网管系统中基于谷歌地图的拓扑可视化实现

为了解决网络管理系统中简洁高效实现网络拓扑可视化的问题,提出一种基于谷歌地图API的网络拓扑可视化设计与实现方法:先采用分层算法将网络拓扑分为主干网与子网两层,再用谷歌地图API实现网络拓扑的分层显示,同时对设备数据和业务数据予以显示,使网管人员在获得地理位置信息的同时,能直观地查看设备和业务相关信息.实际工程结果表明采用该方法设计和开发的网管系统实现了拓扑展示的功能,且具有很好的可操作性.     

A new approach for data clustering and visualization using self-organizing maps

A self-organizing map (SOM) is a nonlinear, unsupervised neural network model that could be used for applications of data clustering and visualization. One of the major shortcomings of the SOM algorithm is the difficulty for non-expert users to interpret the information involved in a trained SOM. In this paper, this problem is tackled by introducing an enhanced version of the proposed visualization method which consists of three major steps: (1) calculating single-linkage inter-neuron distance, (2) calculating the number of data points in each neuron, and (3) finding cluster boundary. The experimental results show that the proposed approach has the strong ability to demonstrate the data distribution, inter-neuron distances, and cluster boundary, effectively. The experimental results indicate that the effects of visualization of the proposed algorithm are better than that of other visualization methods. Furthermore, our proposed visualization scheme is not only intuitively easy understanding of the clustering results, but also having good visualization effects on unlabeled data sets.     

Ranked centroid projection: a data visualization approach with self-organizing maps

The self-organizing map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, the clustering and visualization capabilities of the SOM, especially in the analysis of textual data, i.e., document collections, are reviewed and further developed. A novel clustering and visualization approach based on the SOM is proposed for the task of text mining. The proposed approach first transforms the document space into a multidimensional vector space by means of document encoding. Afterwards, a growing hierarchical SOM (GHSOM) is trained and used as a baseline structure to automatically produce maps with various levels of detail. Following the GHSOM training, the new projection method, namely the ranked centroid projection (RCP), is applied to project the input vectors to a hierarchy of 2-D output maps. The RCP is used as a data analysis tool as well as a direct interface to the data. In a set of simulations, the proposed approach is applied to an illustrative data set and two real-world scientific document collections to demonstrate its applicability.     

Structural enhanced information and its application to improved visualization of self-organizing maps

In this paper, we propose structural enhanced information for detecting and visualizing main features in input patterns. We have so far proposed information enhancement for feature detection, where, if we want to focus upon components such as units and connection weights and interpret the functions of the components, we have only to enhance competitive units with the components. Though this information enhancement has given favorable results in feature detection, we further refine the information enhancement and propose structural enhanced information. In structural enhanced information, three types of enhanced information can be differentiated, that is, first-, second- and third-order enhanced information. The first-order information is related to the enhancement of competitive units themselves in a competitive network, and the second-order information is dependent upon the enhancement of competitive units with input patterns. Then, the third-order information is obtained by subtracting the effect of the first-order information from the second-order information. Thus, the third-order information more explicitly represents information on input patterns. With this structural enhanced information, we can estimate more detailed features in input patterns. For demonstrating explicitly and intuitively the improved performance of our method, the conventional SOM was used, and we transformed competitive unit outputs so as to improve visualization. The method was applied to the well-known Iris problem, an OECD countries classification problem and the Johns Hopkins University Ionosphere database. In all these problems, we succeeded in visualizing the detailed and important features of input patterns by using the third-order information.     

