Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.     

Merging uncertain information with semantic heterogeneity in XML

Semistructured information can be merged in a logic-based framework [6, 7]. This framework has been extended to deal with uncertainty, in the form of probability values, degrees of beliefs, or necessity measures, associated with leaves (i.e. textentries) in the XML documents [3]. In this paper we further extend this approach to modelling and merging uncertain information that is defined at different levels of granularity of XML textentries, and to modelling and reasoning with XML documents that contain semantically heterogeneous uncertain information on more complex elements in XML subtrees. We present the formal definitions for modelling, propagating and merging semantically heterogeneous uncertain information and explain how they can be handled using logic-based fusion techniques. Anthony Hunter received a B.Sc. (1984) from the University of Bristol and an M.Sc. (1987) and Ph.D. (1992) from Imperial College, London. He is currently a reader in the Department of Computer Science at University College London. His main research interests are: Knowledge representation and reasoning, Analysing inconsistency, Argumentation, Default reasoning and Knowledge Fusion. Weiru Liu is a senior lecturer at the School of Computer Science, Queen's University Belfast. She received her B.Sc. and M.Sc. degrees in Computer Science from Jilin University, P.R China, and her Ph.D. degree in Artificial Intelligence from the University of Edinburgh. Her main research interests include reasoning under uncertainty, knowledge representation and reasoning, uncertain knowledge and information fusion, and knowledge discovery in databases. She has published over 50 journal and conference papers in these areas.     

基于CompactPCI的应用与分析

鉴于目前电信的声讯系统中竞争的激烈性，它们急需要提高自身的系统集成度及高可用性，保证以最小的投资获得最丰厚的回报，由此出现了CompactPCI的系列产品，它不仅可以大大提高系统的集成度，同时对于系统的高可用性也进行了充分的考虑。本文将就声讯系统中基于CompactPCI的应用进行分析。     

Managing information technology in the nineties

Business, not technology leaders should manage the change of Information Technology (IT) from a self-contained business support unit of the sixties to a distributed strategic business function of the nineties. Top management should recognize that a good business plan can only be developed and executed through the partnership between the business unit managers and the managers of the financial, the personnel, and the IT resource units. The technical problems associated with the management of IT may again be the easier part of the total management challenge.     

信息融合的飞机识别方法

以信息融合的理论为基础，利用从可见光图像序列和8-12μm长波红外图像序列中提取的信息对不同种类飞机进行识别。采用矩特征并结合BP神经网络的方法，分别在特征级和决策级两个不同层次上实现了信息融合。实验结果表明，通过信息融合进行飞机识别的准确率可达到90％以上。     

Lower bounds on the information rate of secret sharing schemes with homogeneous access structure

We present some new lower bounds on the optimal information rate and on the optimal average information rate of secret sharing schemes with homogeneous access structure. These bounds are found by using some covering constructions and a new parameter, the k-degree of a participant, that is introduced in this paper. Our bounds improve the previous ones in almost all cases.     

The State of the Art in Text Filtering

This paper develops a conceptual framework for text filtering practice and research, and reviews present practice in the field. Text filtering is an information seeking process in which documents are selected from a dynamic text stream to satisfy a relatively stable and specific information need. A model of the information seeking process is introduced and specialized to define text filtering. The historical development of text filtering is then reviewed and case studies of recent work are used to highlight important design characteristics of modern text filtering systems. User modeling techniques drawn from information retrieval, recommender systems, machine learning and other fields are described. The paper concludes with observations on the present state of the art and implications for future research on text filtering. This revised version was published online in July 2006 with corrections to the Cover Date.     

N—ISDN走出低谷B—ISDN迈向市场

本文介绍了全球Ｎ－ＩＳＤＮ的商用情况和Ｂ－ＩＳＤＮ的发展趋势，展示出Ｎ－ＩＳＤＮ走了低谷、Ｂ－ＩＳＤＮ迈向市场的美好前景。     

Data-logging: effects on practical science

Abstract This paper describes an investigation into the processes and effects of using electronic data-logging in practical science. A pilot study of classical laboratory work in schools was compared with similar tasks performed with data-logging systems. A more detailed exploration of pupils' performance was then conducted through an extensive series of observations in a range of secondary schools. The results reinforce previous indications of the potential benefits of data-logging, but such benefits must be viewed in the curriculum context of the type of measurement activity and the pedagogical context of teaching and learning objectives. The paper concludes with a discussion of the latter issues.     

强度型光纤传感器的信号检测系统

本文阐述了一种可提高强度型光纤传感器测量精度的检测系统。该系统利用同一检测电路交替检测信号、参考通道的输出信号，并将信号、参考两通道的检测结果相除，从而消除了因发光二极管光源波动及检测电路系统不稳定所带来的误差。采用同步相关技术抑制了噪声，提高了输出信噪比。实验证明，当时间常数ＲＣ为０．０５Ｓ时，采用该检测系统可获得优于千分之一的零点稳定性和优于２×１０３的输出信噪比。