用电营销管理信息系统的建设

分析供电部门用电营销管理信息系统的发展和建设,阐述该系统建设应当注意的问题。指出系统建设关键是要提高各级领导和管理人员的现代意识、信息意识,同时提高对用电营销管理信息系统建设重要性的认识。     

对重催I/A'S系统三冲量控制回路的探讨

本文主要对广州石油化工总厂重油催化裂化装置的复杂回路——三冲量控制在I/A'S系统的实现进行探讨和实施。     

多对多转移链关系信息模型的设计及其应用

本文主要介绍在关系信息模型中增加联系,配置适当的数据完整性控制,实现有向的多对多关系,并在房地产权转移、变更管理信息系统中得到应用。     

一阶滞后对象的温度控制

本文主要介绍了利用μ XL中小型集散控制系统,对未知参数的一阶惯性滞后对象,实现温度控制,并得到理想的温度控制曲线。     

直升机尾桨试验台拖动与计算机监控系统的应用

根据尾桨试验台拖动系统的特点及技术要求,采用S7-300 PLC作为中央控制器,Pll工控机作为监控计算机,SIMOVERT MD工程型变频器作为DP从站,构成了一个基于PROFIBUS-DP现场总线的控制网络.     

Fuzzy medial axis transformation (fmat): Image representation,skeleton extraction and uncertainty management in computer vision

The problem of extraction of medial axis transformation of a gray image with reference to skeletonization, image representation and uncertainty management in a vision system has been addressed. The Fuzzy Medial Axis Transformation (fmat) of a fuzzy setf is a set of fuzzy disks whose sup isf. Unfortunately, specifying thefmat sometimes requires more storage space than specifyingf itself. The present paper describes some techniques to improve the compact representation offmat; thereby making it practically useful to an image for its skeleton extraction and compact representation, for shape analysis and template matching, for representation and retrieval, for uncertainty management in recognition and for creating new images of various poses. The algorithms involve reduction of redundancy infmat, its approximation, and reduction of the searching spaces for its computation. Computational aspects for the convenience of writing an efficient program have been described. Some applications of thefmat have also been mentioned. This work was done while SKP held annrc-nasa Senior Research Associateship at the Lyndon B Johnson Space Center, Houston, Texas.     

冲击式振动落砂机的动态响应与分叉

本文考虑一类振动落砂机简化力学模型的次谐运动、稳定性与分叉问题.数值工作表明该模型存在"跳跃"和多种分叉现象.     

One-dimensional and multi-dimensional substring selectivity estimation

With the increasing importance of XML, LDAP directories, and text-based information sources on the Internet, there is an ever-greater need to evaluate queries involving (sub)string matching. In many cases, matches need to be on multiple attributes/dimensions, with correlations between the multiple dimensions. Effective query optimization in this context requires good selectivity estimates. In this paper, we use pruned count-suffix trees (PSTs) as the basic data structure for substring selectivity estimation. For the 1-D problem, we present a novel technique called MO (Maximal Overlap). We then develop and analyze two 1-D estimation algorithms, MOC and MOLC, based on MO and a constraint-based characterization of all possible completions of a given PST. For the k-D problem, we first generalize PSTs to multiple dimensions and develop a space- and time-efficient probabilistic algorithm to construct k-D PSTs directly. We then show how to extend MO to multiple dimensions. Finally, we demonstrate, both analytically and experimentally, that MO is both practical and substantially superior to competing algorithms. Received April 28, 2000 / Accepted July 11, 2000     

Clustering categorical data: an approach based on dynamical systems

We describe a novel approach for clustering collections of sets, and its application to the analysis and mining of categorical data. By “categorical data,” we mean tables with fields that cannot be naturally ordered by a metric – e.g., the names of producers of automobiles, or the names of products offered by a manufacturer. Our approach is based on an iterative method for assigning and propagating weights on the categorical values in a table; this facilitates a type of similarity measure arising from the co-occurrence of values in the dataset. Our techniques can be studied analytically in terms of certain types of non-linear dynamical systems. Received February 15, 1999 / Accepted August 15, 1999     

Optimizing multiple dimensional queries simultaneously in multidimensional databases

Some significant progress related to multidimensional data analysis has been achieved in the past few years, including the design of fast algorithms for computing datacubes, selecting some precomputed group-bys to materialize, and designing efficient storage structures for multidimensional data. However, little work has been carried out on multidimensional query optimization issues. Particularly the response time (or evaluation cost) for answering several related dimensional queries simultaneously is crucial to the OLAP applications. Recently, Zhao et al. first exploited this problem by presenting three heuristic algorithms. In this paper we first consider in detail two cases of the problem in which all the queries are either hash-based star joins or index-based star joins only. In the case of the hash-based star join, we devise a polynomial approximation algorithm which delivers a plan whose evaluation cost is $ O(n^{\epsilon }$) times the optimal, where n is the number of queries and is a fixed constant with . We also present an exponential algorithm which delivers a plan with the optimal evaluation cost. In the case of the index-based star join, we present a heuristic algorithm which delivers a plan whose evaluation cost is n times the optimal, and an exponential algorithm which delivers a plan with the optimal evaluation cost. We then consider a general case in which both hash-based star-join and index-based star-join queries are included. For this case, we give a possible improvement on the work of Zhao et al., based on an analysis of their solutions. We also develop another heuristic and an exact algorithm for the problem. We finally conduct a performance study by implementing our algorithms. The experimental results demonstrate that the solutions delivered for the restricted cases are always within two times of the optimal, which confirms our theoretical upper bounds. Actually these experiments produce much better results than our theoretical estimates. To the best of our knowledge, this is the only development of polynomial algorithms for the first two cases which are able to deliver plans with deterministic performance guarantees in terms of the qualities of the plans generated. The previous approaches including that of [ZDNS98] may generate a feasible plan for the problem in these two cases, but they do not provide any performance guarantee, i.e., the plans generated by their algorithms can be arbitrarily far from the optimal one. Received: July 21, 1998 / Accepted: August 26, 1999