基于Web的PSE-Bio交互式可视化

PSE-Bio是一个基于Web服务面向生物信息学的问题求解平台。为了方便用户仅使用浏览器就能分析调用服务返回的结果,采用SVG技术实现基于WEB的可视化,设计了面向对象的统一可视化数据对象以封装调用不同Web服务返回的消息;设计了面向对象的可视化图形对象以利于交互可视化的实现;并用SVG脚本语言实现了用户与图形的交互以及可视化结果与服务的交互。实验结果表明,基于SVG的可视化方案能够满足生物信息数据的Web可视化需求。     

FIRST: a flexible and interactive resampling tool for CFD simulation data

We introduce a flexible, variable resolution tool for interactive resampling of computational fluid dynamics (CFD) simulation data on versatile grids. The tool and coupled algorithm afford users precise control of glyph placement during vector field visualization via six interactive degrees of freedom. Other important characteristics of this method include: (1) an algorithm that resamples any unstructured grid onto any structured grid, (2) handles changes to underlying topology and geometry, (3) handles unstructured grids with holes and discontinuities, (4) does not rely on any pre-processing of the data, and (5) processes large numbers of unstructured grid cells efficiently. We believe this tool to be a valuable asset in the engineer's pursuit of understanding and visualizing the underlying flow field in CFD simulation results.     

Geoic: an interactive terminal-based geochemical data processing system

A series of interactive terminal-based FORTRAN IV programs have been developed for processing and evaluating major and trace element data produced in the analysis of rock samples. The GEOIC system consists of three stages. The first is concerned with the processing of analytical data produced in the X-ray fluorescence (XRF) analysis of fused samples for major elements and pressed powder briquettes for trace elements. In the second stage, the major and trace element results are linked together by a tabulation program which creates an input file for CIPW norm programs. The tabulation program will sort also the analyses into groups according to an 8 character “group identifier” keyword attached to each analysis. Average analyses are calculated also for each group. The tabulation program combines the major, trace and normative data to produce a data base file as well as a tabulated output file for dispatch to a line printer. In the third stage, the data base file serves as the input to interactive programs for graphical and statistical evaluation of the geochemical data. The graphics program allows the user to plot rapidly binary and ternary diagrams for all samples or plotting may be restricted to specified groups or only to the group averages. The statistical program allows the user to calculate various parameters as well as a correlation coefficient matrix for all samples, for selected groups or for only group averages.The group identifier keyword attached by the user to each sample analysis facilitates the division of the suite of samples under study into groups and subgroups. This important feature adds considerable flexibility to the processing and evaluation of data via the tabulation, graphics and statistics programs.The tabulation program will accept also free-format major and trace element data produced by analytical methods other than XRF. The second and third stages of the system may be used, therefore, as a general purpose geochemical data processing and evaluation package.     

Highly interactive distributed visualization

We report on our iGrid2005 demonstration, called the “Dead Cat Demo”; an example of a highly interactive augmented reality application consisting of software services distributed over a wide-area, high-speed network. We describe our design decisions, analyse the implications of the design on application performance and show performance measurements.     

电子商务数据挖掘可视化系统模型研究及应用

将数据挖掘与相关的数据可视化技术和联机分析处理技术集成,构造一个应用于电子商务Web环境中的以数据挖掘技术为基础的数据可视化分析系统模型——电子商务数据挖掘可视化模型(EDVM),并技术实现主要模块功能,使之能够进行挖掘结果的动态更新与可视化输出,并通过实验初步验证了EDVM模型的有效性。     

