如何利用Invisible-web获取更多的网络信息资源

在浩瀚如海的网络世界里,信息资源犹如海洋生物,大大小小,无孔不入,如何能够快速而准确地找到并获取自己所需的信息,成为我们这个时代最需解决的根本问题之一。当然,利用各种搜索引擎可以查找到很多信息资源,但是也有一些信息通过搜索引擎是无法找到的,它们隐藏在这个网络世界的某个角落,因为某种原因而不为大多人所熟知,但是这些信息本身却有着很高的使用价值。美国的Sherman·C等人把这些资源命名为“看不见的网站（Invisible-web）”。“看不见的网站”里拥有信息检索人员难以置信的有价值的资源。本文阐述了“看不见的网站”的含义及价值,指出信息检索人员应该如何有效利用“看不见的网站”资源,最后提供一些查找“看不见网站”的途径与工具。     

分布矩形光束的多棱镜面反射器道路灯具

本文介绍了道路灯具反射器的演变及现状,提出了一种可分布矩形光束的多棱镜面反射器道路灯具的设计原理,并分析其照明质量及低杆安装的可行性,展望了它在道路照明中的应用前景。     

Network partitioning using harmony search and equivalencing for distributed computing

Power system has a highly interconnected network that requires intense computational effort and resources for centralized control. Distributed computing needs the systems to be partitioned optimally into clusters. The network partitioning is an optimization problem whose objective is to minimize the number of nodes in a cluster and the tie lines between the clusters. Harmony Search(HS) Algorithm is one of the recently developed meta heuristic algorithms that can be applied to optimization problems. In this work, the HS algorithm is applied to the network partitioning problem and power flow based equivalencing is done to represent the external system. Simulation is done on IEEE Standard Test Systems. The algorithm is found to be very effective in partitioning the system hierarchically and the equivalencing method gives accurate results in comparison to the centralized control.     

自然语言处理在搜索引擎信息检索中的应用

随着Internet的发展，网络搜索的作用越来越重要，但目前网络搜索的精确度不高，在查全率和查准率方面都有待提高。本文提出了一种信息检索模型，以自然语言的形式进行检索，得到用户想要得到的内容，进而提高查询的准确性。     

How causal knowledge simplifies decision-making

Making decisions can be hard, but it can also be facilitated. Simple heuristics are fast and frugal but nevertheless fairly accurate decision rules that people can use to compensate for their limitations in computational capacity, time, and knowledge when they make decisions [Gigerenzer, G., Todd, P. M., & the ABC Research Group (1999). Simple Heuristics That Make Us Smart. New York: Oxford University Press.]. These heuristics are effective to the extent that they can exploit the structure of information in the environment in which they operate. Specifically, they require knowledge about the predictive value of probabilistic cues. However, it is often difficult to keep track of all the available cues in the environment and how they relate to any relevant criterion. This problem becomes even more critical if compound cues are considered. We submit that knowledge about the causal structure of the environment helps decision makers focus on a manageable subset of cues, thus effectively reducing the potential computational complexity inherent in even relatively simple decision-making tasks. We review experimental evidence that tested this hypothesis and report the results of a simulation study. We conclude that causal knowledge can act as a meta-cue for identifying highly valid cues, either individual or compound, and helps in the estimation of their validities.     

控制系统模型简化及参数寻优的仿真

本文应用随机数直接搜索的单纯形最优化方法将系统高阶模型简化为低阶等效模型，并对控制系统调节器参数进行在线寻优，该方法的主要特点是：编程简单，有较宽的初值选择范围，搜索的结果可靠。