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检索条件"任意字段=Conference on Visualization and Data Analysis 2010"

共 1162 条记录，以下是41-50 订阅

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Information visualization using the Weibull Distribution

Information Visualization using the Weibull Distribution

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3rd IEEE International conference on Computer Science and Information Technology (ICCSIT)

作者： Mongkolnam, Pornchai King Mongkuts Univ Technol Thonburi Sch Infonnat Technol Bangkok Thailand

ISBN: (纸本)9781424455379

visualization has been around for more than two decades. Various techniques have been proposed, and some have found their fitting places in many applications in documentation visualization, scientific visualization, etc. To our knowledge, no one has applied the Weibull distribution's probability density functions whose flexibility lies in their adjustable shape and scale parameters to the information visualization. It is known that the different shapes and scales of the probability density functions could statistically model and effectively represent underlying data. Most data could approximately be modeled by the functions, their translations their reflection symmetries, or a combination of them. We: therefore, explore the potential of the visualization technique which is based on the Weibull distribution's probability density functions.

关键词： Visual analysis information visualization information exploration Weibull distribution probability density function multiresolution

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A visual analytics tool for analysing microarray data

A visual analytics tool for analysing microarray data

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10th IEEE International conference on data Mining Workshops, ICDMW 2010

作者： Amélie, Martin Noirhomme-Fraiture, Monique Nguyen, Quang Vinh Simoff, Simeon Faculty of Computer Science University of Namur Namur Belgium School of Computing and Mathematics University of Western Sydney Sydney Australia

ISBN: (纸本)9780769542577

This paper presents a new visual analytics tool for analysing microarray data with several thousands of attributes. The tool includes two components 1) automated data analysis and 2) interactive visualization. Automated data analysis is used to reduce of the amount of attributes, through the construction of data groups and principle component analysis (PCA). Interactive visualization provides an interface that allows the user to explore the variables of these data groups and to extract more information from all the attributes © 2010 IEEE.

关键词： data visualization

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Using GIS for data visualization and Processing in Pollution Sources Census

Using GIS for Data Visualization and Processing in Pollution...

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3rd IEEE International conference on Computer Science and Information Technology (ICCSIT)

作者： Huang Jiejun Cui Wei Chen Ting Zhan Yunjun Li Ye Wuhan Univ Technol Sch Resource & Environm Engn Wuhan Peoples R China

ISBN: (纸本)9781424455379

Pollution sources census will provide data for the macro-control of environmental protection and management and promote economy structure adjustment and planning. data visualization and processing for pollution sources census is practically meaningful for improving the pollution sources census digitalization and intelligence management level. Based on GIS and spatial database, an information management system for pollution sources census has been developed. It has some functions such as data visualization, data query, data statistics and spatial analysis. Combined with the characteristics of environmental management, the system can provide efficient technical support and scientific basis for environment protection, total quantity control of pollution sources emissions, pollution sources management and economic structure optimization, et al. The experiment results show that it has a certain value and significance for census data exploration and application.

关键词： Geographic Information System (GIS) pollution source census data visualization dada processing spatial analysis

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The use of software engineering technique to develop a GIS-based system for infrastructure assets

The use of software engineering technique to develop a GIS-b...

引用

31st Asian conference on Remote Sensing 2010, ACRS 2010

作者： Hagahmoodi, Salah O. Department of Computer Science College of Computer Science and Software Engineering University of Hail Saudi Arabia

ISBN: (纸本)9781617823978

With the vertical growth of infrastructure in modern cities several practical problems have arisen in: providing urban services, maintaining the current assets and planning for the future's peoples' needs these not only linked with the dramatic changes of today cities and urban growth, but also depend on the timeous analysis of urban planning data. The analysis and process of urban data face a number of problems, in particular relating to the storage and integrative processing of large spatial and non-spatial datasets from various sources and different formats, data types, and multi-dimensional locations. These problems complicate database structure and design, algorithm operations, relationships, and require data types that joined the spatial and non-spatial in seamless manor, providing ad hoc queries, and as well as offer a practical visualization of the infrastructure's data. The proposed system is expected to provide a number of tools for data storage, analysis of spatial and non-spatial datasets with visualization representation in multidimensional.

