Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. visualization by reduc...
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Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. visualization by reducing the dimensionality of Kansei data to less than or equal to three dimensions could help the analyzer to understand the data.
Social and economic data are almost paid greatest attention by the country leaders and used to sense the situation of a country. The manner of visualization and dataanalysis to social and economic data will greatly a...
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Social and economic data are almost paid greatest attention by the country leaders and used to sense the situation of a country. The manner of visualization and dataanalysis to social and economic data will greatly affects the knowledge detection and information acquisition, so designing a good analysis system would be very necessary. This paper tries to use flash technology to design an online visualization and dataanalysis system to the social and economic data. By comparisons with the traditional web GIS systems, the system designed by the paper has great priorities in following three aspects: (1) Accelerating the online dataanalysis speed by changing the common work flow. (2) Enhancing the system interactivity by integrating and associating the spatial map, attribute data and statistics chart. (3) Creating a distribute map for any selected element and generating a time series animation dynamically. The result shows that using flash technology can achieve difficult functions that the traditional GIS software can't realize.
visualization of three dimensional volumetric medical data has been widely used. Even though, it still faces a lot of challenges, such as helping users find out structure of their interest, illustrating features which...
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ISBN:
(纸本)9781424464968
visualization of three dimensional volumetric medical data has been widely used. Even though, it still faces a lot of challenges, such as helping users find out structure of their interest, illustrating features which are significant for diagnosis of disease. In our paper, a multi-feature based transfer function is provided to improve the quality of visualization. We compute a multi-feature descriptor for both two-phase clustering and transfer function design. Moreover, we test the transfer function on several medical datasets to show the efficiency and practicability of our method.
This paper sketches one approach to facilitate comprehension of distributed software systems. These systems gain more and more importance due to a paradigm shift in software systems and applications, evolving from sin...
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ISBN:
(纸本)9781450304948
This paper sketches one approach to facilitate comprehension of distributed software systems. These systems gain more and more importance due to a paradigm shift in software systems and applications, evolving from single-chip solutions to multi-tiered web-based applications. For a single developer, it becomes increasingly difficult to cope with the complexity of such software systems. We propose a novel automated analysis and visualization technique that aims at the interactive exploration of static structures and behavior of distributed software systems. First, it automatically gathers communication data from the instrumented system components. Second, it generates a visual representation using a heuristic layout approach. Finally, it allows developers to interactively refine and explore this structural and behavioral information.
Parallel coordinates technique has been widely used in information visualization applications and it has achieved great success in visualizing multivariate data and perceiving their trends. Nevertheless, visual clutte...
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ISBN:
(纸本)9780819479235
Parallel coordinates technique has been widely used in information visualization applications and it has achieved great success in visualizing multivariate data and perceiving their trends. Nevertheless, visual clutter usually weakens or even diminishes its ability when the data size increases. In this paper, we first propose a tile-based parallel coordinates, where the plotting area is divided into rectangular tiles. Each tile stores an intersection density that counts the total number of polylines intersecting with that tile. Consequently, the intersection density is mapped to optical attributes, such as color and opacity, by interactive transfer functions. The method visualizes the polylines efficiently and informatively in accordance with the density distribution, and thus, reduces visual cluttering and promotes knowledge discovery. The interactivity of our method allows the user to instantaneously manipulate the tiles distribution and the transfer functions. Specifically, the classic parallel coordinates rendering is a special case of our method when each tile represents only one pixel. A case study on a real world data set, U. S. stock mutual fund data of year 2006, is presented to show the capability of our method in visually analyzing financial data. The presented visual analysis is conducted by an expert in the domain of finance. Our method gains the support from professionals in the finance field, they embrace it as a potential investment analysis tool for mutual fund managers, financial planners, and investors.
To analyze large amounts of numerical data, one of the most useful approaches is to use scientific visualization to transform them into graphical images. Flow visualization as one of the challenging topics has played ...
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Previous techniques for visualizing time-series of multivariate data mostly plot the time along additional axes, are often complex, and does not support intuitive interaction. In this poster paper, we present an inter...
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ISBN:
(纸本)9781450304948
Previous techniques for visualizing time-series of multivariate data mostly plot the time along additional axes, are often complex, and does not support intuitive interaction. In this poster paper, we present an interactive visualization approach for the analysis of software metric trends that allows users to operate with Kiviat diagrams on 2D planes in the space and to intuitively extend this visual representation into 3D if needed.
The analysis and exploration necessary to gain deep understanding of large databases demand an intuitive and informative human-computer interface. In this paper, we present a visualization system with a client-server ...
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ISBN:
(纸本)9789896740276
The analysis and exploration necessary to gain deep understanding of large databases demand an intuitive and informative human-computer interface. In this paper, we present a visualization system with a client-server architecture for multiscale visualization of relational databases. The visual interface on the client supports web-based remote access. We use zoom trees to represent the entire history of a zooming process that reveals multiscale details. Every path in a zoom tree represents a zoom path and every node in the tree can have an arbitrary number of subtrees to support arbitrary branching and backtracking. Zoom trees are seamlessly integrated with a table-based overview using "hyperlinks" embedded in the table. To support fast query processing on the server, we further develop efficient GPU-based parallel algorithms for online data cubing and CPU-based data clustering. Also, a user study was conducted to evaluate the effectiveness of our design.
Critical climate applications like cyclone tracking and earthquake modeling require high-performance simulations and online visualization simultaneously performed with the simulations for timely analysis. Remote visua...
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In computation flow visualization, integration based geometric flow visualization is often used to explore the flow field structure. A typical time-varying dataset from a Computational Fluid Dynamics (CFD) simulation ...
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ISBN:
(纸本)9781424455379
In computation flow visualization, integration based geometric flow visualization is often used to explore the flow field structure. A typical time-varying dataset from a Computational Fluid Dynamics (CFD) simulation can easily require hundreds of gigabytes to even terabytes of storage space, which creates challenges for the consequent data-analysis tasks. This paper presents a new technique for path-lines visualization of extremely large time varying vector data using high performance computing. The high level requirements that guided the formulation of the new technique are (a) support for large dataset sizes, (b) support for temporal coherence of the vector data, (c) support for distributed memory high performance computing and (d) optimum utilization of the computing nodes with multi-cores (multi-core processors). The challenge is to design and implement a technique that meets these complex requirements and balances the conflicts between them. The fundamental innovation in this work is developing efficient distributed path-lines visualization for large time varying vector data. The maximum performance was reached through the parallelization of multiple processes on the multi-cores of each computing node. Accuracy of the proposed technique was confirmed compared to the results of the visualization Tool Kit (VTK). In addition, the proposed technique exhibited acceptable scalability for different data sizes with better scalability for the larger ones. Finally, the utilization of the computing nodes was satisfactory for the considered test cases.
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