H∞ fuzzy integral controller for nonlinear descriptor systems
Conference proceedings article
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
ไม่พบข้อมูลที่เกี่ยวข้อง
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Vorrawan C., Assawinchaichote W.
ผู้เผยแพร่: Hindawi
ปีที่เผยแพร่ (ค.ศ.): 2019
Volume number: 15
Issue number: 2
หน้าแรก: 741
หน้าสุดท้าย: 756
จำนวนหน้า: 16
ISBN: 9781538679104
นอก: 0146-9428
eISSN: 1745-4557
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
Nowadays, the overall well-being is considered to be one of the most important issue. The company has been taking more and more consideration in improving their employees' well-being. The employees also have been taking several approaches to improve their current well-being status. However, the well-being is usually related to the daily activity and behavior, especially in the workplace where it affects stress and mood level. In other words, the quality of a person's well-being is affected by the behavior in a workplace. In this study, we proposed a well-being recognition system where we adopted a deep learning technique to provide a non-invasive monitoring system. We classified the well-being level using three features from two surveys, which covered both stress and mood. For this preliminary study, we trained the model for both generic classification and personalized classification. The personalized approach was taken as a step to provide a personalized health decision support system, which would help raise awareness in users and encourage them to improve their behavior and eventually contribute to a better well-being. We achieved the accuracy of 83% on generic model and 91% on a personalized model. ฉ 2019 IEEE.
คำสำคัญ
Consumer Health, Well-being
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