress_publication_list\"><h3 class=\"tp_h3\" id=\"tp_h3_2025\">2025<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Alfan Kurnia Yudha, Natt Leelawat, Jing Tang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('609','tp_links')\" style=\"cursor:pointer;\">A systematic review and bibliometric analysis of the impacts of COVID-19 on economy and mobility from the geospatial data perspective<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Results in Engineering, <\/span><span class=\"tp_pub_additional_volume\">vol. 26, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 25901230<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 1)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_609\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('609','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_609\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('609','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_609\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('609','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_609\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Yudha2025,<br \/>\r\ntitle = {A systematic review and bibliometric analysis of the impacts of COVID-19 on economy and mobility from the geospatial data perspective},<br \/>\r\nauthor = {Alfan Kurnia Yudha and Natt Leelawat and Jing Tang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105005182205&doi=10.1016%2fj.rineng.2025.105282&partnerID=40&md5=b0da3f68fe3fad4c74a18654be3ac488},<br \/>\r\ndoi = {10.1016\/j.rineng.2025.105282},<br \/>\r\nissn = {25901230},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {Results in Engineering},<br \/>\r\nvolume = {26},<br \/>\r\npublisher = {Elsevier B.V.},<br \/>\r\nabstract = {The COVID-19 pandemic has greatly impacted the global economy, human health, and daily life. The World Health Organization declared it a pandemic on March 11, 2020. By May 2023, it had caused over seven million deaths. Until now, its economic and social effects are still felt. This systematic review and bibliometric analysis focuses on how COVID-19 has affected the economy and mobility using geospatial data. Geospatial data from sensors, social media, mobile apps, cars, and remote sensing give us near-real-time insights into people's behaviors and perceptions during the pandemic. The study examines how COVID-19 spread over time and space to help understand and reduce its impact. Even with challenges in combining different datasets, spatial analysis shows patterns of how humans and the pandemic interact. The finding answers key questions: How did COVID-19 affect economic activities and mobility? What common patterns do geospatial data show during the pandemic? By identifying common geospatial datasets and analyzing research trends, the study provides insights for policymakers and researchers to better prepare for future pandemics. This review helps understand the complex systems of pandemics and their effects on society using geospatial big data. Notably, the findings show that nighttime light intensity and mobile phone mobility data were the most consistently used indicators to monitor pandemic-driven disruptions and recovery, captured shifts in behavior and compliance with public health measures, offering a critical data source for real-time health surveillance, enabling health experts to better understand population responses, and adaptive policy interventions. \u00a9 2025},<br \/>\r\nnote = {Cited by: 1},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('609','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_609\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The COVID-19 pandemic has greatly impacted the global economy, human health, and daily life. The World Health Organization declared it a pandemic on March 11, 2020. By May 2023, it had caused over seven million deaths. Until now, its economic and social effects are still felt. This systematic review and bibliometric analysis focuses on how COVID-19 has affected the economy and mobility using geospatial data. Geospatial data from sensors, social media, mobile apps, cars, and remote sensing give us near-real-time insights into people&#8217;s behaviors and perceptions during the pandemic. The study examines how COVID-19 spread over time and space to help understand and reduce its impact. Even with challenges in combining different datasets, spatial analysis shows patterns of how humans and the pandemic interact. The finding answers key questions: How did COVID-19 affect economic activities and mobility? What common patterns do geospatial data show during the pandemic? By identifying common geospatial datasets and analyzing research trends, the study provides insights for policymakers and researchers to better prepare for future pandemics. This review helps understand the complex systems of pandemics and their effects on society using geospatial big data. Notably, the findings show that nighttime light intensity and mobile phone mobility data were the most consistently used indicators to monitor pandemic-driven disruptions and recovery, captured shifts in behavior and compliance with public health measures, offering a critical data source for real-time health surveillance, enabling health experts to better understand population responses, and adaptive policy interventions. \u00a9 2025<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('609','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_609\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105005182205&amp;doi=10.1016%2fj.rineng.2025.105282&amp;partnerID=40&amp;md5=b0da3f68fe3fad4c74a18654be3ac488\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105005182205&amp;doi=10.1016[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105005182205&amp;doi=10.1016[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.rineng.2025.105282\" title=\"Follow DOI:10.1016\/j.rineng.2025.105282\" target=\"_blank\">doi:10.1016\/j.rineng.2025.105282<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('609','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Kumpol Saengtabtim, Natt