基于聚类的数据加权优化在犯罪预测中的应用

近年来，我国传统暴力犯罪与成年人犯罪呈下降态势，但是，犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力，打击各类违法犯罪事件,本文针对犯罪数据，提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类，然后进行数据降维提取关键属性生成特征数据，继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习，从而预测犯罪案由。实验结果表明，与传统方法相比，本文方法具有更好的预测效果，为公安实践工作中类似案件的侦破和预防，提供新的路径支撑。     

动态高压微射流处理对方竹笋膳食纤维理化及结构特性的影响

以方竹笋中提取的膳食纤维为研究对象，采用动态高压微射流（dynamic high-pressure micro-fluidization, DHPM）在不同压力条件（0，50，100，150，200 MPa）下进行处理，探究其对竹笋膳食纤维（bamboo shoots dietary fiber, BSDF）理化和结构特性的影响。结果表明，随着处理压力的增大，BSDF粒径先增大后减小，当处理压力为150 MPa时，粒径最小，为（370±11） nm，此条件下BSDF的持水力、持油力和膨胀力达到最大，较对照组分别提高了47.74%，50.54%，61.27%，且差异显著（P<0.05）。红外光谱分析表明DHPM处理不会改变BSDF的官能团，但会使BSDF内部的部分氢键断裂和半纤维素、木质素等发生降解；X射线衍射和热重分析表明DHPM处理不会引起BSDF的晶体结构改变，但晶体有序度会下降，进而导致其热稳定性降低；微观结构分析显示DHPM处理会使BSDF颗粒尺寸减小、表面粗糙、组织松散，且当处理压力为200 MPa时，颗粒发生团聚。综上，DHPM可以有效改善BSDF的理化性质，在膳食纤维改性方面具有一定的应用价值。     

光照水电站装设筒形阀分析

筒形阀是一种新型的水轮机进水阀,它与球阀或蝴蝶阀相比较有防止机组飞逸事故扩大效果明显、减轻导叶全关时导水机构的快速破坏并减少漏水量,以及动水开启方便、所需时间短等优点,但对运行条件也有一定的要求。光照水电站是贵州省第1个拟采用筒形阀的电站,为此对装设筒形阀的可行性和必要性进行了认真的分析。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

Effective Location Based Services with Dynamic Data Management in Mobile Environments

With the proliferation of mobile computing technologies, location based services have been identified as one of the most promising target application. We classify mobile information service domains based on feature characteristics of the information sources and different patterns of mobile information access. By carefully examining the service requirements, we identify the dynamic data management problem that must be addressed for effective location based services in mobile environments. We then devise a general architecture and cost model for servicing both location independent and location dependent data. Based on the architecture and cost model, we propose a set of dynamic data management strategies that employs judicious caching, proactive server pushing and neighborhood replication to reduce service cost and improve response time under changing user mobility and access patterns. Detail behavior analysis helps us in precisely capturing when and how to apply these strategies. Simulation results suggest that different strategies are effective for different types of data in response to different patterns of movement and information access. Shiow-yang Wu is an associate professor of the Department of Computer Science and Information Engineering at National Dong Hwa University, Hualien, Taiwan, R.O.C. He received the BS and MS degrees in computer engineering from National Chiao Tung University, Hsinchu, Taiwan, ROC, and the PhD degree in computer science from the University of Texas at Austin in 1984, 1986, and 1995, respectively. His research interests include data/knowledge bases, mobile computing, distributed processing, intelligence information systems, and electronic commerce. Kun-Ta Wu was born in Taipei, Taiwan, R.O.C., in 1976. He received the B.S. degree in computer science from Soochow University, Taipei, Taiwan, R.O.C., in 1999 and the M.S. degree in computer science and information engineering from National Dong Hwa University, Hualien, Taiwan, R.O.C., in 2001. Currently, he is an Assistant Researcher in the Domestic Division at Science and Technology Information Center, National Science Council, R.O.C., as a member of Information Gathering and Analysis Group of National Information and Communication Security Taskforce. His research interests include mobile computing, wireless network and information security.     

