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Machine-learning based classification of the behavior of children with PIMD/SMID: ICIET2021 Okayama University, Japan
While there may be substantial evidence of the relationship between weather parameters and behaviors among typically developing children across settings, studies involving children with neurological functioning impairments that affect communication or those with physical and motor disabilities are unexpectedly scarce. Recently, the importance of weather parameters and location information to better understand the context of the communication of children with profound intellectual and multiple disabilities or severe motor and intellectual disorders has been proposed through the development of ChildSIDE. This app collects behaviors, location, and environment data. However, an investigation has not been done on whether these data can be used to classify behavior.
Our study on investigating whether location and environment data would allow more accurate classification of behavior by evaluating the performance of different machine learning algorithms (random forest, support vector machine, XGBoost, and neural networks) using critical metrics was presented in the 2021 9th International Conference on Information and Education Technology (ICIET) held last March 27th to 29th, 2021. Although it was planned to be held at Okayama University, Japan, the organizing committee has made the difficult decision to turn it into an onsite conference (local attendees) blended with virtual mode after due consideration and in view of the global health emergency and widespread travel restrictions (foreign attendees).
Prof. Nobuo Funabiki, the conference’s local chair, welcomed all the attendees from the conference venue at Okayama University, Japan. It was followed by keynote speeches from Prof. Hai Jin (Fellow of IEEE, CCF, and Life Member of ACM, Huazhong University of Science and Technology, China) delivered her speech on Towards the Practical Blockchain System: Challenges and Practices, while Prof. Akihiko Sugiyama (Fellow of IEEE and IEICE, Yahoo Japan Corporation, Japan) talked about Be Kind to the Reviewers and They will Reward You. A talk on University Education Based on Research Activities and Academic Activities, Global and Innovative Human Resource Development was the focus of the talk delivered by Prof. Yoshiaki Kakuda (Member of IEEE (U.S.A.), IEICE (Japan) and IPSJ (Japan), Hiroshima City University, Japan). The last keynote speech was about Computer should make someone happy! by Prof. Masahito Hirakawa (Shimane University, Japan).
A high-end venue for researchers, scientists, engineers, scholars, and graduate students to share the most recent research findings, ICIET2021 aims to provide theoretical foundations, practical knowledge, and personal contacts that will aid in the development of long-term, productive, and sustainable communication among researchers and practitioners in related scientific fields. With this in mind, the sessions were focused on Intelligent Education System and Education Informatization, Online Learning and Assessment, Blended Teaching and Game-Based Learning, Artificial Intelligence in Education and Educational Information Technology, Information Communication Technology and Computer Application, Subject Education and Talent Cultivation, Higher Education and Educational Research, and Digital Society and Knowledge Engineering.
Led by Prof. Tadashi Takahashi, Konan University, Japan & Dr. Andrea Urushima, Kyoto University, Japan, we were able to talk about our study on the machine learning approach to predicting the behavior of children with PIMD/SMID in the parallel online session on Artificial Intelligence in Education and Educational Information Technology. Presentations in the session included the use of information and communication technologies, E-learning system, and machine learning models application in teaching and learning. At the end of the session, we were again recognized as the Best Presentation among the roster of students and experts from different professors and researchers in Japan, China, Peru, Indonesia, and the US.
ICIET2021 was co-sponsored by IEEE, Okayama University (Japan), South China Normal University (China), and the International Academy of Computing Technology (Hong Kong).
For more information about the conference, please click this link: http://www.iciet.org/2021.html.
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