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26th Annual CHI conference on Human Factors in Computing Systems

作者： Shrinivasan, Yedendra B. van Wijk, Jarke J. Tech Univ Eindhoven Dept Math & Comp Sci Eindhoven Netherlands

ISBN: (纸本)9781605580111

This paper presents anew information visualization framework that supports the analytical reasoning process. It consists of three views - a data view, a knowledge view and a navigation view. The data view offers interactive information visualization tools. The knowledge view enables the analyst to record analysis artifacts such as findings, hypotheses and so on. The navigation view provides an overview of the exploration process by capturing the visualization states automatically. An analysis artifact recorded in the knowledge view can be linked to a visualization state in the navigation view. The analyst can revisit a visualization state from both the navigation and knowledge views to review the analysis and reuse it to look for alternate views. The whole analysis process can be saved along with the synthesized information. We present a user study and discuss the perceived usefulness of a prototype based on this framework that we have developed.

关键词： visual analytics analytical reasoning process information visualization

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ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining

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BMC BIOINFORMATICS 2008年第9期9卷 1-13页

作者： Huan, Tianxiao Sivachenko, Andrey Y. Harrison, Scott H. Chen, Jake Y. Indiana Univ Purdue Univ Sch Informat Indianapolis IN 46202 USA Indiana Ctr Syst Biol & Personalized Med Indianapolis IN 46202 USA Purdue Univ Dept Comp & Informat Sci Indianapolis IN 46202 USA Shandong Univ Coll Life Sci Jinan 250100 Peoples R China MIT Broad Inst Cambridge MA 02141 USA Harvard Univ Cambridge MA 02141 USA

Background: New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. Results: We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both data Definition Languages (DDL) and data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc;2) applying network data association rules to build the network and perform the visual annotation of graph node

关键词： Association Rule Structure Query Language Network visualization visual Annotation Biomolecular Network

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Unveiling intrinsic similarity -: Application to temporal analysis of ECG

Unveiling intrinsic similarity -: Application to temporal an...

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1st International conference on Bio-Inspired Systems and Signal Processing

作者： Lourenco, Andre Fred, Ana Inst Super Engn Lisboa Inst Telecomun Lisbon Portugal

ISBN: (纸本)9789898111180

The representation of data in some visual form is one of the first steps in a data-mining process in order to gain some insight about its structure. We propose to explore well known visualization and unsupervised learning techniques, namely clustering, to improve the understanding about the data and to enhance possible relations or intrinsic similarity between patterns. Specifically, Clustering Ensemble Methods are exploited separately and combined to provide a clearer visualization of data organization. The presented methodology is used to improve the understanding of ECG signal acquired during Human Computer Interaction (HCI).

关键词： visualization unsupervised learning Clustering evidence accumulation clustering co-association matrix ECG analysis behavior identification

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The Empirical Research on the Relationship between Employee Psychological Contract and Job Satisfaction

The Empirical Research on the Relationship between Employee ...

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1st International conference on Information Management, Innovation Management and Industrial Engineering

作者： Cui Huibao Zhang Shuo Ding Qiang Shandong Univ Technol Sch Management Zibo 255049 Peoples R China China Mobile Grp Design Inst Co Ltd Jinan 250001 Peoples R China

ISBN: (纸本)9780769534350

Psychological contract is the vital ligament between enterprise and employees. From the visual angle of employee, the paper conducts empirical research on the relationship between employee psychological contract and job satisfaction by questionnaire investigation. In the research, the samples are selected from employees of representative enterprises in Shandong province, and data collected are analyzed by SPSS 13.0 with methods such as factor analysis, reliability analysis, correlation analysis and regression analysis. By analysis results can be drawn as follows. There are two facets which are organization obligation and employee obligation in employee psychological contract, and both of them include three dimensions: transactional obligation, relational obligation and developmental obligation. Job satisfaction consists of five dimensions which are job itself, working payback, working group, working condition and enterprise management. And there is a significant positive linear correlation between employee psychological contract and job satisfaction, namely, better fulfillment of employee psychological contract tends to make the level of job satisfaction higher. Finally, on the basis of these research conclusions, the issues need to be further studied are also discussed.

