Special Session

We welcome the proposal of a special session where the researchers present and discuss specific topics.
The special session has to gather three or more papers. In the special session, all presentations should be made as oral presentations.
The organizer(s) of the special session have to submit following information to M. Fukumoto via e-mail (fukumoto_AT_fit.ac.jp) by February 21st, 2023February 7th, 2023:
(1) the name of the organizer(s)
(2) the title of the special session
(3) purpose of the organized session
(4) the tentative title and author(s) of the papers that will be presented in the special session.

Proposed Special Sessions:
Special Session 1
Organizers: Teruhisa Hochin, Akihiro Ogino, Makoto Fukumoto, Yuichiro Kinoshita
Title: Wellbeing and Affective Engineering
Purpose: Advances in information and communication technologies have brought tremendous benefits to us. These benefits include improvement of the way of life. Information and communication technologies may help us to live more comfortably and happily. Computers might assist us to spend time in a wellbeing state. The methods for assisting people to be wellbeing state should be clarified, developed, and applied to our real lives. This organized session treats all aspects of affective engineering for wellbeing, which include clarifying the principle of wellbeing based on affective engineering, realizing wellbeing, and broadening the applications of wellbeing. This organized session encourages participants to discuss about their research results, exchange ideas, and promote research on wellbeing and affective engineering.
Special Session 2
Organizers: Nobuyuki Nishiuchi, Makoto Fukumoto
Title: Machine Learning Using Biometric Data and Kansei Data
Purpose: Machine learning has been used in various research fields in recent years. Many studies applying machine learning have been reported in research fields such as image recognition, speech recognition, and natural language processing. On the other hand, there is a lot of research on human understanding, classification, and authentication by measuring human data, but research approaches that apply machine learning to data analysis have not yet been fully implemented. This organized session will focus on the research that applies machine learning using Biometric Data and Kansei Data which mean human data related to physical, behavioral, physiological, and psychological characteristics. We will discuss various know-how such as points to note, problems, effects, and effectiveness in applying machine learning.