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检索条件"任意字段=Conference on Visual Data Exploration and Analysis II"

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Context-aware visual exploration of molecular databases

Context-aware visual exploration of molecular databases

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作者： Di Fatta, Giuseppe Fiannaca, Antonino Rizzo, Riccardo Urso, Alfonso Berthold, Michael R. Gaglio, Salvatore School of Systems Engineering University of Reading Whiteknights Reading Berkshire RG6 6AY United Kingdom ICAR-CNR National Research Council 90128 Palermo Italy Department of Computer and Information Science University of Konstanz 78457 Konstanz Germany DINFO University of Palermo 90128 Palermo Italy

ISBN: (纸本)0769527027

Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self-organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions. © 2006 IEEE.

关键词： Molecules

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Task-at-hand interface for change detection in stock market data 06

Task-at-hand interface for change detection in stock market ...

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AVI '06 - Working conference on Advanced visual Interfaces 2006

作者： Merino, Carmen Sanz Sips, Mike Keim, Daniel A. Panse, Christian Spence, Robert MicroStrategy Ibrica Madrid Spain University of Konstanz Germany FGCZ-Uni ETH Zurich Switzerland Imperial College London United Kingdom

ISBN: (纸本)1595933530

Companies trading stocks need to store information on stock prices over specific time intervals, which results in very large databases. Large quantities of numerical data (thousands of records) are virtually impossible to understand quickly and require the use of a visual model, since that is the fastest way for a human brain to absorb those enormous collections of data. However, little work has been done on verifying which visualizations are more suitable to represent these data sets. Such work is of crucial importance, since it enables us to identify those useful visual models and, in addition, opens our minds to new research possibilities. This paper presents an empirical study of different visualizations, that have been employed for stock market data, by comparing the results obtained by all studied techniques in typical exploratory data analysis tasks. This work provides several research contributions to the design of advanced visual data exploration interfaces. Copyright 2006 ACM.

关键词： Interfaces (computer)

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A Java framework for data sonification and 3D graphic rendering

A Java framework for data sonification and 3D graphic render...

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Sound and Music Computing conference, SMC 2006

作者： Vicinanza, Domenico University of Salerno - Musica inaudita Department of Mathematics and Computer Science Italy

data audification is the representation of data by means of sound signals (waveforms or melodies typically). Although most data analysis techniques are exclusively visual in nature, data presentation and exploration systems could benefit greatly from the addition of sonification capabilities. In addition to that, sonic representations are particularly useful when dealing with complex, high-dimensional data, or in data monitoring or analysis tasks where the main goal is the recognition of patterns and recurrent structures. The main goal of this paper is to briefly present the audification process as a mapping between a discrete data set and a discrete set of notes (we shall deal with MIDI representation), and look at a couple of different examples from two well distinguished fields, geophysics and linguistics (seismograms sonificaton and text sonification). Finally the paper will present another example of the mapping between data sets and other information, namely a 3D graphic image generation (rendered with POVRay) driven by the ASCii text.

关键词： Mapping

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Time series relevance determination through a topology-constrained hidden Markov model

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7th International conference on Intelligent data Engineering and Automated Learning (IDEAL 2006)

作者： Olier, Ivan Vellido, Alfredo Univ Politecn Cataluna Dept Comp Languages & Syst LSI Barcelona 08034 Spain

ISBN: (纸本)3540454853

Most of the existing research on multivariate time series concerns supervised forecasting problems. In comparison, little research has been devoted to unsupervised methods for the visual exploration of this type of data. The interpretability of time series clustering results may be difficult, even in exploratory visualization, for high dimensional datasets. In this paper, we define and test an unsupervised time series relevance determination method for Generative Topographic Mapping Through Time, a topology-constrained Hidden Markov Model that performs simultaneous time series data clustering and visualization. This relevance determination method can be used as a basis for time series selection, and should ease the interpretation of the time series clustering results.

关键词： Time series analysis

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exploration of the vector fusion method for basic behavior unit segmentation from visual data

Exploration of the vector fusion method for basic behavior u...

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2006 IEEE International conference on Multisensor Fusion and Integration for Intelligent Systems, MFI

作者： Xue, Xinwei Henderson, Thomas C. School of Computing University of Utah Salt Lake City UT 84112 United States Faculty of School of Computing University of Utah Salt Lake City UT 84112 United States

ISBN: (纸本)1424405661

It becomes an increasingly important research area to automatically analyze object behaviors from visually captured data (e.g., motion) or video recordings. Among this research, the automatic basic behavior unit (BBU) discovery is very important. In this paper, we explore the applicability of the vector fusion (SBP) method, a multi-variate vector visualization technique, in BBU segmentation. This technique is also inherently a data dimension reduction technique: it reduces the multiple dimensional data into two dimensional (SBP)space, and the spatial and temporal analysis in SBP space can help discover the underlying data groups. We present results on a physical system and a synthetic mouse-in-a-cage scenario. The vector fusion method provides a good distinction and interpretation for the bouncing ball example and the analytical data from the synthetic video simulation upon certain selected features. Our experiments show that several factors influence the effectiveness of the vector fusion method in BBU segmentation. The temporal analysis in SBP space seems to be very effective to detect periodic BBUs. Overall, this method is simple and effective for grouping BBUs with periodic motion. © 2006 IEEE.

关键词： Vector quantization

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Proceedings of the 3rd International Workshop on visualization for Computer Security, VizSEC'06. Co-located with t he 13th ACM conference on Computer and Communications Security, CCS'06

Proceedings of the 3rd International Workshop on Visualizati...