关键词： Psychology Contracts Innovation management Technology management Information management Industrial engineering conference management Engineering management Ligaments data analysis

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12th International conference Information visualisation 2008

作者： Alencar, A. B. Paulovich, F. V. Minghim, R. Andrade, M. G. Oliveira, M. C. R. Univ Sao Paulo Inst Ciencias Matemat & Computacao BR-05508 Sao Paulo Brazil

ISBN: (纸本)9780769532684

Time series analysis poses many challenges to professionals in a wide range of domains. Several visualization solutions have been proposed for exploratory tasks on time series collections. For large data sets, however current techniques fail to provide a global view that supports a good association between groups of similar time series. We employ fast multidimensional projection techniques to create concise visual representations of a collection of time series. The whole collection can be viewed in a two-dimensional graph-based representation that provides a starting point for further exploration and detailed analysis. The projections employ distance metrics to compare the series and generate a layout that attempts to group those with similar behavior. We illustrate the approach on a real data set containing streamflows describing the behavior of hydroelectric power plants in Brazil.

关键词： Hydroelectric power plants

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XMAS: An experiential approach for visualization, analysis, and exploration of time series microarray data

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Communications in Computer and Information Science 2008年 13卷 16-31页

作者： Dalziel, Ben Yang, Hui Singh, Rahul Gormley, Matthew Fisher, Susan Department of Computer Science San Francisco State University San Francisco CA United States Departments of Cell and Tissue Biology University of California San Francisco San Francisco CA United States Department of Anatomy University of California San Francisco San Francisco CA United States Departments of Obstetrics Gynecology and Reproductive Sciences University of California San Francisco San Francisco CA United States Departments of Pharmaceutical Chemistry University of California San Francisco San Francisco CA United States Institute for Regeneration Medicine and the Human embryonic Stem Cell Program University of California San Francisco San Francisco CA United States

ISBN: (纸本)9783540705987

Time series microarray analysis provides an invaluable insight into the genetic progression of biological processes, such as pregnancy and disease. Many algorithms and systems exist to meet the challenge of extracting knowledge from the resultant data sets, but traditional methods limit user interaction, and depend heavily on statistical, black box techniques. In this paper we present a new design philosophy based on increased human computer synergy to overcome these limitations, and facilitate an improved analysis experience. We present an implementation of this philosophy, XMAS (eXperiential Microarray analysis System) which supports a new kind of "sit forward" analysis through visual interaction and interoperable operators. Domain knowledge, (such as pathway information) is integrated directly into the system to aid users in their analysis. In contrast to the "sit back", algorithmic approach of traditional systems, XMAS emphasizes interaction and the power, and knowledge transfer potential of facilitating an analysis in which the user directly experiences the data. Evaluation demonstrates the significance and necessity of such a philosophy and approach, proving the efficacy of XMAS not only as tool for validation and sense making, but also as an unparalleled source of serendipitous results. Finally, one can download XMAS at http://***/~huiyang/xmas_website/***. © Springer-Verlag Berlin Heidelberg 2008.

关键词： Time series analysis

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analysis of multi-objective evolutionary algorithms to optimize dynamic data types in embedded systems 08

Analysis of multi-objective evolutionary algorithms to optim...

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10th Annual Genetic and Evolutionary Computation conference, GECCO 2008

作者： Hidalgo, J. Ignacio Risco-Martín, José L. Atienza, David Lanchares, Juan Department of Computer Architecture and Automation Complutense University of Madrid Prof. José García Santesmases s/n 28040 Madrid Spain

ISBN: (纸本)9781605581309

New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated data Types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large design space of possible DDTs implementations. Thus, suitable exploration methods for embedded design metrics (memory accesses, memory usage and power consumption) need to be developed. In this work we present a detailed analysis of the characteristics of different types of Multi-Objective Evolutionary Algorithms (MOEAs) to tackle the optimization of DDTs in multimedia applications and compare them with other state-of-the-art heuristics. Our results with state-of-the-art MOEAs in two object-oriented multi-media embedded applications show that more sophisticated MOEAs (SPEA2 and NSGA-ii) offer better solutions than simple schemes (VEGA). Moreover, the suitable sophisticated scheme varies according to the available exploration time, namely, NSGA-ii outperforms SPEA2 in the first set of solutions (300-500 generations), while SPEA2 offers better solutions afterwards. Copyright 2008 ACM.

