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Simulation Study on Parameters of SLF Chaotic Neural Network Model
Yonggang Ye 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.1
A novel chaotic-neuron model is presented by introducing the non-monotonous activation function which is composed of the Legendre function and the Sigmoid function. The reversed bifurcation of the chaotic neuron model is given and analyzed, meanwhile, how do parameters influence the network convergence speed is discussed. Based on the neuron model, the piecewise simulated annealing SLF chaotic neural network was made by introducing the simulated annealing idea, the model improve the convergence speed, at the same time, the precision of this network have not being influenced. The simulation experiment of function optimization and TSP problem verify the effectiveness of the segmented simulated annealing strategy.
Identification and management the financial risks of accumulator
Yonggang Ye,Siying Lv 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10
This paper focuses on using building block approach to identify and management financial risks of acumulator which is a kind of high-riskand complex financial derivative. When the underlying asset pricek rise, the investors could earn a lot from accumulator contracts, on the contrary, there are huge potential risks if the price falls. At present, the accumulator causes enormous losses to lots of investors, eve resulting in bankruptcy. These investors were not fully aware of the potential risks. This paper uses financial building blocks approach to decompose the accumulator into a number of well-known financial derivatives, helping investors to analyze the potential investment risks of accumulator contracts in different economic situations. Then base on the essential characteristics of accumulator, this paper proposes and testifies the proposal of hedging, making investors be fully aware of the risks of accumulator and managing the financial risks.
Qin Ye,Yonggang Wang,Peng Du,Renbao Gan,Zhimin Li 한국생물공학회 2005 Biotechnology and Bioprocess Engineering Vol.10 No.2
Secretion of the expressed heterologous proteins can reduce the stress to the host cells and is beneficial to their recovery and purification. In this study, fed-batch cultures of Escherichia coli YK537 (pAET-8) were conducted in a 5-L fermentor for the secretory production of human epidermal growth factor (hEGF) whose expression was under the control of alkaline phosphatase promoter. The effects of feeding of glucose and complex nitrogen sources on hEGF production were investigated. When the fed-batch culture was conducted in a chemically defined medium, the cell density was 9.68 g/L and the secreted hEGF was 44.7 mg/L in a period of 60 h. When a complex medium was used and glucose was added in pH-stat mode, the secreted hEGF was improved to 345 mg/L. When the culture was fed with glucose at a constant specific rate of 0.25 gg-1h-1, hEGF reached 514 mg/L. The effects of adding a solution containing yeast extract and tryptone were further studied. Different rate of the nitrogen source feeding resulted in different levels of phosphate and acetic acid formation, thus affected hEGF expression. At the optimal feeding rate, hEGF production achieved 686 mg/L.
Wang Yonggang,Du Peng,Gan Renbao,Li Zhimin,Ye Qin The Korean Society for Biotechnology and Bioengine 2005 Biotechnology and Bioprocess Engineering Vol.10 No.2
Secretion of the expressed heterologous proteins can reduce the stress to the host cells and is beneficial to their recovery and purification. In this study, fed-batch cultures of Escherichia coli YK537 (pAET-8) were conducted in a 5-L fermentor for the secretory production of human epidermal growth factor (hEGF) whose expression was under the control of alkaline phosphatase promoter. The effects of feeding of glucose and complex nitrogen sources on hEGF production were investigated. When the fed-batch culture was conducted in a chemically de-fined medium, the cell density was 9.68 g/L and the secreted hEGF was 44.7 mg/L in a period of 60 h. When a complex medium was used and glucose was added in pH-stat mode, the secreted hEGF was improved to 345 mg/L. When the culture was fed with glucose at a constant specific rate of $0.25\;gg^{-1}h^{-1}$, hEGF reached 514 mg/L. The effects of adding a solution containing yeast extract and tryptone were further studied. Different rate of the nitrogen source feeding resulted in different levels of phosphate and acetic acid formation, thus affected hEGF expression. At the optimal feeding rate, hEGF production achieved 686 mg/L.
Microflame diffusion properties of AP/HTPB propellant under binder width effects
Kaixuan Chen,Xiaochun Xue,Yonggang Yu,Zhenwei Ye 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.2
The present study proposes a method to estimate the microflame properties of ammonium perchlorate/hydroxyl-terminated polybutadiene (AP/HTPB) propellant at different binder widths. A 3D random particle packing is generated by the Monte Carlo method. A transformation from Miller packing to sandwich model is used by the dual slicing technique. The gassolid coupling model and the two-step BDP flame model in the combustion field are established to study the influence of kinetic chemical and fluid diffusion process on the micrflame properties. Finally, the mathematical relationships of the burning rate br and the final flame height H 3on the HTPB thickness D are obtained by analyzing and fitting combustion processes of multiple AP/HTPB propellants, namely, b+1.22D 2 -13.07D+67.73.
Instance segmentation with pyramid integrated context for aerial objects
Juan Wang,Liquan Guo,Minghu Wu,Guanhai Chen,Zishan Liu,Yonggang Ye,Zetao Zhang 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.3
Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.