Leelawat, Ampan Laosunthara, Jing Tang, Akira Kodaka, Yasushi Onda, Naohiko Kohtake<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('607','tp_links')\" style=\"cursor:pointer;\">Tourism Business Resilience and Sustainability during COVID-19: A Geoinformation Evidence of Nakhon Si Thammarat, Thailand<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_volume\">vol. 1479, <\/span><span class=\"tp_pub_additional_number\">no. 1, <\/span><span class=\"tp_pub_additional_publisher\">Institute of Physics, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 17551307<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_607\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('607','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_607\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('607','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_607\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('607','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_607\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Saengtabtim2025,<br \/>\r\ntitle = {Tourism Business Resilience and Sustainability during COVID-19: A Geoinformation Evidence of Nakhon Si Thammarat, Thailand},<br \/>\r\nauthor = {Kumpol Saengtabtim and Natt Leelawat and Ampan Laosunthara and Jing Tang and Akira Kodaka and Yasushi Onda and Naohiko Kohtake},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105003395954&doi=10.1088%2f1755-1315%2f1479%2f1%2f012056&partnerID=40&md5=9690896d402d721d48acf66f04eaf6a5},<br \/>\r\ndoi = {10.1088\/1755-1315\/1479\/1\/012056},<br \/>\r\nissn = {17551307},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {IOP Conference Series: Earth and Environmental Science},<br \/>\r\nvolume = {1479},<br \/>\r\nnumber = {1},<br \/>\r\npublisher = {Institute of Physics},<br \/>\r\nabstract = {Tourism has been a significant source of revenue for Thailand. However, during COVID-19, Thailand's tourism-related businesses, such as hotels, accommodation, and transportation, suffered greatly. Nakhon Si Thammarat is a second-tier Thai province in the country's south. Although the tourism businesses in this province suffered during COVID-19, they were expected to recover quickly. In this case, this study aims to highlight the positive aspects of the tourism industry during the COVID-19 pandemic, focusing on resilience, innovation, and long-term opportunities. This study analyzed the tourism businesses in Nakhon Si Thammarat using descriptive analysis and satellite imaging based on relative luminance. The descriptive analysis was conducted using flight data to Nakhon Si Thammarat and the occupancy rate, and the satellite image analysis used Planet data from PlanetScope sensors in the Wat Chedi area, a key tourism recovery area in Nakhon Si Thammarat. The satellite image analysis compared the land use and land cover (LULC) from 2018 to 2021 satellite images. Four satellite images from each year compare the LULC to indicate the change in the land used in the focused area. The results found that the tourism situation in Nakhon Si Thammarat had improved faster than Thailand's overall tourism situation, and the area's tourism industry's recovery and resilience to sustainability were primarily due to the influence of faith in Wat Chedi. \u00a9 Published under licence by IOP Publishing Ltd.},<br \/>\r\nnote = {Cited by: 0},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('607','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_607\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Tourism has been a significant source of revenue for Thailand. However, during COVID-19, Thailand&#8217;s tourism-related businesses, such as hotels, accommodation, and transportation, suffered greatly. Nakhon Si Thammarat is a second-tier Thai province in the country&#8217;s south. Although the tourism businesses in this province suffered during COVID-19, they were expected to recover quickly. In this case, this study aims to highlight the positive aspects of the tourism industry during the COVID-19 pandemic, focusing on resilience, innovation, and long-term opportunities. This study analyzed the tourism businesses in Nakhon Si Thammarat using descriptive analysis and satellite imaging based on relative luminance. The descriptive analysis was conducted using flight data to Nakhon Si Thammarat and the occupancy rate, and the satellite image analysis used Planet data from PlanetScope sensors in the Wat Chedi area, a key tourism recovery area in Nakhon Si Thammarat. The satellite image analysis compared the land use and land cover (LULC) from 2018 to 2021 satellite images. Four satellite images from each year compare the LULC to indicate the change in the land used in the focused area. The results found that the tourism situation in Nakhon Si Thammarat had improved faster than Thailand&#8217;s overall tourism situation, and the area&#8217;s tourism industry&#8217;s recovery and resilience to sustainability were primarily due to the influence of faith in Wat Chedi. \u00a9 Published under licence by IOP Publishing Ltd.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('607','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_607\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105003395954&amp;doi=10.1088%2f1755-1315%2f1479%2f1%2f012056&amp;partnerID=40&amp;md5=9690896d402d721d48acf66f04eaf6a5\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105003395954&amp;doi=10.1088[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105003395954&amp;doi=10.1088[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1088\/1755-1315\/1479\/1\/012056\" title=\"Follow DOI:10.1088\/1755-1315\/1479\/1\/012056\" target=\"_blank\">doi:10.1088\/1755-1315\/1479\/1\/012056<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('607','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Ampan Laosunthara, Kodchakorn Krutphong, Natt Leelawat, Wongsa Wararuksajja, Naruethep Sukulthanasorn, Anawat Suppasri, Ratchaneekorn Thongthip, Chatpan Chintanapakdee<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('605','tp_links')\" style=\"cursor:pointer;\">Initial