研究者業績

Thatsanee Charoenporn

  (タッサネーチャロエンポーン タッサネー)

Profile Information

Affiliation
Lecturer, Faculty of Data Science, Musashino University
Degree
Ph.D.(Sirindhorn International Institute of Technology, Thailand)

Other name(s) (e.g. nickname)
Kaeng-SOM
J-GLOBAL ID
201901012821607047
researchmap Member ID
B000350703

In the age that information blows into us anywhere and anytime, it enables people to access across various sciences easily. The combination of science, arts and humanity can occur serenely. I believe that science and mind are compatible. My deep passion is to apply various academic aspects including truth together for the benefit and highest happiness of mankind. I therefore became a part of many important multidisciplinary project such as the Multi-lingual Machine Translation Project (1989-1995), Language Resource Development for Computer Science (ORCHID), E-Learning for Minor Languages, Information Literacy, Application of IOT for the elderly and Well-Being, Digital Cultural Information Development (Digitized Thailand), Digital Thinking, Social Entrepreneur, University Entrepreneur, Start up Promotion Support and so on.

I have an M.A. and B.A. in Arts and Linguistics and Ph.D. in Information Technology. All degrees and experiences from the real implemented projects granted me as part of a member of the National Electronics and Computer Technology Center, Thailand (1994-2014), Faculty of Informatics, Burapha University of Thailand (2014-2019). Currently, I am a member of the Faculty of Data Science, and Asia AI Institute of Musashino University, Japan.

My research interests include Language Resource Development, Semantics, Syntactic, Morphological Analysis, Machine Translation, Language Intermediate Representation, Natural Language Processing, Social Innovation, Business Model and Inspiration, Social Understanding,  Standardization on Heritage Information, and Cultural and Historic Digitization.

Papers

 38
  • Virach Sornlertlamvanich, Thatsanee Charoenporn, Somrudee Deepaisarn
    Frontiers in Artificial Intelligence and Applications, Jan 16, 2024  
    The Thammasat AI City distributed platform is a proposed AI platform designed to enhance city intelligent management. It addresses the limitations of current smart city architecture by incorporating cross-domain data connectivity and machine learning to support comprehensive data collection. In this study, we delve into two main areas, that is, monitoring and visualization of city ambient lighting, and indoor human physical distance tracking. The smart street light monitoring system provides real-time visualization of street lighting status, energy consumption, and maintenance requirement, which helps to optimize energy consumption and maintenance reduction. The indoor camera-based system for human physical distance tracking can be used in public spaces to monitor social distancing and ensure public safety. The overall goal of the platform is to improve the quality of life in urban areas and align with sustainable urban development concepts.
  • Virach Sornlertlamvanich, Pawinee Iamtrakul, Teerayuth Horanont, Narit Hnoohom, Konlakorn Wongpatikaseree, Sumeth Yuenyong, Jantima Angkapanichkit, Suthasinee Piyapasuntra, Prittipoen Lopkerd, Santirak Prasertsuk, Chawee Busayarat, I-soon Raungratanaamporn, Somrudee Deepaisarn, Thatsanee Charoenporn
    Frontiers in Artificial Intelligence and Applications, Jan 23, 2023  
    This research proposes an AI platform for data sharing across multiple domains. Since the data in the smart city concept are domain-specific processed, the existing smart city architecture is suffered from cross-domain data interpretation. To go beyond the digital transformation efforts in smart city development, the AI city is created on the architecture of cross-domain data connectivity and transform learning in the machine learning paradigm. In this research, the health and human behavioral data are targeted on human traceability and contactless technologies. To measure the inhabitants quality of life (QoL), the primary emotion expression study is conducted to interpret the emotional states and the mental health of people in the urbanized city. The results of information augmentation draw attention to the immersive visualization of the Thammasat model.
  • Taiki Kimura, Thatsanee Charoenporn, Virach Sornlertlamvanich
    2022 International Electronics Symposium (IES), Aug 9, 2022  
  • Virach Sornlertlamvanich, Thatsanee Charoenporn, Shiori Sasaki, Yasushi Kiyoki
    IIAI-AAI-Winter, 225-229, 2022  
  • Virach Sornlertlamvanich, Kitiya Suriyachay, Thatsanee Charoenporn
    Human Language Technology. Challenges for Computer Science and Linguistics, 143-160, 2022  

Misc.

 1

Presentations

 21

Teaching Experience

 12