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3rd International Workshop on visualization for Computer Security, VizSEC'06. Co-located with the 13th ACM conference on Computer and Communications Security, CCS'06

ISBN: (纸本)1595935495

The proceedings contain 19 papers. The topics discussed include: understanding multistage attacks by attack-track based visualization of heterogeneous event streams;visual toolkit for network security experiment specification and data analysis;an intelligent, interactive tool for exploration and visualization of time-oriented security data;visualizing DNS traffic;real-time collaborative network monitoring and control using 3D game engines for representation and interaction;using visual motifs to classify encrypted traffic;visualization assisted detection of sybil attacks in wireless networks;ensuring the continuing success of VizSec;VAST: visualizing autonomous system topology;discovering an RC4 anomaly through visualization;visualizations to improve reactivity towards security incidents inside corporate networks;visualization for privacy compliance;and interactively combining 2D and 3D visualization for network traffic monitoring.

关键词： Intrusion detection

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Balancing systematic and flexible exploration of social networks

Balancing systematic and flexible exploration of social netw...

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IEEE visualization conference (Vis 2006)/IEEE Symposium on Information visualization (InfoVis 2006)

作者： Perer, Adam Shneiderman, Ben Univ Maryland Dept Comp Sci College Pk MD 20742 USA

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks.

关键词： social networks interactive graph visualization attribute ranking coordinated views exploratory data analysis

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Review of bioinspired real-time motion analysis systems

Review of bioinspired real-time motion analysis systems

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conference on BioMEMS and Nanotechnology ii

作者： Rainsford, T Al-Sarawi, S Bender, A Univ Adelaide Ctr Biomed Engn Sch Elect & Elect Engn Adelaide SA 5005 Australia Univ Adelaide Ctr Biomed Engn Ctr High Performance Integrated Technol & Syst CH Adelaide SA 5005 Australia Def Sci & Technol Org Land Operat Div Edinburgh SA 5111 Australia

ISBN: (纸本)0819460672

Flying insects are able to manoeuvre through complex environments with remarkable ease and accuracy despite their simple visual system. Physiological evidence suggests that flight control is primarily guided by a small system of neurons tuned to very specific types of complex motion. This system is a promising model for bio-inspired approaches to low-cost artificial motion analysis systems, such as collision avoidance devices. A number of models of motion detection have been proposed, with the basic model being the Reichardt Correlator. Electrophysiological data suggest a variety of non-linear elaborations, which include compressive non-linearities and adaptive feedback of local motion detector outputs. In this paper we review a number of computational models for motion detection from the point of view of ease of implementation in low cost VLSI technology. We summarise the features of biological motion analysis systems that are important for the design of real-time artificial motion analysis systems. Then we report on recent progress in bio-inspired analog VLSI chips that capture properties of biological neural computation.

关键词： motion detection motion analysis bioinspired artificial vision Reichardt Correlator

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Playing with maps Explore, discover, learn, categorize, model, analyse, explain, present geographic and non-geographic data

Playing with maps Explore, discover, learn, categorize, mode...

引用

International conference on Information visualisation (IV)

作者： M.-J. Kraak Department of Geo-Information Procesing I.T.C. Netherlands

Maps are especially known for their capability to provide insight in geographic patterns and trends. Maps do this well because they only present a selection of the complex reality and visualize it in an abstract way. But today they have many more roles to play. They should also be seen as flexible interface to geospatial data, since they offer interaction with the data behind the visual representation and additionally maps are instruments that encourage exploration. As such they are used to stimulate (visual) thinking about geospatial patterns, relationships, and trends. The context where maps like this operate is the world of geovisualization which can be described as a loosely bounded domain that addresses the visual exploration, analysis, synthesis and presentation of geospatial data by integrating approaches from disciplines including cartography with those from scientific visualization, image analysis, information visualization, exploratory data analysis, visual analytics, and GIScience. Contact with all those disciplines has enriched the world of maps but have also stimulated others to use the map (metaphor) to visualize non-geographic data. The discussion illustrated the new and exiting role maps can play to visualize geographic and non-geographic data in combination with other visual means

关键词： data visualization Instruments Image analysis Pattern analysis Information analysis data analysis visual analytics Europe Employment Graphics

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exploration of methods for estimation of number of endmembers in hyperspectral imagery

Exploration of methods for estimation of number of endmember...

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conference on Chemical and Biological Sensors for Industrial and Environmental Monitoring ii

作者： Wu, Chao-Cheng Liu, Weimin Chang, Chein-, I Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Remote Sensing Signa & Image Proc Lab Baltimore MD 21250 USA

ISBN: (纸本)9780819464767

An endmember is an idealized, pure signature for a class and provides crucial information for hyperspectral image analysis. Recently, endmember extraction has received considerable attention in hyperspectral imaging due to significantly improved spectral resolution where the likelihood of a hyperspectral image pixel uncovered by a hyperspectral image sensor as an endmember is substantially increased. Many algorithms have been proposed for this purpose. One great challenge in endmember extraction is the determination of number of endmembers, p required for an endmember extraction algorithm (EEA) to generate. Unfortunately, this issue has been overlooked and avoided by making an empirical assumption without justification. However, it has been shown that an appropriate selection of p is critical to success in extracting desired endmembers from image data. This paper explores methods available in the literature that can be used to estimate the value, p. These include the commonly used eigenvalue-based energy method, An Information criterion (AIC), Minimum Description Length (MDL), Gershgorin radii-based method, Signal Subspace Estimation (SSE) and Neyman-Pearson detection method in detection theory. In order to evaluate the effectiveness of these methods, two sets of experiments are conducted for performance analysis. The first set consists of synthetic image-based simulations which allow us to evaluate their performance with a priori knowledge, while the second set comprising of real hyperspectral image experiments which demonstrate utility of these methods in real applications.

关键词： Hyperspectral imaging Minerals Image analysis Interference (communication) Detection theory Signal to noise ratio Calcite Image sensors Neodymium Signal detection

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