Visual transformation for interactive spatiotemporal data mining

Analytical models intend to reveal inner structure, dynamics, or relationship of things. However, they are not necessarily intuitive to humans. Conventional scientific visualization methods are intuitive, but limited by depth, dimension, and resolution. The purpose of this study is to bridge the gap with transformation algorithms for mapping the data from an abstract space to an intuitive one, which include shape correlation, periodicity, multiphysics, and spatial Bayesian. We tested this approach with the oceanographic case study. We found that the interactive visualization increases robustness in object tracking and positive detection accuracy in object prediction. We also found that the interactive method enables the user to process the image data at less than 1 min per image versus 30 min per image manually. As a result, our test system can handle at least 10 times more data sets than traditional manual analyses. The results also suggest that minimal human interactions with appropriate computational transformations or cues may significantly increase the overall productivity. Yang Cai is Director of Ambient Intelligence Laboratory and Faculty of Cylab and Institute of Complex Engineered Systems (ICES), Carnegie Mellon University, and Professor of Industrial Design at Modern Industrial Design Institute, Zhejiang University, P.R. China. He was Systems Scientist at Human–Computer Interaction Institute, Senior Scientist in CMRI at CMU, and Senior Designer for Daimler Chrysler. Cai’s interests include pattern recognition, visualization, and Ambient Intelligence. He cochaired international workshops in Ambient Intelligence for Scientific Discovery, Vienna, 2004 and AmI for Everyday Life, Spain, 2005 and Digital Human Modeling, UK, 2006. He is Editor of the Lecture Notes in Artificial Intelligence, LNAI 3345 and LNAI 3864, published by Springer. He was NASA Faculty Fellow in 2003 and 2004. Richard Stumpf is a Senior Oceanographer and Team Leader of Remote Sensing National Oceanic and Atmospheric Administration (NOAA), Center for Coastal Monitoring and Assessment, Silver Spring, MD, where he leads 6–10 team members developing remote sensing capabilities for NOAA. Dr. Stumpf has extensively published papers on remote sensing for monitoring and forecasting harmful algal blooms and river plumes. He received his Ph.D. in Oceanography. Timothy Wynne is an oceanographer with I.M. Systems Group and NOAA. Primarily his work at NOAA has involved ocean color imagery with an emphasis on algal bloom detection. He has also used remotely sensed data to quantify resuspension events. He has a M.S. in Oceanography from Old Dominion University and a B.S. in Marine Science from the Richard Stockton College of New Jersey. Michelle Tomlinson has been an Oceanographer with the Center for Coastal Monitoring and Assessment, National Ocean Service, NOAA since 2002. Her current research focuses on the application of satellite-derived ocean color sensors (SeaWiFS, MODIS, MERIS) to detect, monitor, and forecast the occurrence of harmful algal blooms. This work has led to the development of an operational forecast system for harmful Karenia brevis blooms in the Gulf of Mexico. She received her B.S. in Marine Science Biology from Southampton College of Long Island University, and a M.S. in Oceanography from Old Dominion University. Daniel Sai Ho (Daniel) Chung is a Master of Science Degree Student at the Institute of Networked Information, Carnegie Mellon University. He has been a Research Assistant in the Ambient Intelligence Laboratory since 2004, where he developed data mining and wireless video streaming systems for NASA and TRB-sponsored projects. Xavier Boutonnier is a Research Assistant at Carnegie Mellon University, CYLAB—Ambient Intelligence Laboratory, Pittsburgh, PA, USA. He is a Master of Science Degree Student at the National Superior School of Electronics of Toulouse (ENSEEIHT) in France. He specialized in Signal, Image, Acoustic, and optimization. He has been working with Dr. Yang Cai on the NASA-sponsored data mining project. His favorite fields of application are Video, Image, acoustic, and other signal processing. Matthias Ihmig is pursuing his Ph.D. in the area of software-defined radio at Munich Technical University, while he is working at BMW, Germany. He was an Intern Graduate Student at Carnegie Mellon University, USA. His interests include stereo vision, wireless networks, and intelligent systems. Rafael Franco is a Master’s Degree Student in Electronics and Telecommunications at the Engineering School of ENSEEIHT in France. Currently, he is an Intern at Cylab working on assignments related to information visualization and wireless user positioning. Nathaniel Bauernfeind is a Research Assistant at Carnegie Mellon University, CYLAB—Ambient Intelligence Laboratory, Pittsburgh, PA, USA. He is a Computer Science and Mathematics student in the School of Computer Science at CMU. His research interests include computational algorithms, 3D graphics programming, and artificial intelligence. He is working with Dr. Yang Cai on a driving simulator that focuses on algorithmic automation for General Motors.     