A balanced decomposition approach to real-time visualization of large vector maps in CyberGIS

With the dramatic development of spatial data infrastructure, CyberGIS has become significant for geospatial data sharing. Due to the large number of concurrent users and large volume of vector data, CyberGIS faces a great challenge in how to improve performance. The real-time visualization of vector maps is themost common function in Cyber-GIS applications, and it is time-consuming especially when the data volume becomes large. So, how to improve the efficiency of visualization of large vector maps is still a significant research direction for GIScience scientists. In this research, we review the existing three optimization strategies, and determine that the third category strategy (i.e., parallel optimization) is appropriate for the real-time visualization of large vector maps. One of the key issues of parallel optimization is how to decompose the real-time visualization tasks into balanced sub tasks while taking into consideration the spatial heterogeneous characteristics. We put forward some rules that the decomposition should conform to, and design a real-time visualization framework for large vector maps. We focus on a balanced decomposition approach that can assure efficiency and effectiveness. Considering the spatial heterogeneous characteristic of vector data, we use a “horizontal grid, vertical multistage” approach to construct a spatial point distribution information grid. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds. Then, all the sub viewsheds are distributed to multiple server nodes to be executed in parallel, so as to improve the realtime visualization efficiency of large vector maps. A group of experiments have been conducted by us. The analysis results demonstrate that the approach proposed in this research has the ability of balanced decomposition, and it is efficient and effective for all geometry types of vector data.     

Externally growing self-organizing maps and its application to e-mail database visualization and exploration

In this paper we present an approach to organize and classify e-mails using self-organizing maps. The aim is on the one hand to provide an intuitive visual profile of the considered mailing lists and on the other hand to offer an intuitive navigation tool, were similar e-mails are located close to each other, so that the user can scan easily for e-mails similar in content. To be able to evaluate this approach we have developed a prototypical software tool that imports messages from a mailing list and arranges/groups these e-mails based on a similarity measure. The tool combines conventional keyword search methods with a visualization of the considered e-mail collection. The prototype was developed based on externally growing self-organizing maps, which solve some problems of conventional self-organizing maps and which are computationally viable. Besides the underlying algorithms we present and discuss some system evaluations in order to show the capabilities of the approach.     

Object-oriented visualization

Feature based techniques incorporated into standard visualization algorithms can greatly enhance the quantification and visualization of observed phenomena, as described in the article. The methods to isolate and recognize coherent 3D structures are analogous to 2D vision techniques. The overall goals are the same in both fields, namely, to interpret an image (data) and construct a model to describe it. Although the article uses data sets from numerical simulations of fluid flow, the concepts are applicable to other domains where scientists study the evolution and morphologies of 4D space time vector and scalar fields. More work is needed to explore complex features based upon domain specific knowledge and to define the parameters for classification and tracking. Sophisticated databases for storage and retrieval of feature based data sets are also an interesting area of study. The ultimate goal of visualization is to aid in the understanding and analysis of data. With faster parallel computers and more sophisticated laboratory equipment, information is being produced in ever greater amounts. This information must be presented to the scientist in a form suitable for cogent assimilation and manipulation. The article presents issues and algorithms for an object oriented approach to this problem and demonstrates its usefulness for visualization     

Caricaturistic visualization

Caricatures are pieces of art depicting persons or sociological conditions in a non-veridical way. In both cases caricatures are referring to a reference model. The deviations from the reference model are the characteristic features of the depicted subject. Good caricatures exaggerate the characteristics of a subject in order to accent them. The concept of caricaturistic visualization is based on the caricature metaphor. The aim of caricaturistic visualization is an illustrative depiction of characteristics of a given dataset by exaggerating deviations from the reference model. We present the general concept of caricaturistic visualization as well as a variety of examples. We investigate different visual representations for the depiction of caricatures. Further, we present the caricature matrix, a technique to make differences between datasets easily identifiable.     

Software visualization

The field of software visualization (SV) investigates approaches and techniques for static and dynamic graphical representations of algorithms, programs (code), and processed data. SV is concerned primarily with the analysis of programs and their development. The goal is to improve our understanding of inherently invisible and intangible software, particularly when dealing with large information spaces that characterize domains like software maintenance, reverse engineering, and collaborative development. The main challenge is to find effective mappings from different software aspects to graphical representations using visual metaphors. This paper provides an overview of the SV research, describes current research directions, and includes an extensive list of recommended readings.     