observations and immediate lessons learned from Thailand&#8217;s response to the 2025 Mandalay earthquake<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">International Journal of Disaster Risk Reduction, <\/span><span class=\"tp_pub_additional_volume\">vol. 127, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 22124209<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_605\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('605','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_605\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('605','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_605\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('605','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_605\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Laosunthara2025,<br \/>\r\ntitle = {Initial observations and immediate lessons learned from Thailand's response to the 2025 Mandalay earthquake},<br \/>\r\nauthor = {Ampan Laosunthara and Kodchakorn Krutphong and Natt Leelawat and Wongsa Wararuksajja and Naruethep Sukulthanasorn and Anawat Suppasri and Ratchaneekorn Thongthip and Chatpan Chintanapakdee},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105010414313&doi=10.1016%2fj.ijdrr.2025.105675&partnerID=40&md5=0fc5e58eef5451c6ec4fbe6f61886754},<br \/>\r\ndoi = {10.1016\/j.ijdrr.2025.105675},<br \/>\r\nissn = {22124209},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {International Journal of Disaster Risk Reduction},<br \/>\r\nvolume = {127},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {On March 28, 2025, a magnitude 7.7 earthquake struck central Myanmar, with tremors widely felt across Thailand. Bangkok, in particular, experienced severe disruption due to long-period ground motion (LPGM), highlighting the city's vulnerability to distant seismic events. This earthquake represents the most wide-reaching seismic disruption to affect Thailand since the 2004 Aceh Tsunami. This study presents preliminary observations of Thailand's response during the critical first 72 h, focusing on structural damage, emergency coordination, evacuation challenges, and public risk communication. In Bangkok, the collapse of a 30-story construction site resulted in 19 fatalities and 78 missing persons. Vulnerable groups, including people with limited mobility, faced heightened risks due to inaccessible infrastructure. Hospitals struggled to maintain operations while evacuating patients, and misinformation on social media intensified public confusion. This research identifies key policy implications: enhancing building standards to address non-structural elements, institutionalizing regular evacuation drills for high-rise buildings, and accelerating the deployment of nationwide cell broadcast alert systems. The 2025 Mandalay earthquake revealed that seismic events beyond national borders can cascade into multi-dimensional urban crises. The findings underscore the urgency of integrated risk governance frameworks and strengthened regional collaboration across Southeast Asia to prepare for and mitigate cross-border disaster impacts. \u00a9 2025 Elsevier Ltd},<br \/>\r\nnote = {Cited by: 0},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('605','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_605\" style=\"display:none;\"><div class=\"tp_abstract_entry\">On March 28, 2025, a magnitude 7.7 earthquake struck central Myanmar, with tremors widely felt across Thailand. Bangkok, in particular, experienced severe disruption due to long-period ground motion (LPGM), highlighting the city&#8217;s vulnerability to distant seismic events. This earthquake represents the most wide-reaching seismic disruption to affect Thailand since the 2004 Aceh Tsunami. This study presents preliminary observations of Thailand&#8217;s response during the critical first 72 h, focusing on structural damage, emergency coordination, evacuation challenges, and public risk communication. In Bangkok, the collapse of a 30-story construction site resulted in 19 fatalities and 78 missing persons. Vulnerable groups, including people with limited mobility, faced heightened risks due to inaccessible infrastructure. Hospitals struggled to maintain operations while evacuating patients, and misinformation on social media intensified public confusion. This research identifies key policy implications: enhancing building standards to address non-structural elements, institutionalizing regular evacuation drills for high-rise buildings, and accelerating the deployment of nationwide cell broadcast alert systems. The 2025 Mandalay earthquake revealed that seismic events beyond national borders can cascade into multi-dimensional urban crises. The findings underscore the urgency of integrated risk governance frameworks and strengthened regional collaboration across Southeast Asia to prepare for and mitigate cross-border disaster impacts. \u00a9 2025 Elsevier Ltd<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('605','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_605\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105010414313&amp;doi=10.1016%2fj.ijdrr.2025.105675&amp;partnerID=40&amp;md5=0fc5e58eef5451c6ec4fbe6f61886754\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105010414313&amp;doi=10.1016[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105010414313&amp;doi=10.1016[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.ijdrr.2025.105675\" title=\"Follow DOI:10.1016\/j.ijdrr.2025.105675\" target=\"_blank\">doi:10.1016\/j.ijdrr.2025.105675<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('605','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2024\">2024<\/h3><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Teerapat Tappanom, Natt Leelawat, Kumpol Saengtabtim, Jing Tang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('606','tp_links')\" style=\"cursor:pointer;\">Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_publisher\">Institute of Electrical and Electronics Engineers Inc., <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 