企业信息系统实施方案与ASP

经过20年左右的市场经济改革,中国市场已逐渐成为国际市场必不可少的一个组成部分.面对新千年的这一全球化趋势,国内的众多企业家已清醒的认识到利用最新的信息技术实现企业全面信息化是迅速提高企业竞争实力的一条必由之路,并为此作了许多相应的努力.企业计算机应用在计算机硬件配备方面近几年已经达到了一个相当高的水平,而在企业专用软件的开发和应用方面则仍处于一个相对滞后的状态.

Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment

This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.

BOOTSTRAPPING FOR EXTRACTING RELATIONS FROM LARGE CORPORA

A new approach of relation extraction is described in this paper. It adopts a bootstrap- ping model with a novel iteration strategy, which generates more precise examples of specific relation. Compared with previous methods, the proposed method has three main advantages: first, it needs less manual intervention; second, more abundant and reasonable information are introduced to represent a relation pattern; third, it reduces the risk of circular dependency occurrence in bootstrapping. Scalable evaluation methodology and metrics are developed for our task with comparable techniques over TianWang 100G corpus. The experimental results show that it can get 90% precision and have excellent expansibility.

Development of CAPP System for Small and Medium Size Apparel Enterprises

Existing computer-aided process planning （CAPP） systems for garment manufacturing emphasize all-purpose ones, lack specialism and availability. So, few developed is popular in the garment industries. This study is intended for developing a CAPP system, which aims at the actual condition of process planning in the small and medium size apparel enterprises （SMAs）. It enables the technologists of process planning to be quicker in generating suitable plans that are similar to existing styles or new. It also automatically provides labor cost by considering the shop-ricer caztiticns. Process planning is achieved by adopting the Hybrid Interactive-variant process planning mete. The proposed system has been realized in Borland Delphi 7 and Orade 8. For validation of the system, the software has been implemented successfully in a firm named Jingchen in China.

ORDINAL REGRESSION FOR INFORMATION RETRIEVAL

This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression problem (i.e. ranking problem) instead of binary classification. It is noted that the task of IR is to rank documents according to the user information needed, so IR can be viewed as ordinal regression problem. Two parameter learning algorithms for ORM are presented. One is a perceptron-based algorithm. The other is the ranking Support Vector Machine (SVM). The effec- tiveness of the proposed approach has been evaluated on the task of ad hoc retrieval using three English Text REtrieval Conference (TREC) sets and two Chinese TREC sets. Results show that ORM sig- nificantly outperforms the state-of-the-art language model approaches and OKAPI system in all test sets; and it is more appropriate to view IR as ordinal regression other than binary classification.

Image Registration Based on Improved Mutual Information with Hybrid Optimizer

An improved image registration method is proposed based on mutual infor- mation with hybrid optimizer. Firstly, mutual information measure is combined with morphological gradient information. The essence of the gradient information is that locations a large gradient magnitude should be aligned, but also the orientation of the gradients at those locations should be similar. Secondly, a hybrid optimizer combined PSO with Powell algorithm is proposed to restrain local maxima of mutual information function and improve the registration accuracy to sub-pixel level. Lastly, muhlresolution data structure based on Mallat decomposition can not only improve the behavior of registration function, but also improve the speed of the algorithm. Experimental results demonstrate that the new method can yield good registration result, superior to traditional optimizer with respect to smoothness and attraction basin as well as convergence speed.

A Metadata Model Based on Coupling Testing Information to Increase Testability of Component

A software component must be tested every time it is reused in order to assure quality of component itself and system in which it is to be integrated.So how to increase testability of component has become a key technology in the software engineering community.Here a method is introduced to increase component testability.And meanings of component testability and relative effective ways to increase testability are summarized.Then definitions of component coupling testing criterion,DU-I(Definition-Use Information) and OP-Vs(Observation-Point Values)are given.Base on these,a definition-use table is introduced,which includes DU-A and OP-Vs item,to help component testers to understand and observe interior details about component under test better.Then a framework of testable component based on above DU-table is given.These facilities provide ways to detect errors,observe state variables by observation-points based monitor mechanism.Moreover,above methods are applied to our application developed by ourselves before,and some test cases are generated.Then our method is compared with Orso method and Kan method using the same example,presenting the comparison results.The results illustrate the validity of our method,effectively generating test cases and killing more mutants.

Attribute reduction based on background knowledge and its application in classification of astronomical spectra data

To improve the efficiency of the attribute reduction, we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields. Under the condition of known background knowledge, the algorithm can not only greatly improve the efficiency of attribute reduction, but also avoid the defection of information entropy partial to attribute with much value. The experimental result verifies that the algorithm is effective. In the end, the algorithm produces better results when applied in the classification of the star spectra data.

Application of GML and SVG in the development of WebGIS

Our study deals with two major issues impacting current WebGIS development： interoperability of heterogeneous data and visualization of vector data on the Web. By using the combination of Geography Markup Language （GML）, Scalable Vector Graphics （SVG） and Web Feature Service （WFS） Implementation Specifications developed by the OpenGIS Consortium （OGC）, a strategy of WebGIS is proposed. The GML is used as a coding and data transportation mechanism to realize interoperability, the SVG to display GML data on the Web and the WFS as a data query mechanism to access and retrieve data at the feature level in real time on the Web. A case study shows that the combination mentioned above has enormous potential to achieve interoperability while not requiring considerable changes to existing legacy data. Original data formats need not be changed and could still be retrieved using WFS and transformed into GML in real time. SVG can oroduce suoerior ouality vector maps on a Web browser.

