2015 IEEE Pacific Visualization Symposium (PacificVis)最新文献_第2页

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156379

Yu Meng, Hui Zhang, Mengchen Liu, Shixia Liu

引用次数: 15

Visual exploration of Location-Based Social Networks data in urban planning 基于位置的社交网络数据在城市规划中的可视化探索

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156367

D. F. Prieto, Eva Hagen, D. Engel, Dirk Bayer, J. T. Hernández, C. Garth, Inga Scheler

{"title":"Visual exploration of Location-Based Social Networks data in urban planning","authors":"D. F. Prieto, Eva Hagen, D. Engel, Dirk Bayer, J. T. Hernández, C. Garth, Inga Scheler","doi":"10.1109/PACIFICVIS.2015.7156367","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156367","url":null,"abstract":"The increasing amount of data generated by Location Based Social Networks (LBSN) such as Twitter, Flickr, or Foursquare, is currently drawing the attention of urban planners, as it is a new source of data that contains valuable information about the behavior of the inhabitants of a city. Making this data accessible to the urban planning domain can add value to the decision making processes. However, the analysis of the spatial and temporal characteristics of this data in the context of urban planning is an ongoing research problem. This paper describes ongoing work in the design and development of a visual exploration tool to facilitate this task. The proposed design provides an approach towards the integration of a visual exploration tool and the capabilities of a visual query system from a multilevel perspective (e.g., multiple spatial scales and temporal resolutions implicit in LBSN data). A preliminary discussion about the design and the potential insights that can be gained from the exploration and analysis of this data with the proposed tool is presented, along with the conclusions and future work for the continuation of this work.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129698741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Uncertainty modeling and error reduction for pathline computation in time-varying flow fields 时变流场路径计算的不确定性建模与误差减小

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156380

Chun-Ming Chen, Ayan Biswas, Han-Wei Shen

{"title":"Uncertainty modeling and error reduction for pathline computation in time-varying flow fields","authors":"Chun-Ming Chen, Ayan Biswas, Han-Wei Shen","doi":"10.1109/PACIFICVIS.2015.7156380","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156380","url":null,"abstract":"When the spatial and temporal resolutions of a time-varying simulation become very high, it is not possible to process or store data from every time step due to the high computation and storage cost. Although using uniformly down-sampled data for visualization is a common practice, important information in the un-stored data can be lost. Currently, linear interpolation is a popular method used to approximate data between the stored time steps. For pathline computation, however, errors from the interpolated velocity in the time dimension can accumulate quickly and make the trajectories rather unreliable. To inform the scientist the error involved in the visualization, it is important to quantify and display the uncertainty, and more importantly, to reduce the error whenever possible. In this paper, we present an algorithm to model temporal interpolation error, and an error reduction scheme to improve the data accuracy for temporally down-sampled data. We show that it is possible to compute polynomial regression and measure the interpolation errors incrementally with one sequential scan of the time-varying flow field. We also show empirically that when the data sequence is fitted with least-squares regression, the errors can be approximated with a Gaussian distribution. With the end positions of particle traces stored, we show that our error modeling scheme can better estimate the intermediate particle trajectories between the stored time steps based on a maximum likelihood method that utilizes forward and backward particle traces.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126550612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Adaptive particle relaxation for time surfaces 时间表面的自适应粒子弛豫

