Ming-Chuan Chiu

dblp:137/3481 · DBLP profile ↗
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10ranked-venue papers
6as first author
4since 2021 · last 2024
0000-0001-9821-8240ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 7 · 5 first-author · 4 since 2021Human-computer interaction and ubiquitous computing · 2Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
YearPublicationVenuePosition
2024 Integrating object detection and natural language processing models to build a personalized attraction recommendation agent in a smart product service system
Ming-Chuan Chiu, Cheng-Zhou Tsai, Yu-Chen Huang
Adv. Eng. Informatics1
2024 Integrating explainable AI and depth cameras to achieve automation in grasping Operations: A case study of shoe company
Ming-Chuan Chiu, Li-Sheng Yang
Adv. Eng. Informatics1
2024 Connecting humans and machines: Deep integration of advanced HCI in intelligent engineering
Ching-Hung Lee, Fan Li 0015, Ming-Chuan Chiu, Amy J. C. Trappey, Edward Huang, Pisut Koomsap
Adv. Eng. Informatics3
2022 A novel directional object detection method for piled objects using a hybrid region-based convolutional neural network
Ming-Chuan Chiu, Ho-Yen Tsai, Jing-Er Chiu
Adv. Eng. Informatics1
2020 Design a personalised product service system utilising a multi-agent system
Ming-Chuan Chiu, Chi-Hsuan Tsai
Adv. Eng. Informatics1
2018 Utilizing text mining and Kansei Engineering to support data-driven design automation at conceptual design stage
Ming-Chuan Chiu, Kong-Zhao Lin
Adv. Eng. Informatics1
2017 Develop a personalized intelligent music selection system based on heart rate variability and machine learning
Ming-Chuan Chiu, Li-Wei Ko
Multim. Tools Appl.1
2015 A case-based method for service-oriented value chain and sustainable network design
Ming-Chuan Chiu
Adv. Eng. Informatics2
2014 Service dissatisfaction detection and service recovery design with a case study of kinect health management motion sport game
abstract
The goal of service recovery is to make immediate response when service failures result in customer dissatisfaction or complaints. However, it is difficult to detect service failures and customer dissatisfactions easily because customers might not express their true reception. Hence, this study builds a logistical regression model to detect the effectiveness of service and provide service recovery suggestions when customer satisfaction level is not achieved. A health management motion sport game is applied to present the proposed method. An experiment is conducted to collected objective physiological data (e.g., heart rate, blood pressure) and subjective user ratings of perceived exertion after the sport game. The contribution of this study mainly focuses on the usage of the logistical regression model built to assure the effectiveness of exercise. Hence, the users can follow the results of the suggestions, which are in accordance with different effectiveness of exercise, suited for them to effectively maintain good health status.
Yi-Jie Chang, Po-Hsin Huang, Ming-Chuan Chiu
CSCWD3
2014 Integrating psychological and physiological techniques to measure and improve usability an empirical study on health management sport applied product
abstract
This research aimed to evaluate an approach of measuring, monitoring and auditing the usability of health care product. Based on the ergonomic perspective and principles, the interactions of the user and motion sports will be studied by using physiological data that gathered by heart rate sensor and eye tracker. Furthermore, the questionnaires used in this research are integrated from the proposed questionnaires as well as applied to reveal the subjective cognition of product usability. This research made use and analyzed the objective and subjective data simultaneously so as to gain more insightful information of users, where we took physiological data as objective data and questionnaire result as subjective data. Therefore, we considered that using eye activity data, heart rate data, mental workload data and questionnaires data was a complete and detailed approach to evaluate usability. Furthermore, we can provide advices for improving the usability based on the result of the proposed method by this research.
Wei-Ying Cheng, Po-Hsin Huang, Ming-Chuan Chiu
CSCWD3