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Application of Multiobjective Genetic Algorithms for Optimizing Aircraft Crew Pairing Problems
Tung-Kuan Liu,Chiu-Hung Chen,Jyh-Horng Chou,Shinn-Horng Chen,Ta-Yuan Chou 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper develops a method of inequalities-based multiobjective genetic algorithm (MMGA) to solve the crew pairing problems which mainly assign the crew members to each flight segment of a given time period, while complying with a variety of work regulations and collective agreements.There are various objectives to be addressed here and formulated into mathematical equations including legal turn-around time, dead-head, layover, flying time and flying duty period. Through the verification of the real-world study case, the proposed method can solve the crew pairing problems, and obtain feasible solutions which are more useful for practical use.
Kuan‑Jung Chung,Cheng‑Han Dai,Tung‑Chun Chiang,June‑Jia Xie,Ming-Tzer Lin 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.9
This study adopted AI to identify the normal and abnormal vibration signals generated during robotic grinding. This study classified four fundamental factors affecting grinding into three levels to obtain a widely used result and designed an L9(34)orthogonal array for the grinding experiment. During experimentation, part of the grinding wheels was added weight to produce abnormal vibration signals, which an accelerometer would measure. The study transformed the collected vibration signals into recurrence plots and conducted model training with VGG16 CNN architecture. Finally, this study tested a model with 89.6% training accuracy. The results showed the model could identify whether the recurrence plots stand for normal or abnormal vibrations, with an accuracy of 85%. This means it could predict normal and abnormal grinding conditions and help avoid problems caused by abnormal vibrations.
Daw-Tung Lin,Kuan-Yu Wu 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.3
Seamless object tracking in wide area is an important and yet challenging issue of intelligent visual surveillance multi-camera collaboration tracking approach has been becoming attractive. In this work, a flexible and integrated system is constructed for object tracking using multiple cameras either with overlapping fields of views (FOVs), non-overlapping FOVs or mixed configurations for wide areas surveillance. The Kalman filter is applied for object tracking in a single camera and object motion prediction is implemented across blind regions for non-overlapping FOVs. Furthermore, a client and server architecture is constituted using TCP/IP network. The FOV lines are used to guide camera switching. In addition, we integrate various features for object matching. Finally, this system can track objects in a wide area no matter the FOVs are overlapping, non-overlapping or mixed situations.
Design of disk cam mechanisms with a translating follower having symmetrical double-concave faces
Yu-Hsuan Chuang,Kuan-Lun Hsu,Wen-Tung Chang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.8
This paper presents an analytical approach for designing disk cam mechanisms with an improved translating follower having symmetrical double-concave faces. The doubleconcave faces of such a follower can increase the actual contact area between the cam and the follower. Additionally, during the dwell periods of the follower motion, both the concave faces of the follower can simultaneously contact the cam profile so as to share the carried loading. Such beneficial characteristics can result in a lower level of contact stress between the cam and the follower. Numerical examples are provided to illustrate the nature and the advantage of this improved follower.