SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)最新文献_第2页

Visual analytics of brain effective connectivity using convergent cross mapping 使用收敛交叉映射的大脑有效连接可视化分析

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139303

H. Natsukawa, K. Koyamada

{"title":"Visual analytics of brain effective connectivity using convergent cross mapping","authors":"H. Natsukawa, K. Koyamada","doi":"10.1145/3139295.3139303","DOIUrl":"https://doi.org/10.1145/3139295.3139303","url":null,"abstract":"To elucidate the dynamics of information processing in the brain, it is necessary to identify the direction of neural information transmission in the neuronal network and clarify the effects (i.e., the causal relationship) of neuronal activity in one area on neuronal activity in another area. Convergent cross mapping (CCM) has been employed in the neuroscience field to examine the effective connectivity of brain functions. CCM can detect causality from time series data created from deterministic and nonlinear systems. Because CCM includes complicated processes such as the determination of advance parameters, the confirmation of nonlinearity, and the interpretation of results, which results in a lowering of the usability of CCM, there is a strong need for an effective visual interface. In this paper, we propose a visual analytic system that increases the usability of CCM and contributes to new discoveries in effective connectivity. The usability was evaluated using a domain expert questionnaire. It was confirmed that the usability was improved by comparing the proposed system to the original character user interface from the viewpoint of the results and process comprehensibility. In addition, with the proposed system, new findings in human brain connectivity have been obtained from actual magnetoencephalography data during visual cognitive task and resting-state task.","PeriodicalId":92446,"journal":{"name":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89605000","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: 6

Mobile situated analytics of ego-centric network data 移动定位的自我中心网络数据分析

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139309

Mingqian Zhao, Yijia Su, Jian Zhao, Shaoyu Chen, Huamin Qu

{"title":"Mobile situated analytics of ego-centric network data","authors":"Mingqian Zhao, Yijia Su, Jian Zhao, Shaoyu Chen, Huamin Qu","doi":"10.1145/3139295.3139309","DOIUrl":"https://doi.org/10.1145/3139295.3139309","url":null,"abstract":"Situated Analytics has become popular and important with the resurge of Augmented Reality techniques and the prevalence of mobile platforms. However, existing Situated Analytics could only assist in simple visual analytical tasks such as data retrieval, and most visualization systems capable of aiding complex Visual Analytics are only designed for desktops. Thus, there remain lots of open questions about how to adapt desktop visualization systems to mobile platforms. In this paper, we conduct a study to discuss challenges and trade-offs during the process of adapting an existing desktop system to a mobile platform. With a specific example of interest, egoSlider [Wu et al. 2016], a four-view dynamic ego-centric network visualization system is tailored to adapt the iPhone platform. We study how different view management techniques and interactions influence the effectiveness of presenting multi-scale visualizations including Scatterplot and Storyline visualizations. Simultaneously, a novel Main view+Thumbnails interface layout is devised to support smooth linking between multiple views on mobile platforms. We assess the effectiveness of our system through expert interviews with four experts in data visualization.","PeriodicalId":92446,"journal":{"name":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88208097","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: 6

Smooth animation of structure evolution in time-varying graphs with pattern matching 基于模式匹配的时变图形结构演化平滑动画

