2016 IEEE Pacific Visualization Symposium (PacificVis)最新文献_第4页

Interactive exploration of atomic trajectories through relative-angle distribution and associated uncertainties 通过相对角度分布和相关不确定性的原子轨迹的交互探索

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-19 DOI: 10.1109/PACIFICVIS.2016.7465259

H. Bhatia, A. Gyulassy, Valerio Pascucci, Martina Bremer, M. Ong, V. Lordi, E. Draeger, J. Pask, P. Bremer

{"title":"Interactive exploration of atomic trajectories through relative-angle distribution and associated uncertainties","authors":"H. Bhatia, A. Gyulassy, Valerio Pascucci, Martina Bremer, M. Ong, V. Lordi, E. Draeger, J. Pask, P. Bremer","doi":"10.1109/PACIFICVIS.2016.7465259","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2016.7465259","url":null,"abstract":"Exploration of atomic trajectories is fundamental to understanding and characterizing complex chemical systems important in many applications. For instance, any new insight into the mechanisms of ionic migration in catalytic materials could lead to a substantial increase in battery performance. A new statistical measure, called the relative-angle distribution, has been proposed to understand complex motion - whether Brownian, ballistic, or diffusive. The relative-angle distribution can be represented as a collection of 1D histograms, but is currently created in a slow, offline process, making any parameter exploration a tedious and time-consuming task. Furthermore, the resulting plot can hide uncertainty in both the data and the visualization. As a result, once rastered or printed at a fixed resolution, these histograms can be misleading. We present a new analysis tool for the exploration of atomic trajectories that combines an interactive histogram visualization with uncertainty information for both data and plotting errors, and is also linked to an interactive 3D display of trajectories. Our tool enables a holistic exploration of trajectories previously not feasible, with the potential for significant scientific impact. In collaboration with domain experts, we have deployed our tool ta analyze molecular dynamics simulations of lithium-ion diffusion. Users have found that the tool significantly accelerates the exploration process and have used it to validate a number of previously unconfirmed hypotheses.","PeriodicalId":129600,"journal":{"name":"2016 IEEE Pacific Visualization Symposium (PacificVis)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115715454","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: 1

Semantic word cloud generation based on word embeddings 基于词嵌入的语义词云生成

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-19 DOI: 10.1109/PACIFICVIS.2016.7465278

Jin Xu, Y. Tao, Hai Lin

引用次数: 40

Geo word clouds 地理字云

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-19 DOI: 10.1109/pacificvis.2016.7465262

K. Buchin, D. Creemers, Andrea Lazzarotto, B. Speckmann, J. Wulms

{"title":"Geo word clouds","authors":"K. Buchin, D. Creemers, Andrea Lazzarotto, B. Speckmann, J. Wulms","doi":"10.1109/pacificvis.2016.7465262","DOIUrl":"https://doi.org/10.1109/pacificvis.2016.7465262","url":null,"abstract":"Word clouds are a popular method to visualize the frequency of words in textual data. Nowadays many text-based data sets, such as Flickr tags, are geo-referenced, that is, they have an important spatial component. However, existing automated methods to generate word clouds are unable to incorporate such spatial information. We introduce geo word clouds: word clouds which capture not only the frequency but also the spatial relevance of words. Our input is a set of locations from one (or more) geographic regions with (possibly several) text labels per location. We aggregate word frequencies according to point clusters and employ a greedy strategy to place appropriately sized labels without overlap as close as possible to their corresponding locations. While doing so we \"draw\" the spatial shapes of the geographic regions with the corresponding labels. We experimentally explore trade-offs concerning the location of labels, their relative sizes and the number of spatial clusters. The resulting word clouds are visually pleasing and have a low error in terms of relative scaling and locational accuracy of words, while using a small number of clusters per label.","PeriodicalId":129600,"journal":{"name":"2016 IEEE Pacific Visualization Symposium (PacificVis)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122440876","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: 21

SepMe: 2002 New visual separation measures 2002年9月9日新的视觉分隔措施

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-19 DOI: 10.1109/PACIFICVIS.2016.7465244

Michaël Aupetit, M. Sedlmair

引用次数: 43

Bookwall: Visualizing books online based on user experience in physical bookstores Bookwall:基于实体书店用户体验的在线图书可视化