A new approach to query expansion in information retrieval

To eliminate the mismatch between words of relevant documents and user's query and more seriousnegative effects it has on the performance of information retrieval,a method of query expansion on the ba-sis of new terms co-occurrence representation was put forward by analyzing the process of producingquery.The expansion terms were selected according to their correlation to the whole query.At the sametime,the position information between terms were considered.The experimental result on test retrievalconference(TREC)data collection shows that the method proposed in the paper has made an improve-ment of 5%～19% all the time than the language modeling method without expansion.Compared to thepopular approach of query expansion,pseudo feedback,the precision of the proposed method is competi-tive.

Registration Method for CT-MR Image Based on Mutual Information

Medical image registration is important in many medical applications. Registration method based on maximization of mutual information of voxel intensities is one of the most popular methods for 3-D multi-modality medical image registration. Generally, the optimization process is easily trapped in local maximum, resulting in wrong registration results. In order to find the correct optimum, a new multi-resolution approach for brain image registration based on normalized mutual information is proposed. In this method, to eliminate the effect of local optima, multi-scale wavelet transformation is adopted to extract the image edge features. Then the feature images are registered, and the result at this level is taken as the initial estimate for the registration of the original images. Three-dimensional volumes are used to test the algorithm. Experimental results show that the registration strategy proposed is a robust and efficient method which can reach sub-voxel accuracy and improve the optimization speed.

A Scalable Communication Mechanism in Service Emergence Based on Bio-network

A scalable communication mechanism is proposed for service emergence based on bio-network.Service emergence is a novel model inspired by the characteristics of emergence and self-evolution in biological neuroendocrine and immune system,emergent communication means a group communication of mobile bio-entities.A series of protocol and algorithm are presented within frequently bio-entities migration and failure,it includes distribution and parallelization of message propagation method,a token-ring protocol that considerably improves the performance of emergence,and failure detection mechanisms.Experiment results show the desired capability via the proposed solution.

FUZZY PRINCIPAL COMPONENT ANALYSIS AND ITS KERNEL-BASED MODEL

Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances.

Impact of Information Technology Adoption on Value Relevance of Accounting Information： Evidence From the Colombo Stock Exchange

The purpose of this paper is to investigate the value relevance of earning based accounting information and to see how value relevance has changed with the introduction of new information technology at Colombo Stock Exchange （CSE） in Sri Lanka. Sample of the study includes 129 companies selected from 6 major sectors at CSE. Cross sectional and time series cross-sectional regressions are used for the data analysis. Study finds that earnings per share （EPS） and returns on equity （ROE） have a significant impact on market price. However, the explanatory power of combined variables is below average. Further, value explanatory power of earnings has considerably improved after the new information technology adoption at CSE. This study is unique because it examines the impact of technological advancements on value relevance of accounting information probably as the first paper to be applied on Sri Lanka.

THE THEORETICAL BER PERFORMANCE ANALYSIS OF A COOPERATIVE DIVERSITY SCHEME IN FREQUENCY SELECTIVE FADING CHANNEL

A novel cooperative diversity scheme based on Distributed Space-Time Block Coding and Multi-Carrier Code Division Multiple Access (DSTBC-MC-CDMA) is proposed which works well in frequency selective fading channels with multiple single-antenna users. And an analytical error model is established to describe the symbol decoding errors between interusers, based on which a close form expression for theoretical Bit Error Rate (BER) performance of the scheme is derived to analyze the influence of the interuser decoding errors on the BER performance of the scheme. Then simulation is complimented to verify the analytic result above, which also shows that the BER performance of DSTBC-MC-CDMA outgoes that of non-cooperative MC-CDMA with considerable gains. Further- more, the simulations coincide with the theoretical results well.

Linguistic Truth Values Lattice Implication Algebras

In order to study uncertainty reasoning and automatic reasoning with linguistic terms, in this paper, the set of basic linguistic truth values and the set of modifiers are defined, according to common sense; partially orderings are defined on them. Based on it, a lattice implication algebra model L18 of linguistic terms is built; furthermore, its some basic properties are discussed.

Multimedia Production and Multi（media） Literacy in Gymnasiums

The article displays the possibilities for introducing multimedia production based on computer science to gymnasiums （general secondary school programs）, where students who usually continue their education at college are educated. The purpose of the research was to prepare an assessment of the situation and recommendations to gymnasiums on how to improve the situation in this field and what options and opportunities appear for schools and the media environment in which they are active. Special attention was paid to the situation of activities （extracurricular activities and optional subjects） related to multimedia production and uses of ICT （information-communication technology）.

Modeling Multisource-heterogeneous Information Based on Random Set and Fuzzy Set Theory

This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. Firstly, based on strong random set and weak random set, the unified form to describe both data (unambiguous information) and fuzzy evidence (uncertain information) is introduced. Secondly, according to signatures of fuzzy evidence, two Bayesian-markov nonlinear measurement models are proposed to fuse effectively data and fuzzy evidence. Thirdly, by use of "the models-based signature-matching scheme", the operation of the statistics of fuzzy evidence defined as random set can be translated into that of the membership functions of relative point state variables. These works are the basis to construct qualitative measurement models and to fuse data and fuzzy evidence.

A Distributed Data Mining System Based on Multi-agent Technology

Distributed Data Mining is expected to discover preciously unknown, implicit and valuable information from massive data set inherently distributed over a network. In recent years several approaches to distributed data mining have been developed, but only a few of them make use of intelligent agents. This paper provides the reason for applying Multi-Agent Technology in Distributed Data Mining and presents a Distributed Data Mining System based on Multi-Agent Technology that deals with heterogeneity in such environment. Based on the advantages of both the CS model and agent-based model, the system is being able to address the specific concern of increasing scalability and enhancing performance.