A comparison of transformation methods for evaluating two‐dimensional weakly singular integrals

Accurate numerical evaluation of integrals arising in the boundary element method is fundamental to achieving useful results via this solution technique. In this paper, a number of techniques are considered to evaluate the weakly singular integrals which arise in the solution of Laplace's equation in three dimensions and Poisson's equation in two dimensions. Both are two‐dimensional weakly singular integrals and are evaluated using (in a product fashion) methods which have recently been used for evaluating one‐dimensional weakly singular integrals arising in the boundary element method. The methods used are based on various polynomial transformations of conventional Gaussian quadrature points where the transformation polynomial has zero Jacobian at the singular point. Methods which split the region of integration into sub‐regions are considered as well as non‐splitting methods. In particular, the newly introduced and highly accurate generalized composite subtraction of singularity and non‐linear transformation approach (GSSNT) is applied to various two‐dimensional weakly singular integrals. A study of the different methods reveals complex relationships between transformation orders, position of the singular point, integration kernel and basis function. It is concluded that the GSSNT method gives the best overall results for the two‐dimensional weakly singular integrals studied. Copyright © 2002 John Wiley & Sons, Ltd.     

LNG冷量优化集成利用技术

我国将相继在沿海地区建成多个LNG接收站，每年将进口数以千万吨计的LNG，同时携带数着巨额冷量，而这些冷量可用于发电、空气分离、制造干冰、低温冷库等众多领域。基于国外LNG冷量利用现状，指出我国即将展开和实施此项技术还存在着：过程火用损较大，缺乏系统、全面的LNG冷量利用技术的研发指导机制，以及宏观调控力度薄弱等问题，进而提出了发展LNG冷量的集成利用方案，可为此类技术的研发利用提供新思路。以福建即将进口的LNG为例，模拟了空气分离与干冰制备的集成工艺流程，结果表明：福建每年进口的260×10⁴t LNG可以冷却290×10⁴t空气，相当于60000 m³/h的氧气制备规模，还可以生产100×10⁴t的干冰，其过程火用损较小；其剩余的高温位冷量可应用于低温冻结库或冰灯等项目，这对主体装置的实施效果和过程火用损的影响较小。该技术的优点在于可灵活控制冷却空气的液化率，基本不用冷却循环水，流程简单，设备投资少，能耗低等。     

燃气管网动态仿真的研究及应用

研究和了解燃气在管道中的流动，是进行燃气管网系统优化和提高管网输运系统安全性的前提和基础。以流体力学三大守恒方程为基础，建立了等温和非等温条件下的燃气管网稳态和动态仿真理论模型。以有限差分法为基础，得到了上述模型的求解方法，并加入了耗散项，提高了求解方法的稳定性。通过增加初始点和延长出口点的方法，简化了模型的求解。通过在北京六环天然气管网中的初步应用，分别得到了与实际值综合相对误差为1.21％和2.62％的压力和流量仿真值，从而验证了模型及求解方法的可靠性。     

智能动态网络资源分配系统

通过对解决GSM移动通信网络热点区域话务拥塞问题的研究，提出了利用可控功分器实现智能动态网络资源的分配，解决不同种类的话务拥塞问题，并着重讨论了该系统目前的成功运用及前景。     

法国电信集团运营模式研究

中国电信企业经过多年的高速发展，逐渐步入成熟期，增长率下降、利润降低将是必然趋势，因此目前亟需探索新的运营模式，向综合型全业务电信运营商的方向发展。法国电信集团历史悠久，市场转型起步早．其发展经验有许多地方值得借鉴，包括法国电信集团具有特色的品牌战咯、灵活的经营模式、为企业提供全方位服务的经营手段。中国电信企业应积极开展全业务经营，加快发展企业网市场，完善合作运营模式，争取早日走向世界。