979-835035395-2<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_606\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('606','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_606\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('606','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_606\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('606','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_606\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Tappanom2024265,<br \/>\r\ntitle = {Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand},<br \/>\r\nauthor = {Teerapat Tappanom and Natt Leelawat and Kumpol Saengtabtim and Jing Tang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216587908&doi=10.1109%2fISCIT63075.2024.10793674&partnerID=40&md5=38609d128e56d8a84283b20b981e6366},<br \/>\r\ndoi = {10.1109\/ISCIT63075.2024.10793674},<br \/>\r\nisbn = {979-835035395-2},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},<br \/>\r\npages = {265 \u2013 270},<br \/>\r\npublisher = {Institute of Electrical and Electronics Engineers Inc.},<br \/>\r\nabstract = {Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed\/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. \u00a9 2024 IEEE.},<br \/>\r\nnote = {Cited by: 0},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('606','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_606\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed\/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang&#8217;s spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. \u00a9 2024 IEEE.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('606','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_606\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216587908&amp;doi=10.1109%2fISCIT63075.2024.10793674&amp;partnerID=40&amp;md5=38609d128e56d8a84283b20b981e6366\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216587908&amp;doi=10.1109%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216587908&amp;doi=10.1109%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ISCIT63075.2024.10793674\" title=\"Follow DOI:10.1109\/ISCIT63075.2024.10793674\" target=\"_blank\">doi:10.1109\/ISCIT63075.2024.10793674<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('606','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Sushank Chaudhary, Nitinun Sinpan, Pruk Sasithong, Sunita Khichar, Panithan La-Aiddee, Natt Leelawat, Amir Parnianifard, Suvit Poomrittigul, Lunchakorn Wuttisittikulkij<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('608','tp_links')\" style=\"cursor:pointer;\">Proximal Policy Optimization for Crowd Evacuation in Complex Environments &#8211; A Metaverse Approach at Krung Thep Aphiwat Central Terminal, Thailand<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">IEEE Access, <\/span><span class=\"tp_pub_additional_volume\">vol. 12, <\/span><span class=\"tp_pub_additional_pages\">pp. 196969 \u2013 196983, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 21693536<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 2; All Open Access, Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_608\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('608','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_608\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('608','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_608\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('608','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_608\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Chaudhary2024196969,<br \/>\r\ntitle = {Proximal Policy Optimization for Crowd Evacuation in Complex Environments - A Metaverse Approach at Krung Thep Aphiwat Central Terminal, Thailand},<br \/>\r\nauthor = {Sushank Chaudhary and Nitinun Sinpan and Pruk Sasithong and Sunita Khichar and Panithan La-Aiddee and Natt Leelawat and Amir Parnianifard and Suvit Poomrittigul and Lunchakorn Wuttisittikulkij},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85211992072&doi=10.1109%2fACCESS.2024.3515153&partnerID=40&md5=1136034d905fd93d139dc7dcb4af0b0b},<br \/>\r\ndoi = {10.1109\/ACCESS.2024.3515153},<br \/>\r\nissn = {21693536},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {IEEE Access},<br \/>\r\nvolume = {12},<br \/>\r\npages = {196969 \u2013 196983},<br \/>\r\npublisher = {Institute of Electrical and Electronics Engineers Inc.},<br \/>\r\nabstract = {Efficient crowd evacuation from railway platforms is critical for passenger safety during emergencies. This study introduces a novel dynamic emergency evacuation route generator using the Proximal Policy Optimization (PPO) algorithm within a custom-built 3D simulation environment developed in Unity. We independently created a detailed digital twin of Krung Thep Aphiwat Central Terminal, Thailand's largest train station, and implemented all elements of the simulation, including the Social Force Model, to accurately replicate crowd behaviors and interactions during evacuation scenarios. Through extensive training over 3,000,000 episodes, our PPO-based model achieved significant improvements in evacuation efficiency. The results indicate that in a major emergency scenario, increasing the number of agents in the station reduced the number of remaining passengers from 111 to just 6, highlighting the model's effectiveness. Similarly, in a minor emergency scenario, the average number of remaining passengers dropped from 38 to 1 with the addition of more agents. These findings confirm the model's ability to adapt to different emergency conditions, offering a practical and scalable solution for enhancing evacuation strategies in high-density environments. Furthermore, increasing the agents' sight range also improved evacuation efficiency, with a 20-meter sight range yielding the best results. \u00a9 2013 IEEE.