关键词： Multiobjective optimization

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ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining

ProteoLens: a visual analytic tool for multi-scale database-...

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5th Annual conference of the MidSouth-Computational-Biology-and-Bioinformatics-Society

关键词： visualization

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visual steering commands and test problems to support research in trade space exploration

Visual steering commands and test problems to support resear...

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作者： Simpson, Timothy W. Spencer, David B. Yukish, Michael A. Stump, Gary Pennsylvania State University University Park PA 16802 United States Applied Research Laboratory State College PA 16804 United States Department of Mechanical Engineering and Industrial Engineering 314D Leonhard Building United States Department of Aerospace Engineering Australia Product and Process Design Department Australia

ISBN: (纸本)9781563479472

Designers can simulate thousands, if not millions, of design alternatives more cheaply and quickly than ever before with today's computing power;however, the resulting data can overwhelm designers without proper tools to support multi-dimensional data visualization. In this paper, we discuss the use of a multi-dimensional data visualization tool and visual steering commands which allow designers to navigate multi-attribute trade spaces. The novelty in our work is providing designers with a set of visual steering commands to simultaneously explore the trade space and exploit new information and insights as they are gained. Specifically, designers can explore the entire design space (either sampled randomly or manually) or along the entire Pareto front using the Basic Sampler, Point Sampler, and/or Pareto Sampler. Alternatively, they can exploit information they have gained during the exploration process by searching near a specific point of interest or within a region of high preference using the Attractor, Preference Sampler, and/or Guided Pareto Sampler. Examples of each are included in this paper. Meanwhile, a suite of test problems is being formalized to support our trade space exploration - algorithmic development as well as empirical studies involving human decision-makers. This work supports our long-term goal of quantifying the benefits of putting humans back "in-the-loop" during design optimization. Copyright © 2008 by Timothy W. Simpson.

关键词： Commerce

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Exploratory 3D geovisual analytics

Exploratory 3D geovisual analytics

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RIVF 2008 - 2008 IEEE International conference on Research, Innovation and Vision for the Future in Computing and Communication Technologies

作者： Ho, Quan Jern, Mikael Department of Science and Technology University of Linkoping Norrkoping Sweden

ISBN: (纸本)9781424423798

In this paper, we extend our generic "GeoAnalytics" visualization (GAV) component toolkit, based on the principles behind visual Analytics (VA), to also support time-oriented, geographically referenced and multivariate attribute volumetric data. GAV includes components that support a mixture of technologies from the three data visualization fields: information visualization (InfoVis), geovisualization (GeoVis) and scientific visualization (SciVis). Our research concentrates on visual user interface (VUI) techniques through dynamic and direct data manipulation that permit the visual analytical process to become more interactive and focused. This paper encourages synergies between well-known information- and volume data visualization methods applied in a multiple-linked and coordinated views interface. We address challenges for improved data interaction techniques with volumetric data and the need for immediate response. Varieties of explorative data analysis (EDA) tasks and the possibility to view the information simultaneously from different perspectives and scenarios are discussed. The effectiveness of our geovisual analytics framework is demonstrated in a tailor-made volume data explorer (VDE) application that integrates InfoVis, GeoVis and SciVis visualization methods assembled from GAV components. VDE facilitates dynamic exploration and correlation of temporal ocean space temperature and salinity data supplied in a NetCDF format from NOAA. This real-world phenomenon that corresponds to a huge volumetric data set comprises more than 31 million values for a time period of 12 months in 1994. ©2008 IEEE.

关键词： data visualization

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