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检索条件"任意字段=4th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2014"

共 68 条记录，以下是51-60 订阅

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Static Correlation visualization for large Time-Varying Volume data

Static Correlation Visualization for Large Time-Varying Volu...

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4th ieee Pacific visualization symposium

作者： Chen, Cheng-Kai Wang, Chaoli Ma, Kwan-Liu Wittenberg, Andrew T. Univ Calif Davis Davis CA 95616 USA Michigan Tech Houghton MI 49931 USA NOAA Silver Spring MD 20910 USA

ISBN: (纸本)9781612849324

Finding correlations among data is one of the most essential tasks in many scientific investigations and discoveries. this paper addresses the issue of creating a static volume classification that summarizes the correlation connection in time-varying multivariate data sets. In practice, computing all temporal and spatial correlations for large 3D time-varying multivariate data sets is prohibitively expensive. We present a sampling-based approach to classifying correlation patterns. Our sampling scheme consists of three steps: selecting important samples from the volume, prioritizing distance computation for sample pairs, and approximating volume-based correlation with sample-based correlation. We classify sample voxels to produce static visualization that succinctly summarize the connection among all correlation volumes with respect to various reference locations. We also investigate the error introduced by each step of our sampling scheme in terms of classification accuracy. Domain scientists participated in this work and helped us select samples and evaluate results. Our approach is generally applicable to the analysis of other scientific data where correlation study is relevant.

关键词： reference locations dataset time varying visualization Correlation analysis

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Design of Soil Pollution Prevention and Control Evaluation and analysis Platform based on WebGIS 4

Design of Soil Pollution Prevention and Control Evaluation a...

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4th International symposium on Computer Technology and Information Science, ISCTIS 2024

作者： Liu, Derong Liang, Hong Gao, Kun Yunnan University School of Information Science and Technology Yunnan Kunming China

ISBN: (纸本)9798350354560

this study focuses on heavy metal pollution in Yunnan Province and designed and developed a data informatization platform for soil environmental quality monitoring and data informatization for pollution control. the platform integrates a large amount of existing heterogeneous data resources from multiple sources, enabling WebGIS visualization of soil environmental quality and pollution, data analysis and graph presentation, thematic mapping and evaluation analysis report generation, and functions for assessing soil environmental quality and determining the causes of agricultural pollution and building areas [1]. By adopting the latest technological architecture such as NodeJS, VueJS and Cesium, the platform achieves efficient data integration, transmission, analysis and visualization, improving the efficiency of analysis, monitoring and control of soil pollution data. the platform uses the single-factor method, the comprehensive Nemerow index method and the analytical hierarchy process as soil pollution assessment methods, combined with coordinated monitoring of heavy metal content in agricultural products, making the assessment results more comprehensive and accurate. this system will help improve soil environmental quality monitoring and pollution control capabilities in Yunnan Province by providing comprehensive and accurate baseline data and scientific decision support to government agencies. © 2024 ieee.

关键词： Soil pollution control

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Remote visualization using resource monitoring technique for volume rendering of large datasets

Remote visualization using resource monitoring technique for...

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4th International symposium on Applications and the Internet (SAINT 2004)

作者： Ebara, Y Watashiba, Y Koyamada, K Sakai, K Doi, A Kyoto Univ Sakyo Ku Kyoto 6068501 Japan

ISBN: (纸本)0769520685

We present a remote visualization using resource monitoring technique for volume rendering which breaks a large volume data into pieces (sub-volumes) so as to maintain volume rendering processing in physical memory in consideration of the available system resources. Each sub-volume is transferred to a rendering PC (personal computer), which performs hardware accelerated volume rendering and generates a partial image (sub-image). the sub-images are piled up in depth order to complete the final image. this technique has been applied to remote visualization of 3-D finite element analysis result of 3-D flow through a lateral saccular aneurysm, and we evaluated at remote places between Kyoto and Iwate. As a result, we showed that it is possible to perform rendering of large dataset that surpasses the available resource on the client side, and our technique was effective the remote visualization.

