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- 저자 : ( Wenxue Ge ) (검색결과 2 건)
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Jinle Xiang,Wenxue Zhu,Junqi Han,Zhixi Li,Hanjin Ge,Dehui Lin 한국식품과학회 2012 Food Science and Biotechnology Vol.21 No.4
Chinese raisin tree (Hovenia dulcis) peduncle is a wonderful food material for fermented food for high contents of sugars and a variety of organic acids. The organic acids in the fresh peduncle, fermented wine, and vinegar were identified and quantified by HPLC, and changes in biochemical parameters and organic acids in the fermentation process were studied. Skin-on fermentation was carried out in the alcoholic fermentation, and 9identified organic acids fluctuated by physical or biochemical reactions during the alcoholic fermentation. Submerged fermentation was carried out in the acetic fermentation. It took 72 h to finish the 1st cycle of acetification with the titratable acidity 5.42%(w/v), and 30h to finish the 2nd cycle. The contents of acetic acid, formic acid, and α-ketoglutaric acid increased, while the rest identified organic acids decreased in the acetification process. The fermentation developed in this study appeared to be a practical processing method for Chinese raisin tree peduncles.
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Quantum Bacterial Foraging Optimization for Cognitive Radio Spectrum Allocation
( Fei Li ),( Jiulong Wu ),( Wenxue Ge ),( Wei Ji ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.2
This paper proposes a novel swarm intelligence optimization method which integrates bacterial foraging optimization (BFO) with quantum computing, called quantum bacterial foraging optimization (QBFO) algorithm. In QBFO, a multi-qubit which can represent a linear superposition of states in search space probabilistically is used to represent a bacterium, so that the quantum bacteria representation has a better characteristic of population diversity. A quantum rotation gate is designed to simulate the chemotactic step for the sake of driving the bacteria toward better solutions. Several tests are conducted based on benchmark functions including multi-peak function to evaluate optimization performance of the proposed algorithm. Numerical results show that the proposed QBFO has more powerful properties in terms of convergence rate, stability and the ability of searching for the global optimal solution than the original BFO and quantum genetic algorithm. Furthermore, we examine the employment of our proposed QBFO for cognitive radio spectrum allocation. The results indicate that the proposed QBFO based spectrum allocation scheme achieves high efficiency of spectrum usage and improves the transmission performance of secondary users, as compared to color sensitive graph coloring algorithm and quantum genetic algorithm.
ScienceON
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