},<br \/>\r\nnote = {Cited by: 2; All Open Access, Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('608','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_608\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Efficient crowd evacuation from railway platforms is critical for passenger safety during emergencies. This study introduces a novel dynamic emergency evacuation route generator using the Proximal Policy Optimization (PPO) algorithm within a custom-built 3D simulation environment developed in Unity. We independently created a detailed digital twin of Krung Thep Aphiwat Central Terminal, Thailand&#8217;s largest train station, and implemented all elements of the simulation, including the Social Force Model, to accurately replicate crowd behaviors and interactions during evacuation scenarios. Through extensive training over 3,000,000 episodes, our PPO-based model achieved significant improvements in evacuation efficiency. The results indicate that in a major emergency scenario, increasing the number of agents in the station reduced the number of remaining passengers from 111 to just 6, highlighting the model&#8217;s effectiveness. Similarly, in a minor emergency scenario, the average number of remaining passengers dropped from 38 to 1 with the addition of more agents. These findings confirm the model&#8217;s ability to adapt to different emergency conditions, offering a practical and scalable solution for enhancing evacuation strategies in high-density environments. Furthermore, increasing the agents&#8217; sight range also improved evacuation efficiency, with a 20-meter sight range yielding the best results. \u00a9 2013 IEEE.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('608','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_608\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85211992072&amp;doi=10.1109%2fACCESS.2024.3515153&amp;partnerID=40&amp;md5=1136034d905fd93d139dc7dcb4af0b0b\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85211992072&amp;doi=10.1109%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85211992072&amp;doi=10.1109%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ACCESS.2024.3515153\" title=\"Follow DOI:10.1109\/ACCESS.2024.3515153\" target=\"_blank\">doi:10.1109\/ACCESS.2024.3515153<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('608','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Jing Tang, Manapat Weeramongkolkul, Supanida Suwankesawong, Kumpol Saengtabtim, Natt Leelawat, Kritchart Wongwailikhit<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('154','tp_links')\" style=\"cursor:pointer;\">Toward a more resilient Thailand: Developing a machine learning-powered forest fire warning system<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Heliyon, <\/span><span class=\"tp_pub_additional_volume\">vol. 10, <\/span><span class=\"tp_pub_additional_number\">no. 13, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 24058440<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 4; All Open Access, Green Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_154\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('154','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_154\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('154','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_154\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('154','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_154\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Tang2024,<br \/>\r\ntitle = {Toward a more resilient Thailand: Developing a machine learning-powered forest fire warning system},<br \/>\r\nauthor = {Jing Tang and Manapat Weeramongkolkul and Supanida Suwankesawong and Kumpol Saengtabtim and Natt Leelawat and Kritchart Wongwailikhit},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85197488130&doi=10.1016%2fj.heliyon.2024.e34021&partnerID=40&md5=12d1d4ba8bc243caa9519b05c8dda86b},<br \/>\r\ndoi = {10.1016\/j.heliyon.2024.e34021},<br \/>\r\nissn = {24058440},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Heliyon},<br \/>\r\nvolume = {10},<br \/>\r\nnumber = {13},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {Forest fires in Thailand are a recurring and formidable challenge, inflicting widespread damage and ranking among the nation's most devastating natural disasters. Most detection methods are labor-intensive, lack speed for early detection, or result in high infrastructure costs. An essential approach to mitigating this issue involves establishing an efficient forest fire warning system based on amalgamating diverse available data sources and optimized algorithms. This research endeavors to develop a binary machine-learning classifier based on Thailand's forest fire occurrences from January 2019 to October 2022 using data acquired from satellite resources, including the Google Earth engine. We use four gas variables including carbon monoxide, sulfur dioxide, nitrogen dioxide, and ozone. The study explores a range of classification models, encompassing linear classifiers, gradient-boosting classifiers, and artificial neural networks. The XGBoost model is the top-performing option across various classification evaluation metrics. The model provides the accuracy of 99.6 % and ROC-AUC score of 0.939. These findings underscore the necessity for a comprehensive forest fire warning system that integrates gas measurement sensor devices and geospatial data. A feedback mechanism is also imperative to enable model retraining post-deployment, thereby diminishing reliance on geospatial attributes. Moreover, given that decision-tree-based algorithms consistently yield superior results, future research in machine learning for forest fire prediction should prioritize these approaches. \u00a9 2024 The Authors},<br \/>\r\nnote = {Cited by: 4; All Open Access, Green Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('154','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_154\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Forest fires in Thailand are a recurring and formidable challenge, inflicting widespread damage and ranking among the nation&#8217;s most devastating natural disasters. Most detection methods are labor-intensive, lack speed for early detection, or result in high infrastructure costs. An essential approach to mitigating this issue involves establishing an efficient forest fire warning system based on amalgamating diverse