Necklace maps

Statistical data associated with geographic regions is nowadays globally available in large amounts and hence automated methods to visually display these data are in high demand. There are several well-established thematic map types for quantitative data on the ratio-scale associated with regions: choropleth maps, cartograms, and proportional symbol maps. However, all these maps suffer from limitations, especially if large data values are associated with small regions. To overcome these limitations, we propose a novel type of quantitative thematic map, the necklace map. In a necklace map, the regions of the underlying two-dimensional map are projected onto intervals on a one-dimensional curve (the necklace) that surrounds the map regions. Symbols are scaled such that their area corresponds to the data of their region and placed without overlap inside the corresponding interval on the necklace. Necklace maps appear clear and uncluttered and allow for comparatively large symbol sizes. They visualize data sets well which are not proportional to region sizes. The linear ordering of the symbols along the necklace facilitates an easy comparison of symbol sizes. One map can contain several nested or disjoint necklaces to visualize clustered data. The advantages of necklace maps come at a price: the association between a symbol and its region is weaker than with other types of maps. Interactivity can help to strengthen this association if necessary. We present an automated approach to generate necklace maps which allows the user to interactively control the final symbol placement. We validate our approach with experiments using various data sets and maps.     

Graph visualization and navigation in information visualization: Asurvey

This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective     

The application visualization system: a computational environmentfor scientific visualization

A software system for developing interactive scientific visualization applications quickly, with a minimum of programming effort, is described. This application visualization system (AVS) is an application framework targeted at scientists and engineers. The goal of the system is to make applications that combine interactive graphics and high computational requirements easier to develop for both programmers and nonprogrammers. AVS is designed around the concept of software building blocks, or modules, which can be interconnected to form visualization applications. AVS allows flow networks of existing modules to be constructed using a direct-manipulation user interface, and it automatically generates a simple user interface to each module     

基于VTK的电磁场三维可视化研究及实现

针对在三维电磁场可视化过程中面临的电磁数据的多样性和数据映射的多样性问题,分析了电磁场三维可视化的主要流程和电磁场数据集,并引入三维可视化类库VTK。利用VTK类库良好的封装性,采用Marching Cube和Hedgehog建模,分别实现了电磁标量场和电磁矢量场的三维可视化。     

Carrying surfaces for return maps of averaged logistic maps

We analyze the average of two iterated logistic maps in both the uncoupled and coupled cases and show that the resulting sequence can be seen as lying on the graph of a function of two variables which we call a carrying surface. Experimenting with different graphical representations of the data led us to discover this surface.     

Task-specific visualization design

This case study in operational weather forecasting demonstrates the principles of task-specific visualization design: defining user needs, implementing that definition, and establishing techniques for different user goals. The current applications can generate visualizations for the Web after an intermediate step of migrating the products to a Web server. This proves advantageous in an operational environment because the forecaster has content control. However, direct generation within a Web browser, which requires a simplified user interface and content, will require further refinement of the task decomposition. The notion of task-driven customization of content and interface has succeeded in weather forecasting, but the idea also applies to other domains. The potential benefits should encourage visualization designers to adopt these principles in their application development     

Program graph visualization

Although there are many algorithms to draw hierarchical structures such as directed graphs and trees none specifically treat the problem of visualizing program graphs. This paper presents an algorithm and the underlying tool — ViewGraph — designed to visualize program graphs. The algorithm is divided in two parts: (1) determine node positions, and (2) assign routes to branches. The first part has three steps: level assignment, scope and position calculation. A modified algorithm used to assign levels to nodes in a tree is used to find Y coordinates; a concept called scope is used to define X coordinates. Scope is a prediction of the space required by a node and its descendants. A search on the available positions left by the placement of nodes is performed to route branches. A set of aesthetic aspects meant to help the development of program graph visualization algorithms is also proposed. The algorithm runs in an acceptable time making it useful even for interactive applications. © 1997 John Wiley & Sons, Ltd.