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Fuzzy Classification for Korean Females’ Lower Body Based on Anthropometric Measurement
Sung Hee Ahn,Yushin Lee,Yong Min Kim,Ilsun Rhiu,Myung Hwan Yun 대한인간공학회 2016 대한인간공학회 학술대회논문집 Vol.2016 No.11
Objective: This study aims to investigate lower body type classification of Korean female using fuzzy clustering method. Background: The knowledge of human body shape is important in product design. Previously, most of studies used crisp classification methods, but the method has limitations to describe a person’s body type. Method: First of all, we collected data required to analyze lower body for Korean females and preprocessed the data. After utilizing factor analysis, we performed fuzzy clustering with four centers. Results: Four factors were found from the factor analysis. Characteristics of four types of lower body were found as well. By age, the composition of body type differed. Conclusion: The younger people and the elderly people belong to a particular lower body type each. Application: It can be helpful for understanding types of lower body for Korean females. The result can be applied to product design.
김재현(Jaehyeon Kim),김유신(Yushin Kim),이세종(Sejong Lee),안세영(Seyoung Ahn),노재원(Jaewon Noh),김종훈(Jonghun Kim),조성현(Sunghyun Cho) 대한전자공학회 2021 대한전자공학회 학술대회 Vol.2021 No.6
Artificial intelligence is being used in a variety of fields, including medicine. But their lack of interpretability and explainability stand as one of the main drawbacks. To solve this problem, explainable artificial intelligence has been studied in healthcare. In this paper, we summarize recent advances in explainable artificial intelligence technologies and introduce the use of explainable artificial intelligence studies in medicine.