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Ji-Hong Li, Hyungjoo Kang, Min-Gyu Kim, Mun-Jik Lee, Gun Rae Cho and Han-Sol Jin
In this paper, we present a 3D formation control scheme for a group of torpedo-type underactuated autonomous underwater vehicles (AUVs). These multiple AUVs combined with an unmanned surface vessel (USV) construct a sort of star-topology acoustic communi...
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Sung-ho Hur and Yiza-srikanth Reddy
The estimation of variables that are normally not measured or are unmeasurable could improve control and condition monitoring of wind turbines. A cost-effective estimation method that exploits machine learning is introduced in this paper. The proposed me...
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Kanishkavikram Purohit, Shivangi Srivastava, Varun Nookala, Vivek Joshi, Pritesh Shah, Ravi Sekhar, Satyam Panchal, Michael Fowler, Roydon Fraser, Manh-Kien Tran and Chris Shum
The proliferation of electric vehicle (EV) technology is an important step towards a more sustainable future. In the current work, two-layer feed-forward artificial neural-network-based machine learning is applied to design soft sensors to estimate the s...
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Yingying Wang, Yibin Li, Yong Song and Xuewen Rong
The convolutional neural network (CNN) has been widely used in image recognition field due to its good performance. This paper proposes a facial expression recognition method based on the CNN model. Regarding the complexity of the hierarchic structure of...
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Yung-Chih Lin, Kung-Da Wu, Wei-Cheng Shih, Pao-Kai Hsu and Jui-Pin Hung
This study presents surface roughness modeling for machined parts based on cutting parameters (spindle speed, cutting depth, and feed rate) and machining vibration in the end milling process. Prediction models were developed using multiple regression ana...
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