关键词： database systems

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SeedMe: A cyberinfrastructure for sharing results

SeedMe: A cyberinfrastructure for sharing results

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ieee symposium on large data analysis and visualization (ldav)

作者： Amit Chourasia Mona Wong-Barnum David Nadeau Michael L Norman University of California San Diego La Jolla CA US San Diego Supercomputer Center University of California San Diego

Computational simulations have become an indispensible tool in a wide variety of science and engineering investigations. Nearly all scientific computation and analyses create transient data and preliminary results, these may consist of text, binary files and visualization images. Quick and effective assessments of these data are necessary for efficient use of the computation resources, but this is complicated when a large collaborating team is geographically dispersed and/or some team members do not have direct access to the computation resource and output data. Current methods for sharing and assessing transient data and preliminary results are cumbersome, labor intensive, and largely unsupported by useful tools and procedures. Each research team is forced to create their own scripts and ad hoc procedures to push data from system to system, and user to user, and to make quick plots, images, and videos to guide the next step in their research. these custom efforts often rely on email, ftp, and scp, despite the ubiquity of much more flexible dynamic web-based technologies and the impressive display and interaction abilities of today's mobile devices. To fill this critical gap we have developed SeedMe (Swiftly Encode, Explore and Disseminate My Experiments), is a web-based architecture to enable the rapid sharing of content directly from applications running on High Performance Computing or cloud resources. SeedMe converts a slow, manual, serial, error prone, repetitive, and redundant sharing and assessment process into a streamlined automatic and web accessible cyberinfrastructure. We provide an easy to use sharing model with granular access control, and mobile device support. SeedMe provides secure input and output complementing HPC resources, without compromising their security model, and thereby expand and extend their capabilities. SeedMe aims to foster rapid assessment, iteration, communication, and dissemination of transient data and preliminary results by seed

关键词： Transient analysis data visualization Educational institutions Supercomputers Computational modeling Videos Electronic mail

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Automated Valuation of Leaves Area for large-Scale analysis Needing data Coupling or Petioles Deletion

Automated Valuation of Leaves Area for Large-Scale Analysis ...

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ieee 4th International symposium on Plant Growth Modeling, Simulation, visualization and Applications (PMA)

作者： Borianne, P. Brunel, G. Cirad UMR Amap F-34000 Montpellier France

ISBN: (纸本)9781467300704;9781467300674

In this paper, we present a new fully-automated approach to analyze the geometry of homogeneous leaves from numerical images produced by a desktop scanner. Our method is focused on two particular aspects: data coupling, specifically weights and areas matching, and numerical deletion of petioles, both in a large-scale analysis context. the process limits user interaction, the leaves segmentation is self conditioned and realized by a k-means classification giving the threshold value for each image. the results are arranged according to the leaves disposition on the scanner pane: the leaves labels are defined by recognitions of rows, obtained by clustering. the result layout eases the data coupling, i.e. the matching of individual leaves measures produced by different devices. We do also propose a new automated petiole removal procedure. the deletion method, applied to each single leaf, uses a morphological analysis from the leaf medial line. the process is adaptive, without expert calibration. the method is implemented in a ready to use application. Tests hold on several data sets show satisfactory results on a wide range of leaf shapes.

关键词： pattern recognition automated image processing leaf segmentation petiole deletion measure coupling large-scale-analysis image processing plug-in

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Sequential data visualization

Sequential data visualization

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International University Communication symposium

作者： Chen, Wei State Key Lab. of CAD and CG Zhejiang University Hangzhou China

ISBN: (纸本)9781424478200

Creating appropriate methods to facilitate the analysis of sequential data is a key issue in many applications. In this talk, we focus on the unique role of the parameter time in the context of visually driven data analysis. We will discuss three major aspects visualization, analysis, and user interaction. It is necessary to consider the characteristics of sequentiality when generating visual representations. Integrating visual and analytical methods has become an increasingly important issue. We present our experiences in temporal data abstraction, principal component analysis, and clustering of large-sized sequential data. Finally, we describe our experiences on supporting user-centered visual analysis. ©2010 ieee.