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139302

Yunzhe Wang, G. Baciu, Chenhui Li

引用次数: 1

Optimal tree reordering for group-in-a-box graph layouts 盒中组图布局的最优树重新排序

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139308

Yosuke Onoue, K. Koyamada

{"title":"Optimal tree reordering for group-in-a-box graph layouts","authors":"Yosuke Onoue, K. Koyamada","doi":"10.1145/3139295.3139308","DOIUrl":"https://doi.org/10.1145/3139295.3139308","url":null,"abstract":"Visualizing the group structure of graphs is important in analyzing complex networks. The group structure referred to here includes not only community structures defined in terms of modularity and the like but also group divisions based on node attributes. Group-In-a-Box (GIB) is a graph-drawing method designed for visualizing the group structure of graphs. Using a GIB layout, it is possible to simultaneously visualize group sizes and both within-group and between-group structures. However, conventional GIB layouts do not optimize display of between-group relations, causing many long edges to appear in the graph area and potentially reducing graph readability. This paper focuses on the tree structure of treemap used in GIB layouts as a basis for proposing a tree-reordered GIB (TRGIB) layout with a procedure for replacing sibling nodes in the tree structure. Group proximity is defined in terms of between-group distances and connection weights, and an optimal tree reordering problem (OTRP) that minimizes group proximity is formulated as a mixed-integer linear programming (MILP) problem. Through computational experiments, we show that optimal layout generation is possible in practical time by solving the OTRP using a general mathematical programming solver.","PeriodicalId":92446,"journal":{"name":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72846093","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: 2

Development of a visual analytics system for cell division dynamics in early C.elegans embryos 早期秀丽隐杆线虫胚胎细胞分裂动力学可视化分析系统的开发

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139310

Sayaka Nagai, Naohisa Sakamoto

引用次数: 1

Winding angle assisted particle tracing in distribution-based vector field 基于分布的矢量场中缠绕角辅助粒子跟踪

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139297

Cheng Li, Han-Wei Shen

引用次数: 1

SIGGRAPH Asia 2017 Symposium on Visualization SIGGRAPH亚洲2017可视化研讨会

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295

K. Koyamada, Puripant Ruchikachorn

引用次数: 0

A multi-layered visualization language for video augmentation 一种用于视频增强的多层可视化语言

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-27 DOI: 10.1145/3139295.3139307

Danny Zhu, M. Veloso

引用次数: 0

ISAVS: Interactive Scalable Analysis and Visualization System. 交互式可扩展分析和可视化系统。

SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand) Pub Date : 2017-11-01 DOI: 10.1145/3139295.3139299

Steve Petruzza, Aniketh Venkat, Attila Gyulassy, Giorgio Scorzelli, Valerio Pascucci, Frederick Federer, Alessandra Angelucci, Peer-Timo Bremer

{"title":"ISAVS: Interactive Scalable Analysis and Visualization System.","authors":"Steve Petruzza, Aniketh Venkat, Attila Gyulassy, Giorgio Scorzelli, Valerio Pascucci, Frederick Federer, Alessandra Angelucci, Peer-Timo Bremer","doi":"10.1145/3139295.3139299","DOIUrl":"https://doi.org/10.1145/3139295.3139299","url":null,"abstract":"<p><p>Modern science is inundated with ever increasing data sizes as computational capabilities and image acquisition techniques continue to improve. For example, simulations are tackling ever larger domains with higher fidelity, and high-throughput microscopy techniques generate larger data that are fundamental to gather biologically and medically relevant insights. As the image sizes exceed memory, and even sometimes local disk space, each step in a scientific workflow is impacted. Current software solutions enable data exploration with limited interactivity for visualization and analytic tasks. Furthermore analysis on HPC systems often require complex hand-written parallel implementations of algorithms that suffer from poor portability and maintainability. We present a software infrastructure that simplifies end-to-end visualization and analysis of massive data. First, a hierarchical streaming data access layer enables interactive exploration of remote data, with fast data fetching to test analytics on subsets of the data. Second, a library simplifies the process of developing new analytics algorithms, allowing users to rapidly prototype new approaches and deploy them in an HPC setting. Third, a scalable runtime system automates mapping analysis algorithms to whatever computational hardware is available, reducing the complexity of developing scaling algorithms. We demonstrate the usability and performance of our system using a use case from neuroscience: filtering, registration, and visualization of tera-scale microscopy data. We evaluate the performance of our system using a leadership-class supercomputer, Shaheen II.</p>","PeriodicalId":92446,"journal":{"name":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","volume":"2017 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3139295.3139299","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36432295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4