available data sources and optimized algorithms. This research endeavors to develop a binary machine-learning classifier based on Thailand&#8217;s forest fire occurrences from January 2019 to October 2022 using data acquired from satellite resources, including the Google Earth engine. We use four gas variables including carbon monoxide, sulfur dioxide, nitrogen dioxide, and ozone. The study explores a range of classification models, encompassing linear classifiers, gradient-boosting classifiers, and artificial neural networks. The XGBoost model is the top-performing option across various classification evaluation metrics. The model provides the accuracy of 99.6 % and ROC-AUC score of 0.939. These findings underscore the necessity for a comprehensive forest fire warning system that integrates gas measurement sensor devices and geospatial data. A feedback mechanism is also imperative to enable model retraining post-deployment, thereby diminishing reliance on geospatial attributes. Moreover, given that decision-tree-based algorithms consistently yield superior results, future research in machine learning for forest fire prediction should prioritize these approaches. \u00a9 2024 The Authors<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('154','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_154\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85197488130&amp;doi=10.1016%2fj.heliyon.2024.e34021&amp;partnerID=40&amp;md5=12d1d4ba8bc243caa9519b05c8dda86b\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85197488130&amp;doi=10.1016%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85197488130&amp;doi=10.1016%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.heliyon.2024.e34021\" title=\"Follow DOI:10.1016\/j.heliyon.2024.e34021\" target=\"_blank\">doi:10.1016\/j.heliyon.2024.e34021<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('154','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Naphat Mahittikul, Nawat Wancham, Wanit Treeranurat, Kumpol Saengtabtim, Ampan Laosunthara, Jing Tang, Natt Leelawat<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('161','tp_links')\" style=\"cursor:pointer;\">Examining the Factors Influencing Tsunami Evacuation Action Selection in Thailand: A Comprehensive Study Involving Local Residents, Non-Local Workers, and Travelers<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Sustainability (Switzerland), <\/span><span class=\"tp_pub_additional_volume\">vol. 16, <\/span><span class=\"tp_pub_additional_number\">no. 5, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 20711050<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0; All Open Access, Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_161\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('161','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_161\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('161','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_161\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('161','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_161\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Mahittikul2024,<br \/>\r\ntitle = {Examining the Factors Influencing Tsunami Evacuation Action Selection in Thailand: A Comprehensive Study Involving Local Residents, Non-Local Workers, and Travelers},<br \/>\r\nauthor = {Naphat Mahittikul and Nawat Wancham and Wanit Treeranurat and Kumpol Saengtabtim and Ampan Laosunthara and Jing Tang and Natt Leelawat},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85187435335&doi=10.3390%2fsu16052024&partnerID=40&md5=6d5f0e6f9a5879d21b589df20d2ca8a2},<br \/>\r\ndoi = {10.3390\/su16052024},<br \/>\r\nissn = {20711050},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Sustainability (Switzerland)},<br \/>\r\nvolume = {16},<br \/>\r\nnumber = {5},<br \/>\r\npublisher = {Multidisciplinary Digital Publishing Institute (MDPI)},<br \/>\r\nabstract = {Tsunamis are a substantial natural threat in Thailand, as evidenced by the 2004 Indian Ocean tsunami. Effective evacuation is vital to reduce casualties and property damage. However, despite improved warning systems, high death tolls still occur, indicating complex evacuation behavior influenced by various factors. This study examines these factors among diverse groups in Phuket and Phang Nga, Thailand. A survey of 1000 locals, non-local workers, and travelers assesses threat and coping appraisals, past tsunami experiences, gender, age, and tsunami evacuation intention and action selection. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data based on the hypotheses related to the Protection Motivation Theory (PMT). The results of the analyses show that threat and coping appraisals significantly predict tsunami evacuation intention, and gender influences threat perception related to evacuation. Variations among respondent types emphasize the need for tailored disaster preparedness and response strategies. This study offers crucial insights for policymakers, emergency responders, and disaster management stakeholders, underlining the significance of further research into the intricate interplay of individual and contextual factors shaping tsunami evacuation behavior. \u00a9 2024 by the authors.},<br \/>\r\nnote = {Cited by: 0; All Open Access, Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('161','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_161\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Tsunamis are a substantial natural threat in Thailand, as evidenced by the 2004 Indian Ocean tsunami. Effective evacuation is vital to reduce casualties and property damage. However, despite improved warning systems, high death tolls still occur, indicating complex evacuation behavior influenced by various factors. This study examines these factors among diverse groups in Phuket and Phang Nga, Thailand. A survey of 1000 locals, non-local workers, and travelers assesses threat and coping appraisals, past tsunami experiences, gender, age, and tsunami evacuation intention and action selection. