Balancing reduction of linear systems having multiple delays

Abstract

In this paper we apply the balancing reduction method to derive reduced‐order models for linear systems having multiple delays. The time‐domain balanced realization is achieved through computing the controllability and observability gramians in the frequency domain. With the variable transformation s = i tan(θ/2), the gramians of linear multi‐delay systems can be accurately evaluated by solving first‐order differential equations over a finite domain. The proposed approach is computationally superior to that of using the two‐dimensional realization of delay differential systems.     

Responding to Change: Foundations for an Integrated Regional Approach to Community Safety and Social Cohesion

Issues relating to crime and community safety attract much media and political attention in Australia. However, responses are usually seen to be reactive and punitive. Integrative and proactive collaborative initiatives, involving community members as key stakeholders, have the potential to facilitate more effective and efficient outcomes. This study, undertaken in collaboration with a regional community safety network, was prompted through community safety concerns associated with predicted population growth in the region, and the complex and interrelated nature of many safety issues. Research results suggest three key areas will need to be addressed.     

选煤厂虚拟现实仿真系统的设计与实现

文章介绍了基于虚拟现实技术开发的选煤厂虚拟现实仿真系统的架构及其关键技术,详细阐述了仿真系统的实现方式。     

Electric load forecasting by using dynamic neural network

Electrical energy is fundamental for the wellbeing and for the economic development of any country. However, all countries must ensure access to essential resources and ensure the continuity of its supply. Due to the non-storable nature of electrical energy, the amount of consumed active power should always be equal the produced active power just to avoid power system frequency deviation problem. In order to keep the relationship production–consumption relation in compliance with different standards and to secure profitable operations of power system, electric load consumption must be predicted and controlled instantaneously. Several statistical and classical techniques are proposed in the literature but unfortunately all these methods are not accurate in a satisfactory manner. In this paper, a dynamic neural network is used for the prediction of daily power consumption. The suitability and the performance of the proposed approach is illustrated and verified with simulations on load data collected from French Transmission System Operator (RTE) website. The obtained results show that the accuracy and the efficiency are improved comparatively to conventional methods widely used in this field of research.     

Reconstruction of graphs based on random walks

The analysis of complex networks is of major interest in various fields of science. In many applications we face the challenge that the exact topology of a network is unknown but we are instead given information about distances within this network. The theoretical approaches to this problem have so far been focusing on the reconstruction of graphs from shortest path distance matrices. Often, however, movements in networks do not follow shortest paths but occur in a random fashion. In these cases an appropriate distance measure can be defined as the mean length of a random walk between two nodes — a quantity known as the mean first hitting time.In this contribution we investigate whether a graph can be reconstructed from its mean first hitting time matrix and put forward an algorithm for solving this problem. A heuristic method to reduce the computational effort is described and analyzed. In the case of trees we can even give an algorithm for reconstructing graphs from incomplete random walk distance matrices.     

路易斯·康的话语方式和修辞策略

以路易斯·康的论文《Order Is》为例，对法则问题及其研究方法的未来走向进行了思考。     

TEG—a hybrid approach to information extraction

This paper describes a hybrid statistical and knowledge-based information extraction model, able to extract entities and relations at the sentence level. The model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labour by relying on statistics drawn from a training corpus. The implementation of the model, called TEG (trainable extraction grammar), can be adapted to any IE domain by writing a suitable set of rules in a SCFG (stochastic context-free grammar)-based extraction language and training them using an annotated corpus. The system does not contain any purely linguistic components, such as PoS tagger or shallow parser, but allows to using external linguistic components if necessary. We demonstrate the performance of the system on several named entity extraction and relation extraction tasks. The experiments show that our hybrid approach outperforms both purely statistical and purely knowledge-based systems, while requiring orders of magnitude less manual rule writing and smaller amounts of training data. We also demonstrate the robustness of our system under conditions of poor training-data quality. Ronen Feldman is a senior lecturer at the Mathematics and Computer Science Department of Bar-Ilan University in Israel, and the Director of the Data Mining Laboratory. He received his B.Sc. in Math, Physics and Computer Science from the Hebrew University, M.Sc. in Computer Science from Bar-Ilan University, and his Ph.D. in Computer Science from Cornell University in NY. He was an Adjunct Professor at NYU Stern Business School. He is the founder of ClearForest Corporation, a Boston based company specializing in development of text mining tools and applications. He has given more than 30 tutorials on next mining and information extraction and authored numerous papers on these topics. He is currently finishing his book “The Text Mining Handbook” to the published by Cambridge University Press. Benjamin Rosenfeld is a research scientist at ClearForest Corporation. He received his B.Sc. in Mathematics and Computer Science from Bar-Ilan University. He is the co-inventor of the DIAL information extraction language. Moshe Fresko is finalizing his Ph.D. in Computer Science Department at Bar-Ilan University in Israel. He received his B.Sc. in Computer Engineering from Bogazici University, Istanbul/Turkey on 1991, and M.Sc. on 1994. He is also an adjunct lecturer at the Computer Science Department of Bar-Ilan University and functions as the Information-Extraction Group Leader in the Data Mining Laboratory.     

基于XML动态网站的架构与实现

基于XML的动态网站解决了传统的web网站的客户端无法一次传送太多数据的问题，实现了XML数据的双向传递，大大减轻了服务器的工作量，达到平衡传送与接收端工作量的目标。     

一种基于传呼的PDA信息更新方式

交通信息系统PDA为了使内部信息具有实时性．并为降低服务成本，不使用GPRS或其它更新方式，而是使用传呼接收电路．实时更新铁路、民航交通信息。本文简要介绍了此功能实现所采用的硬件结构、通信协议及处理方式。     

现代软件工程在现代软件开发中的合理应用

从一个角度分析了现代软件体系结构对现代软件工程方法的影响，指出由RDBMs提供数据服务的C/S结构的软件开发中，使用面向对象软件工程方法并无很大优势，使用传统软件工程方法是一种较好的选择；由RDBMs提供数据服务的三层结构的软件开发中，业务逻辑层组件的分析和设计使用面向对象软件工程方法是合适的，但是也不排斥传统软件工程方法，不宜盲目使用面向对象的软件工程方法、UML和RUP。