An intelligent web-page classifier with fair feature-subset selection

The explosion of on-line information has given rise to many manually constructed topic hierarchies (such as Yahoo!!). But with the current growth rate in the amount of information, manual classification in topic hierarchies results in an immense information bottleneck. Therefore, developing an automatic classifier is an urgent need. However, classifiers suffer from enormous dimensionality, since the dimensionality is determined by the number of distinct keywords in a document corpus. More seriously, most classifiers are either working slowly or they are constructed subjectively without any learning ability. In this paper, we address these problems with a fair feature-subset selection (FFSS) algorithm and an adaptive fuzzy learning network (AFLN) for classification. The FFSS algorithm is used to reduce the enormous dimensionality. It not only gives fair treatment to each category but also has ability to identify useful features, including both positive and negative features. On the other hand, the AFLN provides extremely fast learning ability to model the uncertain behavior for classification so as to correct the fuzzy matrix automatically. Experimental results show that both FFSS algorithm and the AFLN lead to a significant improvement in document classification, compared to alternative approaches.     

用C51系列单片机设计物体分级设备的测量光幕

首先介绍了光幕测量高度的原理 ,给出了高度测量光幕的一种实现方法 ,分析了由该方法设计的系统结构和主要性能。从而彻底解决了相邻通路间的干扰 ,提高了测量精度。     

活塞综合检测仪的研制

介绍了活塞综合检测仪的功能、组成、检测过程、测量原理与方法和主要技术性能指标。该仪器是国内研制的第一台智能型活塞综合检测仪。实际应用表明,这是一台高精度、高稳定性和高效率的检测仪器。     

数控加工的基本坐标系和对刀问题

数控加工中的对刀问题影响机械加工的各个方面。这里从介绍数控机床的基本坐标系出发，重点阐述了对刀的基本原理和方法以及常见数控机床对刀问题的处理。     

热物理性质测试技术研究现状和发展趋势

本文在对热物理性质研究在热能工程、材料科学、信息科学、航天工程、环境工程、生物科学、微电子技术和计量学等众多科技领域中的重要性进行探讨的基础上，评述了热物理性质测试技术的研究现状和发展趋势。鉴于薄膜材料在微电子器件、集成电路和微电子机械系统等领域中日益广泛的应用，本文还综述了亚微米－纳米尺度薄膜材料热导率和热扩散率的测试新技术。     

大把捆远程维护仪的研究

采用单片机开发大把捆远程维护仪，通过电话线，维护仪远程拨叫维护中心，远程采集机器运行状态，远程调整参数，使机器处于最佳状态运行；维修中心专家远程判断故障点，远程维护或远程指导维护，节省维护成本和人力资源。     

Simultaneous translation of lectures and speeches

With increasing globalization, communication across language and cultural boundaries is becoming an essential requirement of doing business, delivering education, and providing public services. Due to the considerable cost of human translation services, only a small fraction of text documents and an even smaller percentage of spoken encounters, such as international meetings and conferences, are translated, with most resorting to the use of a common language (e.g. English) or not taking place at all. Technology may provide a potentially revolutionary way out if real-time, domain-independent, simultaneous speech translation can be realized. In this paper, we present a simultaneous speech translation system based on statistical recognition and translation technology. We discuss the technology, various system improvements and propose mechanisms for user-friendly delivery of the result. Over extensive component and end-to-end system evaluations and comparisons with human translation performance, we conclude that machines can already deliver comprehensible simultaneous translation output. Moreover, while machine performance is affected by recognition errors (and thus can be improved), human performance is limited by the cognitive challenge of performing the task in real time.     

Three perspectives of data mining

This paper reviews three recent books on data mining written from three different perspectives, i.e., databases, machine learning, and statistics. Although the exploration in this paper is suggestive instead of conclusive, it reveals that besides some common properties, different perspectives lay strong emphases on different aspects of data mining. The emphasis of the database perspective is on efficiency because this perspective strongly concerns the whole discovery process and huge data volume. The emphasis of the machine learning perspective is on effectiveness because this perspective is heavily attracted by substantive heuristics working well in data analysis although they may not always be useful. As for the statistics perspective, its emphasis is on validity because this perspective cares much for mathematical soundness behind mining methods.     

PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance

We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the generation of strings of symbols, that have been used in the context of speech and handwriting recognition, and bioinformatics. Recent work on learning PDFAs from random examples has used the KL-divergence as the error measure; here we use the variation distance. We build on recent work by Clark and Thollard, and show that the use of the variation distance allows simplifications to be made to the algorithms, and also a strengthening of the results; in particular that using the variation distance, we obtain polynomial sample size bounds that are independent of the expected length of strings.     

镀锌测厚仪

本文叙述了Ｘ射线荧光测厚仪的原理、特点及测量头的设计考虑原则。并以我们研制的两种镀锌测得仪为例作了详细说明。