WeVoS-ViSOM: An ensemble summarization algorithm for enhanced data visualization

This study presents a novel version of the Visualization Induced Self-Organizing Map based on the application of a new fusion algorithm for summarizing the results of an ensemble of topology-preserving mapping models. The algorithm is referred to as Weighted Voting Superposition (WeVoS). Its main feature is the preservation of the topology of the map, in order to obtain the most accurate possible visualization of the data sets under study. To do so, a weighted voting process between the units of the maps in the ensemble takes place, in order to determine the characteristics of the units of the resulting map. Several different quality measures are applied to this novel neural architecture known as WeVoS-ViSOM and the results are analyzed, so as to present a thorough study of its capabilities. To complete the study, it has also been compared with the well-know SOM and its fusion version, with the WeVoS-SOM and with two other previously devised fusion Fusion by Euclidean Distance and Fusion by Voronoi Polygon Similarity—based on the analysis of the same quality measures in order to present a complete analysis of its capabilities. All three summarization methods were applied to three widely used data sets from the UCI Repository. A rigorous performance analysis clearly demonstrates that the novel fusion algorithm outperforms the other single and summarization methods in terms of data sets visualization.     

An interactive 3D medical visualization system based on a light field display

We present a prototype medical data visualization system exploiting a light field display and custom direct volume rendering techniques to enhance understanding of massive volumetric data, such as CT, MRI, and PET scans. The system can be integrated with standard medical image archives and extends the capabilities of current radiology workstations by supporting real-time rendering of volumes of potentially unlimited size on light field displays generating dynamic observer-independent light fields. The system allows multiple untracked naked-eye users in a sufficiently large interaction area to coherently perceive rendered volumes as real objects, with stereo and motion parallax cues. In this way, an effective collaborative analysis of volumetric data can be achieved. Evaluation tests demonstrate the usefulness of the generated depth cues and the improved performance in understanding complex spatial structures with respect to standard techniques.

The Pascal graphics system

A two dimensional high level graphics programming system based on the CORE standard graphics system¹ has been implemented. The graphics programming language used in the system is an extension of the programming language Pascal. In this paper the graphics programming features in this system are presented and the implementation issues are discussed.     

GlyphLink: An interactive visualization approach for semantic graphs

Graph analysis by data visualization involves achieving a series of topology-based tasks. When the graph data belongs to a data domain that contains multiple node and link types, as in the case of semantic graphs, topology-based tasks become more challenging. To reduce visual complexity in semantic graphs, we propose an approach which is based on applying relational operations such as selecting and joining nodes of different types. We use node aggregation to reflect the relational operations to the graph. We introduce glyphs for representing aggregated nodes. Using glyphs lets us encode connectivity information of multiple nodes with a single glyph. We also use visual parameters of the glyph to encode node attributes or type specific information. Rather than doing the operations in the data abstraction layer and presenting the user with the resulting visualization, we propose an interactive approach where the user can iteratively apply the relational operations directly on the visualization. We present the efficiency of our method by the results of a usability study that includes a case study on a subset of the International Movie Database. The results of the controlled experiment in our usability study indicate a statistically significant contribution in reducing the completion time of the evaluation tasks.     

Web-based dynamic and interactive environmental visualization

The development of novel interactive visualizations can substantially contribute to environmental modeling and understanding of complex environmental processes. To allow the Web Map Service (WMS) to support this, this paper explores a generic framework in which a dynamic environmental modeling process can be interactively visualized, controlled and tuned on the Internet by using Java 3D-based hybrid Internet computation through the simulation steering technique. A hydrological model, TOPMODEL, is employed to illustrate the simulation of a rainfall-run off process within a computational and steering environment. This environment allows users to visually interact and experiment with model computation, thereby facilitating the exploration of process-based environmental applications.     

Categorical data visualization and clustering using subjective factors

Clustering is an important data mining problem. However, most earlier work on clustering focused on numeric attributes which have a natural ordering to their attribute values. Recently, clustering data with categorical attributes, whose attribute values do not have a natural ordering, has received more attention. A common issue in cluster analysis is that there is no single correct answer to the number of clusters, since cluster analysis involves human subjective judgement. Interactive visualization is one of the methods where users can decide a proper clustering parameters. In this paper, a new clustering approach called CDCS (Categorical Data Clustering with Subjective factors) is introduced, where a visualization tool for clustered categorical data is developed such that the result of adjusting parameters is instantly reflected. The experiment shows that CDCS generates high quality clusters compared to other typical algorithms.     