关键词： data visualization

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ieee Pacific visualization symposium 2011, PacificVis 2011 - Proceedings

IEEE Pacific Visualization Symposium 2011, PacificVis 2011 -...

引用

4th ieee Pacific visualization symposium 2011, PacificVis 2011

ISBN: (纸本)9781612849324

the proceedings contain 26 papers. the topics discussed include: full-resolution interactive CPU volume rendering with coherent BVH traversal;context-aware volume navigation;multi-dimensional transfer function design based on flexible dimension projection embedded in parallel coordinates;static correlation visualization for large time-varying volume data;the neuron navigator: exploring the information pathway through the neural maze;CareCruiser: exploring and visualizing plans, events, and effects interactively;loose capacity-constrained representatives for the qualitative visual analysis in molecular dynamics;interactive seismic interpretation with piecewise global energy minimization;uncertain topology of 3D vector fields;edge maps: representing flow with bounded error;view point evaluation and streamline filtering for flow visualization;and dual space analysis of turbulent combustion particle data.

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SEGrapher: visualization-based SELinux policy analysis

SEGrapher: Visualization-based SELinux policy analysis

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ieee 4th symposium on Configuration Analytics and Automation, SAFECONFIG 2011

作者： Marouf, Said Shehab, Mohamed Department of Software and Information Systems University of North Carolina at Charlotte Charlotte NC United States

ISBN: (纸本)9781467304016

Performing SELinux policy analyses can be difficult due to the complexity of the policy language and the sheer number of policy rules and attributes involved. For example, the default policy on most SELinux-enabled systems has over 1;500;000 flat rules, involving over 1;780 types. Simple analyses between types can result in a large amount of data, which is poorly presented to administrators in existing analysis tools. We propose and implement a policy analysis tool "SEGrapher" that addresses the above challenges. SEGrapher visually presents analysis results as a simplified directed graph, where nodes are types, and edges are corresponding policy rules between types. Graphs are generated via a proposed clustering algorithm that clusters types based on their accesses. Clusters provide an abstraction layer that removes undesired data, and focuses on analysis attributes specified by the administrator. © 2011 ieee.

关键词： Directed graphs

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Proceedings - 2012 ieee 4th International symposium on Plant Growth Modeling, Simulation, visualization and Applications, PMA 2012

Proceedings - 2012 IEEE 4th International Symposium on Plant...

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2012 ieee 4th International symposium on Plant Growth Modeling, Simulation, visualization and Applications, PMA 2012

ISBN: (纸本)9781467300681

the proceedings contain 71 papers. the topics discussed include: functional structural plant modeling: applications beyond the plant;when growth controls photosynthesis;topological object types for morphodynamic modeling languages;enhancing on farm and regional irrigation management using MABIA-region tool;mathematical analysis of vector-borne diseases on plants;evaluation of the predictive capacity of five plant growth models for sugar beet;analyzing global climatic change and its impact on fruit tree phenology using ClimaTree tool: example of Anna apple tree under Tunisian conditions;variability of pea morphogenesis. an exploratory study based on six pea genotypes with contrasting architectures;automated valuation of leaves area for large-scale analysis needing data coupling or petioles deletion;and automatic characterization of the cell organization in light microscopic images of wood: application to the identification of the cell file.

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Comparison of Multiple large Fluid-Structure Interaction Simulations in Virtual Reality

Comparison of Multiple Large Fluid-Structure Interaction Sim...

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ieee symposium on large data analysis and visualization (ldav)

作者： Daniel Orban Seth Johnson Hakizumwami Birali Runesha Lingyu Meng Bethany Juhnke Arthur Erdman Francesca Samsel Daniel F. Keefe University of Minnesota University of Chicago University of Texas Austin

ISBN: (纸本)9781538668740

Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].

关键词： data visualization Graphics processing units Solids Rendering (computer graphics) Lead Heart Solid modeling

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