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data based on the hypotheses related to the Protection Motivation Theory (PMT). The results of the analyses show that threat and coping appraisals significantly predict tsunami evacuation intention, and gender influences threat perception related to evacuation. Variations among respondent types emphasize the need for tailored disaster preparedness and response strategies. This study offers crucial insights for policymakers, emergency responders, and disaster management stakeholders, underlining the significance of further research into the intricate interplay of individual and contextual factors shaping tsunami evacuation behavior. \u00a9 2024 by the authors.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('161','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_161\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85187435335&amp;doi=10.3390%2fsu16052024&amp;partnerID=40&amp;md5=6d5f0e6f9a5879d21b589df20d2ca8a2\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85187435335&amp;doi=10.3390%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85187435335&amp;doi=10.3390%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.3390\/su16052024\" title=\"Follow DOI:10.3390\/su16052024\" target=\"_blank\">doi:10.3390\/su16052024<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('161','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Penpitcha Arayachookiat, Kumpol Saengtabtim, Akira Kodaka, Natt Leelawat, Jing Tang, Kenji Watanabe<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('610','tp_links')\" style=\"cursor:pointer;\">Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_publisher\">Institute of Electrical and Electronics Engineers Inc., <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 979-835035395-2<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_610\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('610','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_610\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('610','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_610\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('610','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_610\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Arayachookiat2024247,<br \/>\r\ntitle = {Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones},<br \/>\r\nauthor = {Penpitcha Arayachookiat and Kumpol Saengtabtim and Akira Kodaka and Natt Leelawat and Jing Tang and Kenji Watanabe},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216535244&doi=10.1109%2fISCIT63075.2024.10793677&partnerID=40&md5=abfebc955936d63a6b9bc352ecc342d7},<br \/>\r\ndoi = {10.1109\/ISCIT63075.2024.10793677},<br \/>\r\nisbn = {979-835035395-2},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},<br \/>\r\npages = {247 \u2013 252},<br \/>\r\npublisher = {Institute of Electrical and Electronics Engineers Inc.},<br \/>\r\nabstract = {The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. \u00a9 2024 IEEE.},<br \/>\r\nnote = {Cited by: 0},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('610','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_610\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. \u00a9 2024 IEEE.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('610','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_610\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216535244&amp;doi=10.1109%2fISCIT63075.2024.10793677&amp;partnerID=40&amp;md5=abfebc955936d63a6b9bc352ecc342d7\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216535244&amp;doi=10.1109%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216535244&amp;doi=10.1109%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ISCIT63075.2024.10793677\" title=\"Follow DOI:10.1109\/ISCIT63075.2024.10793677\" target=\"_blank\">doi:10.1109\/ISCIT63075.2024.10793677<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('610','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Ampan Laosunthara, Natt Leelawat, Takumi Ohashi, Titaya Sararit, Mongkonkorn Srivichai, Jing Tang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('611','tp_links')\" style=\"cursor:pointer;\">Awareness of Disaster Risk and Preparedness: Insights from a Survey of Children and Adults in Thailand<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_publisher\">Institute of Electrical and Electronics Engineers Inc., <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 979-835035395-2<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 1)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_611\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('611','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_611\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('611','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_611\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('611','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_611\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Laosunthara2024122,<br \/>\r\ntitle = {Awareness of Disaster Risk and Preparedness: Insights from a Survey of Children and Adults in Thailand},<br \/>\r\nauthor = {Ampan Laosunthara and Natt Leelawat and Takumi Ohashi and Titaya Sararit and Mongkonkorn Srivichai and Jing Tang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216570493&doi=10.1109%2fISCIT63075.2024.10793697&partnerID=40&md5=3ac3343998aa02cd815c2a98ec2a162c},<br \/>\r\ndoi = {10.1109\/ISCIT63075.2024.10793697},<br \/>\r\nisbn = {979-835035395-2},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Conference Proceeding - 23rd International Symposium on Communications and Information Technologies, ISCIT 2024},<br \/>\r\npages = {122 \u2013 127},<br \/>\r\npublisher = {Institute of Electrical and Electronics Engineers Inc.},<br \/>\r\nabstract = {Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society. \u00a9 2024 IEEE.},<br \/>\r\nnote = {Cited by: 1},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('611','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_611\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society. \u00a9 2024 IEEE.