基于GPU光线投射算法的心脏体数据三维可视化

心脏成像和可视化技术在心脏疾病诊断、治疗规划中发挥着重要作用。针对分割后的心脏体数据集,提出了使用图形处理器(GPU)加速光线投射算法进行高质量三维可视化的新方法。该方法结合心脏体数据统计信息设计传递函数,增大细微组织的不透明度值;基于梯度模自适应地调整采样步长,提高组织边界的采样频率;应用改进的Blinn-Phong多光源光照模型,增强可视化效果。实验结果表明,该方法在实现实时绘制的同时,能够获得高质量的体绘制效果,渲染出清晰的瓣膜和冠状动脉血管等心脏细微组织。     

Distributed and collaborative visualization of large data sets using high-speed networks

We describe an architecture for distributed collaborative visualization that integrates video conferencing, distributed data management and grid technologies as well as tangible interaction devices for visualization. High-speed, low-latency optical networks support high-quality collaborative interaction and remote visualization of large data.     

An interactive tool for the visualization of cathode-ray tube monitor gamuts

The aim of this work was the development of an interactive tool for the visualization and the comparison of cathode-ray tube monitor gamuts.     

Design of an integrated data retrieval, analysis, and visualization system: Application in the hydrology domain

In this paper, we present a prototype system, an integrated data management system, which is capable of querying, retrieving, and visualizing datasets with heterogeneous formats and large sizes without requiring users to have any knowledge of any other specific software. Our system has three distinguished characteristics: (1) modular structure and simple architecture which make it easy and feasible for users to add new functions and features to the system, (2) a new search concept and method based on the bounding box and on dynamically delineated watershed boundary from GIS (Geographic Information System), and (3) no requirement on having any knowledge about or installation of any other complicated software. The architecture of our integrated data management system is based on a metadata approach, which consists of four components including a metadata mechanism and a Java-based application engine. The metadata mechanism in conjunction with the Java-based application engine allows users to access and retrieve diverse data formats and structures from many heterogeneous hydrological data sources. The visualization component of the system makes it possible for users to view their queried data first before spending time retrieving them. The extensible and integrative characteristics of our system are illustrated by an example in which new and unique functions for data merging and GIS-based data querying are added to the system. Although the data sources and applications shown in this prototype system are related to the field of hydrology, the ideas, approaches, and system architecture are not domain-specific, and can be used/applied to other fields as well.     

Pursuing interactive visualization of irregular grids

Many branches of the sciences produce sample data not arranged on rectilinear grids, and visualization of such data is generally more complex than visualizing more regular data. While isosurface algorithms such as marching cubes can be adapted with relatively little performance penalty, direct volume rendering presents more difficulties. This paper explores these issues, concentrating on algorithms for a particular kind of irregular grid known as a curvilinear grid, composed of six-sided cells that may be considered a result of the deformation of a regular rectilinear grid.     

Practice and experience with BASIS: An interactive programming system for introductory courses in informatics

The BASIS system is an interactive and conversational system, written in Pascal, to be used in the workshop of the introductory course in informatics. Its language is a subset of Pascal. Based on some years of experience with several versions of the system, we will discuss some implementational aspects.     

A divide-and-conquer local search heuristic for data visualization

Data visualization techniques have become important tools for analyzing large multidimensional data sets and providing insights with respect to scientific, economic, and engineering applications. Typically, these visualization applications are modeled and solved using nonlinear optimization techniques. In this paper, we propose a discretization of the data visualization problem that allows us to formulate it as a quadratic assignment problem. However, this formulation is computationally difficult to solve optimally using an exact approach. Consequently, we investigate the use of a local search technique for the data visualization problem. The space in which the data points are to be embedded can be discretized using an n×n$n\times n$ lattice. Conducting a local search on this n×n$n\times n$ lattice is computationally ineffective. Instead, we propose a divide-and-conquer local search approach that refines the lattice at each step. We show that this approach is much faster than conducting local search on the entire n×n$n\times n$ lattice and, in general, it generates higher quality solutions. We envision two uses of our divide-and-conquer local search heuristic: (1) as a stand-alone approach for data visualization, and (2) to provide a good approximate starting solution for a nonlinear algorithm.     

基于GPS数据可视化的智能拼车软件设计与实现

为减缓交通拥挤,降低污染物排放,提出基于GPS数据可视化的拼车系统体系结构,讨论城市交通路网构建、用户路径信息获取、匹配方案查询、空间数据可视化的设计与实现方法。在此基础上,基于.NET平台开发一套基础软件,基于Processing平台开发拼车信息数据可视化系统。对沈阳市500名真实用户的出行路线进行的分析测试验证了该智能拼车系统的可行性及实用性。