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156371

A. Berres, H. Obermaier, K. Joy, H. Hagen

引用次数: 1

Visualizing 2D scalar fields with hierarchical topology 可视化二维标量场与分层拓扑

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156370

Keqin Wu, Song Zhang

引用次数: 7

Biclustering multivariate data for correlated subspace mining 多变量数据的双聚类相关子空间挖掘

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156389

Kazuho Watanabe, Hsiang-Yun Wu, Yusuke Niibe, Shigeo Takahashi, I. Fujishiro

{"title":"Biclustering multivariate data for correlated subspace mining","authors":"Kazuho Watanabe, Hsiang-Yun Wu, Yusuke Niibe, Shigeo Takahashi, I. Fujishiro","doi":"10.1109/PACIFICVIS.2015.7156389","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156389","url":null,"abstract":"Exploring feature subspaces is one of promising approaches to analyzing and understanding the important patterns in multivariate data. If relying too much on effective enhancements in manual interventions, the associated results depend heavily on the knowledge and skills of users performing the data analysis. This paper presents a novel approach to extracting feature subspaces from multivariate data by incorporating biclustering techniques. The approach has been maximally automated in the sense that highly-correlated dimensions are automatically grouped to form subspaces, which effectively supports further exploration of them. A key idea behind our approach lies in a new mathematical formulation of asymmetric biclustering, by combining spherical k-means clustering for grouping highly-correlated dimensions, together with ordinary k-means clustering for identifying subsets of data samples. Lower-dimensional representations of data in feature subspaces are successfully visualized by parallel coordinate plot, where we project the data samples of correlated dimensions to one composite axis through dimensionality reduction schemes. Several experimental results of our data analysis together with discussions will be provided to assess the capability of our approach.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"405 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134474139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Efficient volume illumination with multiple light sources through selective light updates 通过选择性光更新，具有多个光源的高效体照明

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156382

E. Sundén, T. Ropinski

引用次数: 8

Computation-to-core mapping strategies for iso-surface volume rendering on GPUs gpu等面体绘制的计算到核映射策略

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156372

Junpeng Wang, Fei Yang, Yong Cao

引用次数: 4

CloudGazer: A divide-and-conquer approach to monitoring and optimizing cloud-based networks CloudGazer:一种分而治之的方法，用于监控和优化基于云的网络

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156375

Holger Stitz, S. Gratzl, M. T. Krieger, M. Streit

{"title":"CloudGazer: A divide-and-conquer approach to monitoring and optimizing cloud-based networks","authors":"Holger Stitz, S. Gratzl, M. T. Krieger, M. Streit","doi":"10.1109/PACIFICVIS.2015.7156375","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156375","url":null,"abstract":"With the rise of virtualization and cloud-based networks of various scales and degrees of complexity, new approaches to managing such infrastructures are required. In these networks, relationships among components can be of arbitrary cardinality (1:1, 1:n, n:m), making it challenging for administrators to investigate which components influence others. In this paper we present CloudGazer, a scalable visualization system that allows users to monitor and optimize cloud-based networks effectively to reduce energy consumption and to increase the quality of service. Instead of visualizing the overall network, we split the graph into semantic perspectives that provide a much simpler view of the network. CloudGazer is a multiple coordinated view system that visualizes either static or live status information about the components of a perspective while reintroducing lost inter-perspective relationships on demand using dynamically created inlays. We demonstrate the effectiveness of CloudGazer in two usage scenarios: The first is based on a real-world network of our domain partners where static performance parameters are used to find an optimal design. In the second scenario we use the VAST 2013 Challenge dataset to demonstrate how the system can be employed with live streaming data.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127636098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Dendrogramix: A hybrid tree-matrix visualization technique to support interactive exploration of dendrograms 树形图:一个混合的树矩阵可视化技术，支持树形图的交互式探索

2015 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2015-04-14 DOI: 10.1109/PACIFICVIS.2015.7156353

R. Blanch, Rémy Dautriche, G. Bisson

{"title":"Dendrogramix: A hybrid tree-matrix visualization technique to support interactive exploration of dendrograms","authors":"R. Blanch, Rémy Dautriche, G. Bisson","doi":"10.1109/PACIFICVIS.2015.7156353","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156353","url":null,"abstract":"Clustering is often a first step when trying to make sense of a large data set. A wide family of cluster analysis algorithms, namely hierarchical clustering algorithms, does not provide a partition of the data set but a hierarchy of clusters organized in a binary tree, known as a dendrogram. The dendrogram has a classical node-link representation used by experts for various tasks like: to decide which subtrees are actual clusters (e.g., by cutting the dendrogram at a given depth); to give those clusters a name by inspecting their content; etc. We present Dendrogramix, a hybrid tree-matrix interactive visualization of dendrograms that superimposes the relationship between individual objects on to the hierarchy of clusters. Dendrogramix enables users to do tasks which involve both clusters and individual objects that are impracticable with the classical representation, like: to explain why a particular objects belongs to a particular cluster; to elicit and understand uncommon patterns (e.g., objects that could have been classified in a totally different cluster); etc. Those sensemaking tasks are supported by a consistent set of interaction techniques that facilitates the exploration of large clustering results.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116354829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20