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('611','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_611\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216570493&amp;doi=10.1109%2fISCIT63075.2024.10793697&amp;partnerID=40&amp;md5=3ac3343998aa02cd815c2a98ec2a162c\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216570493&amp;doi=10.1109%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85216570493&amp;doi=10.1109%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ISCIT63075.2024.10793697\" title=\"Follow DOI:10.1109\/ISCIT63075.2024.10793697\" target=\"_blank\">doi:10.1109\/ISCIT63075.2024.10793697<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('611','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Natt Leelawat, Bhanutas Savanachai, Crongchatra Pathsiriyos, Kanokkarn Pinkeaw, Kijwipat Thanasittichai, Paratchaporn Uttraporn, Sirinada Sanprasert, Tandin Dorji, Vimolnath Saisim, Alfan Kurnia Yudha, Jing Tang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('169','tp_links')\" style=\"cursor:pointer;\">The 2021 Tropical Storm Dianmu in Thailand: Disaster Responses and Roles of Information Technology<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Disaster Research, <\/span><span class=\"tp_pub_additional_volume\">vol. 19, <\/span><span class=\"tp_pub_additional_number\">no. 4, <\/span><span class=\"tp_pub_additional_pages\">pp. 645 \u2013 655, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 18812473<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0; All Open Access, Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_169\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('169','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_169\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('169','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_169\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('169','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_169\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Leelawat2024645,<br \/>\r\ntitle = {The 2021 Tropical Storm Dianmu in Thailand: Disaster Responses and Roles of Information Technology},<br \/>\r\nauthor = {Natt Leelawat and Bhanutas Savanachai and Crongchatra Pathsiriyos and Kanokkarn Pinkeaw and Kijwipat Thanasittichai and Paratchaporn Uttraporn and Sirinada Sanprasert and Tandin Dorji and Vimolnath Saisim and Alfan Kurnia Yudha and Jing Tang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85201667143&doi=10.20965%2fjdr.2024.p0645&partnerID=40&md5=7ca25e85c79870e80f8113073e790083},<br \/>\r\ndoi = {10.20965\/jdr.2024.p0645},<br \/>\r\nissn = {18812473},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Journal of Disaster Research},<br \/>\r\nvolume = {19},<br \/>\r\nnumber = {4},<br \/>\r\npages = {645 \u2013 655},<br \/>\r\npublisher = {Fuji Technology Press},<br \/>\r\nabstract = {At the end of September 2021, Tropical Storm Dianmu caused catastrophic floods in Thailand, placing thou-sands of lives, properties, infrastructure, and other things, in danger. These circumstances provide an op-portunity to learn how to respond to tropical storm situations in the future. Our investigation reveals that Thailand has access to a wealth of data, including geospatial, radar, satellite, and sensor information. Thus, these data could be utilized for an urgent alert system and communication channel to mitigate and re-duce the potential for large-scale destruction by tropical storms and floods in the future. \u00a9 Fuji Technology Press Ltd.},<br \/>\r\nnote = {Cited by: 0; All Open Access, Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('169','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_169\" style=\"display:none;\"><div class=\"tp_abstract_entry\">At the end of September 2021, Tropical Storm Dianmu caused catastrophic floods in Thailand, placing thou-sands of lives, properties, infrastructure, and other things, in danger. These circumstances provide an op-portunity to learn how to respond to tropical storm situations in the future. Our investigation reveals that Thailand has access to a wealth of data, including geospatial, radar, satellite, and sensor information. Thus, these data could be utilized for an urgent alert system and communication channel to mitigate and re-duce the potential for large-scale destruction by tropical storms and floods in the future. \u00a9 Fuji Technology Press Ltd.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('169','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_169\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85201667143&amp;doi=10.20965%2fjdr.2024.p0645&amp;partnerID=40&amp;md5=7ca25e85c79870e80f8113073e790083\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85201667143&amp;doi=10.20965[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85201667143&amp;doi=10.20965[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.20965\/jdr.2024.p0645\" title=\"Follow DOI:10.20965\/jdr.2024.p0645\" target=\"_blank\">doi:10.20965\/jdr.2024.p0645<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('169','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><\/div><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">79 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 8 <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172&#038;lang=en&amp;limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=3172&#038;lang=en&amp;limit=8&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"last page\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><\/div><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-3df2e2b e-flex e-con-boxed e-con e-parent\" data-id=\"3df2e2b\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>DRMIS Lab, 5th Floor of Engineering 4 Bldg., Room 511 +66-2218-6824 natt.l@chula.ac.th Facebook-square Linkedin Researchgate External-link-alt Overview Dr. Natt Leelawat [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"","ast-site-content-layout":"full-width-container","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"default","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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