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- 저자 : Huixi Zhang (검색결과 4 건)
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Huixi Li,Zhichao Zhang,Jing Peng,Zhongcheng Xin,Meng Li,Bicheng Yang,Dong Fang,Yuan Tang,Yinglu Guo 대한비뇨의학회 2019 Investigative and Clinical Urology Vol.60 No.5
Purpose: To investigate whether treatment with low-energy shock wave (LESW) alleviates pain and bladder dysfunction in a mouse model of uroplakin 3A (UPK3A)-induced interstitial cystitis/painful bladder syndrome (IC/PBS). Materials and Methods: Forty female BALB/c mice were divided into four groups (n=10/group): Sham, Sham+LESW, UPK3A, and UPK3A+LESW. At 6 weeks of age, mice were injected with an emulsion containing water and complete Freund's adjuvant with (UPK3A and UPK3A+LESW groups) or without (Sham and Sham+LESW groups) 200 µg of UPK3A. At 10 weeks, mice received a second dose of Freund's adjuvant to booster immunization. At 12 weeks, mice underwent pain assessment and a frequency volume chart (FVC) test as the pretreatment assessment. LESW treatment and pain assessment were conducted from 13 to 15 weeks. One week after the final treatment, pain assessment and the FVC were conducted again as the post-treatment assessment. Mice were euthanized and sacrificed at 17 weeks. Results: The presence of tactile allodynia and bladder dysfunction was significant in the UPK3A-injected mice. LESW raised the pain threshold and improved bladder function with decreased urinary frequency and increased mean urine output. Expression and secretion of local and systemic inflammatory markers, including tumor necrosis factor-α (TNF-α) and nerve growth factor (NGF), increased after UPK3A immunization. These markers were significantly decreased after LESW treatment (p<0.05). Conclusions: LESW treatment attenuated pain and bladder dysfunction in a UPK3A-induced model of IC/PBS. Local and systemic inflammation was partially controlled, with a reduced number of infiltrated inflammatory cells and reduced levels of TNF-α and NGF.
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Research on the Management Strategy of the Last Level Cache Sharing Multi-Core Processor
Yuhuai Wang,Huixi Zhang,Yaping Sun,Qihui Wang 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.5
Effective allocation of shared resources limited is a key problem for chip multiprocessors. As the processor core growth in the scale, multi thread for the shared resource limited system competition will become more intense, the performance of the system will also be more significant. In order to alleviate this problem, a fair and effective multi thread shared resources allocation scheduling algorithm is important. In all kinds of shared resources, the largest effect on the system performance is the shared cache and DRAM system. There are essential differences between the last level cache and a cache. The goal of a cache design is to provide fast data processor which requires high access speed. However, the object of the last level cache is to save data in the chip as much as possible, and the access speed requirements are not too high, it is more subject to the plate number of available transistors. Management level cache LRU strategy and its approximate algorithm are not applicable to the large capacity last level cache for traditional. It may cause destructive interference between threads, cache thrashing of stream media program lead, which will lead to a decline in the performance of processor. This paper focuses on the analysis of some hot problems of the last level cache management in the process of the large capacity of multi-core platform sharing, and puts forward the corresponding costs less.
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Load Forecasting Research of Power System Based on Fuzzy Sets Algorithm
Qihui Wang,Yuhuai Wang,Huixi Zhang,Yaping Sun 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6
In this paper, adjust the system parameters back-propagation algorithm based on fuzzy similarity interval type proposed by the fuzzy rule base to streamline redundant fuzzy sets, we can also merge with the means to reduce the number of redundant fuzzy rules, then singular value decomposition method is preferred fuzzy rules. The algorithm can effectively eliminate the adverse effects caused by redundant fuzzy rule, which improve the interpretability of fuzzy rules to reduce the computational complexity of the fuzzy reasoning process, and to improve the approximation accuracy of the system. Based on the long-term and short-term load power load characteristics analysis, to identify the influence of the load itself changes and related factors, gray system theory, neural network model and chaotic time series methods, models and methods for forecasting power load range were research. Examples verified, interval prediction has better precision, demonstrate the effectiveness of the interval prediction algorithm, the research results can be used in power market analysis and forecasting systems, power system operation and provide scientific basis for management decisions.
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Improved Particle Swarm Optimization Algorithm for Optimization of Power Communication Network
Yuhuai Wang,Qihui Wang,Huixi Zhang,Kang An,Xia Ye,Yaping Sun 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.1
Based on particle swarm optimization (PSO) algorithm and its power system reactive power optimization method to in-depth study and research proposed a new hybrid particle swarm optimization algorithm (HPSO). Algorithm combines the differential evolution algorithm and simulated annealing algorithm and particle swarm optimization algorithm, in particle searching optimal except for tracking individual and global, and tracks produced by particle information difference of the three value. At the same time, when the particle search space of one dimension speed lower than the setting value will be re initialized the dimensional particle velocity and the particle of differential evolution mutation. For the crossover and mutation operations, new solution may be worse than the original solution to, the introduction of simulated annealing algorithm, the metropolis rule in a certain extent accept bad solutions, allows the target function in a certain degree of deterioration, practical calculation is not according to the probability to choose the poor solution, but rather the judgment target function difference is less than allows the target function deterioration range. Hybrid particle swarm optimization algorithm combines the advantages of particle swarm optimization algorithm, differential evolution algorithm and simulated annealing algorithm, to maintain the diversity of particles, has very strong practicability.
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