关键词： visualization

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An improved SOM-based visualization technique for DNA microarray data analysis

An improved SOM-based visualization technique for DNA microa...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint conference on Neural Networks, IJCNN 2010

作者： Patra, Jagdish C. Abraham, Jacob Meher, Pramod K. Chakraborty, Goutam School of Computer Engineering Nanyang Technological University Singapore Singapore Department of Communication Systems Institute for Infocomm Research Singapore Singapore Department of Software and Information Science Iwate Prefectural University Japan

ISBN: (纸本)9781424469178

Effective and meaningful visualization techniques are quite important for multidimensional DNA microarray gene expression data analysis. Elucidating the cluster properties of these multidimensional data are often complex. Patterns, hypotheses on the relationships, and ultimately of the function of the gene can be analyzed and visualized by non-linear reduction of the multidimensional data to a lower dimension. In this paper, an improved SOM visualization technique named Improved Side Intensity Modulated (ISIM) Self-Organizing Map (SOM) has been proposed and compared with other SOM based visualization techniques. On different datasets, ISIM-SOM is found to offer better cluster boundary, simplicity and clarity. © 2010 IEEE.

关键词： Self organizing maps

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A Visual Approach to Improve Clustering Based on Cluster Ensembles

A Visual Approach to Improve Clustering Based on Cluster Ens...

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conference on visualization and data analysis 2010

作者： Zhou, Jianping Konecni, Shawn Marx, Kenneth Grinstein, Georges Univ Massachusetts Lowell Lowell MA 01854 USA

ISBN: (纸本)9780819479235

Iterative clustering (e.g. K-Means, EM) is one of the most commonly used clustering methods, which attempts to iteratively find a local optimum starting from an initial condition, including initial centroids and initial number of clusters. For iterative clustering, research has shown that the initial conditions are crucial to clustering quality and running time of a clustering computation. Using a novel visualization tool, CComViz (Cluster Comparison visualization), we present an innovative approach to refine the initial centroids and the number of clusters by visually analyzing multiple clustering results generated by different clustering algorithms. As an example, we apply our new approach to a gene expression case study for generating a better and converging clustering. The proposed approach is considered to be an extension to cluster ensembles since the original data sources are reused, while in classic cluster ensembles they are not.

关键词： Biology and genetics Classifier design and evaluation Clustering visualization techniques and methodologies

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MIXING VIRTUAL REALITY AND 2D visualization Using Virtual Environments as Visual 3D Information Systems for Discussion of data from Geo- and Environmental Sciences

MIXING VIRTUAL REALITY AND 2D VISUALIZATION <i>Using Virtual...

引用

5th International conference on Computer Graphics Theory and Applications (GRAPP 2010)

作者： Zehner, Bjoern UFZ Helmholtz Ctr Environm Res Permoserstr 15 D-04318 Leipzig Germany

ISBN: (纸本)9789896740269

3D stereoscopic visualization and virtual reality techniques are increasingly used for quality control, analysis and discussion of 3D geoscientific data in the oil and gas industry. They provide an excellent and easily comprehensible insight into complex 3D structures of the earth's subsurface. However, in many research topics in environmental and geosciences the analysis of data usually also involves data that might be better viewed in 2D. Examples are maps or histograms. The use of virtual environments as visual information systems for the efficient communication and discussion of complex multi-attribute data sets also requires 2D data to be visualized with a high quality. Further it is often not possible to show all the relevant information simultaneously and so an interactive virtual environment is required that provides an overview and the necessary interaction techniques to select additional information, e.g. from a database, to be visualized on request. This article describes the hardware setup installed at the UFZ Centre for Environmental Research and a software solution for how to use this setup efficiently to connect 2D data representations with 3D visualization and interaction.

