Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Kuei‐Chen Chiu"'
Autor:
Kuei-Chen Chiu1,2 tinachiu@g2.usc.edu.tw
Publikováno v:
Asia Pacific Management Review. Sep2024, Vol. 29 Issue 3, p273-283. 11p.
Publikováno v:
Managerial and Decision Economics. 44:942-959
A STUDY OF SOFTWARE RELIABILITY GROWTH WITH IMPERFECT DEBUGGING FOR TIME-DEPENDENT POTENTIAL ERRORS.
Publikováno v:
International Journal of Industrial Engineering. 2019, Vol. 26 Issue 3, p376-393. 18p.
Autor:
Kuei-Chen Chiu
Publikováno v:
Journal of Facilities Management.
Purpose This paper aims to answer these questions: “Is the public adopting energy-saving and water-saving facilities because they want to save energy and water in their psychological perception?”, “Is it convenient to use energy-saving and wate
Publikováno v:
Journal of Systems and Software. 188:111267
Publikováno v:
IEEM
This research uses big data analysis to find the key factors of copper futures price fluctuations, successfully predicts copper price fluctuations, and applies them to the purchase strategy of copper raw materials for plant construction to help reduc
Autor:
Kuei-Chen Chiu
Publikováno v:
IEEM
This study analyzes affective expression in dream log by text mining, guide participants focusing on the affective words in their dream log to release their emotions. This study provided a new method for exploring the correlation between dream and st
Publikováno v:
IEEM
This study aims to explore the attitudes of the public toward water-saving equipment. We also explore the impact of affect factor, behavior factor, and cognition factor on the acceptance of the public toward water-saving equipment. We conduct a quest
Publikováno v:
IEEM
This paper aims to explore the consistency between conservation cognition and behavior toward adopting energy-saving facilities by establishing a canonical correlation model between acceptance and attitudes toward using energy-saving facilities with
Autor:
Kuei-Chen Chiu
Publikováno v:
Journal of Industrial and Production Engineering. 32:369-386
The proposed models consider multiple change-points in software testing/debugging process with time-varying learning effects and are able to reasonably describe the S and exponential-shaped debugging process, simultaneously. The proposed models inclu