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TRAJECTORY PLANNING FOR AUTOMATED PARKING SYSTEMS USING DEEP REINFORCEMENT LEARNING
Zhuo Du,Qiheng Miao,Changfu Zong 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.4
Deep reinforcement learning (DRL) has been successfully adopted in many tasks, such as autonomous driving and gaming, to achieve or surpass human-level performance. This paper proposes a DRL-based trajectory planner for automated parking systems (APS). A thorough review of literature in this field is presented. A simulation study is conducted to investigate the trajectory planning performance of the parking agent for: (i) different neural-network architectures; (ii) different training set-ups; (iii) efficacy of human-demonstration. Real-time capability of the proposed planner on various embedded hardware platforms is also discussed by the paper, showing promising performance. Insights of the use of DRL for APS are concluded at the end of the paper.
Improved Reliability-Based Iterative Decoding of LDPC Codes Based on Dynamic Threshold
Ma Zhuo,Du Shuanyi 한국전자통신연구원 2015 ETRI Journal Vol.37 No.4
A serial concatenated decoding algorithm with dynamic threshold is proposed for low-density parity-check codes with short and medium code lengths. The proposed approach uses a dynamic threshold to select a decoding result from belief propagation decoding and order statistic decoding, which improves the performance of the decoder at a negligible cost. Simulation results show that, under a high SNR region, the proposed concatenated decoder performs better than a serial concatenated decoder without threshold with an Eb/N0 gain of above 0.1 dB.
Synthesis and Solution Properties of Fluorinated Amphiphilic Polyacrylamide
Fangyuan Zhao,Kai Du,Zhuo Yi,Chao Du,Zhao Fang,Bingquan Mao 한국고분자학회 2015 폴리머 Vol.39 No.3
A series of hydrophobically associating fluorinated amphiphilic polyacrylamide copolymers with remarkably high heat resistance and salt tolerance were synthesized by free radical micellar copolymerization, using acrylamide (AM) and sodium 2-acrylamido-tetradecane sulfonate (AMC14S) as amphiphilic monomers, and 2-(perfluorooctyl) ethyl acrylate (PFHEA) as hydrophobic monomer. The structure of the terpolymer was characterized by FTIR, <SUP>1</SUP>H NMR and <SUP>19</SUP>F NMR. The solution properties of the terpolymers were investigated in details, and the results showed that the terpolymer solution had strong intermolecular hydrophobic association as the concentration exceeded the critical association concentration 1.5 g/L. The terpolymer solution possessed high surface activity, viscoelasticity, excellent heat resistance, salt tolerance and shearing resistance. The viscosity retention rate of copolymer solution was as high as 59.9% under the condition of fresh wastewater, 85℃ and a 60-days aging test.
Pan Li,Zuan-hao Liang,Zhuo Jiang,Ziyou Qiu,Bing Du,Yu-bing Liu,Wen-zhi Li,Li-hao Tan 한국식품과학회 2018 Food Science and Biotechnology Vol.27 No.6
Phthalate plasticizers residue in food is a serious threat to public health. Spores of Ganoderma lucidum are easy to be contaminated with phthalates during collection and processing. In this study, supercritical fluid extraction (SFE) was performed to remove phthalates in spores of G. lucidum, and the effects on acid and peroxide values of spores’ oil were also evaluated. The results showed SFE removed 100% of the residual di-iso-butyl phthalate, di-nbutyl phthalate and di-2-ethylhexyl phthalate in the spores of G. lucidum. No significant differences in polysaccharides content and fatty acid composition were observed between SFE and control spores. However, the triterpenoid extracts of SFE spores had a 7.45% increase, significantly higher than that in control spores. Accelerated oxidation tests further implied that SFE could improve the stability of spores’ oil. Our results suggested SFE is a potential approach to remove phthalate from food related products.