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-19 DOI: 10.1109/PACIFICVIS.2016.7465280

Hsin-I Chen, Wei-Ting Lin, Bing-Yu Chen

引用次数: 3

Rethinking sensitivity analysis of nuclear simulations with topology 基于拓扑的核模拟灵敏度分析再思考

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-01 DOI: 10.1109/PACIFICVIS.2016.7465252

D. Maljovec, Bei Wang, P. Rosen, A. Alfonsi, G. Pastore, C. Rabiti, Valerio Pascucci

{"title":"Rethinking sensitivity analysis of nuclear simulations with topology","authors":"D. Maljovec, Bei Wang, P. Rosen, A. Alfonsi, G. Pastore, C. Rabiti, Valerio Pascucci","doi":"10.1109/PACIFICVIS.2016.7465252","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2016.7465252","url":null,"abstract":"In nuclear engineering, understanding the safety margins of the nuclear reactor via simulations is arguably of paramount importance in predicting and preventing nuclear accidents. It is therefore crucial to perform sensitivity analysis to understand how changes in the model inputs affect the outputs. Modern nuclear simulation tools rely on numerical representations of the sensitivity information - inherently lacking in visual encodings - offering limited effectiveness in communicating and exploring the generated data. In this paper, we design a framework for sensitivity analysis and visualization of multidimensional nuclear simulation data using partition-based, topology-inspired regression models and report on its efficacy. We rely on the established Morse-Smale regression technique, which allows us to partition the domain into monotonic regions where easily interpretable linear models can be used to assess the influence of inputs on the output variability. The underlying computation is augmented with an intuitive and interactive visual design to effectively communicate sensitivity information to nuclear scientists. Our framework is being deployed into the multipurpose probabilistic risk assessment and uncertainty quantification framework RAVEN (Reactor Analysis and Virtual Control Environment). We evaluate our framework using a simulation dataset studying nuclear fuel performance.","PeriodicalId":129600,"journal":{"name":"2016 IEEE Pacific Visualization Symposium (PacificVis)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129867346","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: 14

NetworkSeer: Visual analysis for social network in MOOCs NetworkSeer: mooc中社交网络的可视化分析

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-01 DOI: 10.1109/PACIFICVIS.2016.7465269

Tongshuang Sherry Wu, Y. Yao, Y. Duan, Xinzhi Fan, Huamin Qu

引用次数: 22

STAC: Enhancing stacked graphs for time series analysis 增强时间序列分析的堆叠图

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-01 DOI: 10.1109/PACIFICVIS.2016.7465277

Yun Wang, Tongshuang Sherry Wu, Zhutian Chen, Qiong Luo, Huamin Qu

{"title":"STAC: Enhancing stacked graphs for time series analysis","authors":"Yun Wang, Tongshuang Sherry Wu, Zhutian Chen, Qiong Luo, Huamin Qu","doi":"10.1109/PACIFICVIS.2016.7465277","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2016.7465277","url":null,"abstract":"Stacked graphs have been widely used to represent multiple time series simultaneously to show the changes of individual values and their aggregation over time. However, when the number of time series becomes very large, the layers representing time series with small values take up only very small proportions in the stacked graph, making them hard to trace. As a result, it is challenging for analysts to detect the correlation of individual layers and their aggregation, and find trend similarities and differences between layers solely with stacked graphs. In this paper, we study the correlations of individual layers, and their aggregation in time series data presented with stacked graphs, focusing on the local regions within any given time intervals. Specifically, we present STAC, an interactive visual analytics system, to help analysts gain insights into the correlations in stacked graphs. While preserving the original stacked shape, we further link a stacked graph with auxiliary views to facilitate the in-depth analysis of correlations in time series data. A case study based on a real-world dataset demonstrates the effectiveness of our system in gaining insights into time series data analysis and facilitating various analytical tasks.","PeriodicalId":129600,"journal":{"name":"2016 IEEE Pacific Visualization Symposium (PacificVis)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126967467","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: 5

Visual monitoring of process runs: An application study for stored procedures 过程运行的可视化监控:存储过程的应用研究

2016 IEEE Pacific Visualization Symposium (PacificVis) Pub Date : 2016-04-01 DOI: 10.1109/PACIFICVIS.2016.7465264

M. Meyer, Fabian Beck, S. Lohmann

引用次数: 1