关键词： Virtual environments GIS 3D interaction 3D visual information system visualization Geosciences

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Metric data analysis enhanced through temporal visualization

Metric data analysis enhanced through temporal visualization

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14th International conference on Information Visualisation (IV)

作者： Bueno, Renato Razente, Humberto L. Kaster, Daniel S. Barioni, Maria Camila N. Traina, Agma J. M. Traina, Caetano, Jr. Fed Univ Sao Carlos UFSCar Sao Carlos SP Brazil Fed Univ ABC UFABC Santo Andre SP Brazil Univ Londrina UEL Londrina PR Brazil Univ Sao Paulo Sao Carlos SP Brazil

ISBN: (纸本)9780769541655

The human vision can naturally interpret data in spaces of 2 or 3 dimensions. When data is in higher dimensional spaces, in most cases the visualization is not intuitive. Regarding metric spaces, the interpretation is even harder, since they often do not have a direct spatial representation. However, the need to analyze how metric-represented data evolve over time is pretty common when one needs to understand several phenomena and in decision making processes, as it occurs in medical and agrometeorological applications. This paper presents three interactive techniques to visualize metric data that vary over time. Each one focus on a different way to interpret the temporal information. The first technique shows data evolving in a timeline axis. The second overlaps evolving snapshots of the space showing how the space varies regarding time. The last one does not treat temporal data as a dimension, it is used instead to define the similarity among complex data, employing the new concept of metric-temporal spaces, which seamlessly integrate time and metric data into a single similarity space. visualization examples with real datasets are presented to show the usefulness of the proposed techniques.

关键词： visualization of temporal data metric spaces

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Linked Exploratory visualizations for Uncertain MR Spectroscopy data

Linked Exploratory Visualizations for Uncertain MR Spectrosc...

引用

conference on visualization and data analysis 2010

作者： Feng, David Kwock, Lester Lee, Yueh Taylor, Russell M., II Univ N Carolina Chapel Hill NC 27515 USA

ISBN: (纸本)9780819479235

We present a system for visualizing magnetic resonance spectroscopy (MRS) data sets. Using MRS, radiologists generate multiple 3D scalar fields of metabolite concentrations within the brain and compare them to anatomical magnetic resonance imaging. By understanding the relationship between metabolic makeup and anatomical structure, radiologists hope to better diagnose and treat tumors and lesions. Our system consists of three linked visualizations: a spatial glyph-based technique we call Scaled data-Driven Spheres, a parallel coordinates visualization augmented to incorporate uncertainty in the data, and a slice plane for accurate data value extraction. The parallel coordinates visualization uses specialized brush interactions designed to help users identify nontrivial linear relationships between scalar fields. We describe two novel contributions to parallel coordinates visualizations: linear function brushing and new axis construction. Users have discovered significant relationships among metabolites and anatomy by linking interactions between the three visualizations.

关键词： medical visualization multivariate data parallel coordinates glyphs linked views uncertainty visualization

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PHASE CORRECTION AND DENOISING FOR ICA OF COMPLEX FMRI data

PHASE CORRECTION AND DENOISING FOR ICA OF COMPLEX FMRI DATA

引用

2010 IEEE International conference on Acoustics, Speech, and Signal Processing

作者： Rodriguez, Pedro Adali, Tuelay Li, Hualiang Correa, Nicolle Calhoun, Vince D. Univ Maryland Baltimore Cty Dept CSEE Baltimore MD 21250 USA Univ New Mexico MIND Res Network Dept ECE Albuquerque NM 87131 USA

ISBN: (纸本)9781424442966

analysis of functional magnetic resonance imaging (fMRI) data in its native, complex form has been shown to increase the sensitivity of the analysis both for data driven techniques such as independent component analysis (ICA) and for model-driven techniques;however, the noisy nature of the phase poses a challenge for successful study of fMRI data. In addition, for complex ICA, the inherent scaling ambiguity, which has a phase term, introduces additional difficulty for group analysis and visualization of the results. In this paper, we address these issues, which have been among the main reasons phase information has been traditionally discarded and introduce a phase correction scheme that can be either applied subsequent to ICA of fMRI data or can be incorporated into the ICA algorithm in the form of prior information to eliminate the need for further processing for phase correction. In addition, we introduce methods for visualization of the analysis results as well as preprocessing the complex fMRI data to mitigate the effects of noise in the phase which are not limited to ICA algorithms. We demonstrate the successful application of the methods using actual fMRI data.

关键词： Phase correction denoising complex-valued fMRI ICA

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