Growth Mechanism of IT Service Outsourcing Enterprises

与跨国IT公司合作,进行行业内知识学习和跨行业知识溢出是我国IT服务外包企业快速成长的必由之路。本文在综述知识转移过程、环境及影响因素的基础上,分析我国IT服务外包企业的知识学习和知识溢出过程,研究专业化软件开发-集成化产品-与流程结合的行业化解决方案-国际化服务交付中的知识转移特征,得出我国IT服务外包企业的成长机理模型。Knowledge learning and spillover are important tools of rapidly grow by cooperating with outstanding IT multinational enterprise for IT outsourcing vendor enterprise in China. This paper summarizes the process of knowledge transfer, exploits the function of “specialized information technology, multiple services and production, industrial solution scheme, international networking services” of IT service outsourcing enterprise, and addresses the solutions and countermeasures for policy-marker based on knowledge transfer view.国家自然科学基金(70871034);国家社会科学基金(10BTQ019);安徽大学“211”创新团队项目(SKTD010B

可再生能源分布式微网电源规划方法及应用

近年来,可再生能源分布式发电微网技术研究引起国内外广泛关注.本论文将遗传算法应用到风-光-柴-蓄组成的可再生能源分布式微网电源规划中,建立微网电源规划模型及相关约束条件,以满足能量平衡控制、费效率等为最优原则,给出了算法的实现流程.最后,结合案例说明了算法的应用

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies