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RISS 인기검색어
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- 저자 : Pingyuan Xu (검색결과 5 건)
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Artificial Neural Network Based Mission Planning Mechanism for Spacecraft
Li, Zhaoyu,Xu, Rui,Cui, Pingyuan,Zhu, Shengying The Korean Society for Aeronautical Space Sciences 2018 International Journal of Aeronautical and Space Sc Vol.19 No.1
The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.
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Artificial Neural Networks-Based Mission Planning Mechanism for Spacecraft
Zhaoyu Li,Rui Xu,Pingyuan Cui,Shengying Zhu 한국항공우주학회 2018 International Journal of Aeronautical and Space Sc Vol.19 No.1
The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.
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Correction to: Artificial Neural Network Based Mission Planning Mechanism for Spacecraft
Zhaoyu Li,Rui Xu,Pingyuan Cui,Shengying Zhu 한국항공우주학회 2018 International Journal of Aeronautical and Space Sc Vol.19 No.3
The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.
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Yaru Li,Shuchen Zhang,Ziwei Zhu,Ruonan Zhou,Pingyuan Xu,Lingyan Zhou,Yue Kan,Jiao Li,Juan Zhao,Penghua Fang,Xizhong Yu,Wenbin Shang 고려인삼학회 2022 Journal of Ginseng Research Vol.46 No.4
Background: Ginsenoside Rb1 (GRb1) is capable of regulating lipid and glucose metabolism through itsaction on adipocytes. However, the beneficial role of GRb1-induced up-regulation of adiponectin in liversteatosis remains unelucidated. Thus, we tested whether GRb1 ameliorates liver steatosis and insulinresistance by promoting the expression of adiponectin. Methods: 3T3-L1 adipocytes and hepatocytes were used to investigate GRb1's action on adiponectinexpression and triglyceride (TG) accumulation. Wild type (WT) mice and adiponectin knockout (KO)mice fed high fat diet were treated with GRb1 for 2 weeks. Hepatic fat accumulation and function as wellas insulin sensitivity was measured. The activation of AMPK was also detected in the liver andhepatocytes. Results: GRb1 reversed the reduction of adiponectin secretion in adipocytes. The conditioned medium(CM) from adipocytes treated with GRb1 reduced TG accumulation in hepatocytes, which was partlyattenuated by the adiponectin antibody. In the KO mice, the GRb1-induced significant decrease of TGcontent, ALT and AST was blocked by the deletion of adiponectin. The elevations of GRb1-induced insulinsensitivity indicated by OGTT, ITT and HOMA-IR were also weakened in the KO mice. The CM treatmentsignificantly enhanced the phosphorylation of AMPK in hepatocytes, but not GRb1 treatment. Likewise,the phosphorylation of AMPK in liver of the WT mice was increased by GRb1, but not in the KO mice. Conclusions: The up-regulation of adiponectin by GRb1 contributes to the amelioration of liver steatosisand insulin resistance, which further elucidates a new mechanism underlying the beneficial effects ofGRb1 on obesity
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