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2006 10th International conference on Computer Supported Cooperative Work in Design, CSCWD 2006

作者： Xiufang, Sun Wenfa, Zhan School of Foreign Language Anqing Normal College China Educational Technology Department Anqing Normal College China

ISBN: (纸本)1424401658

Web-based instruction is a new learning medium that offers many advantages in educational settings, The main advantage is reflected in its non-linear interaction. Students can control the pace and sequence of instruction and make personally meaningful choices which in theory should assist in developing their cognitive structure. However, in practice some learners may have difficulties in making the learning paths by themselves. Some influencing factors of learning interaction in web-based instruction are discussed according to individual differences. data were collected from some classes in Anqing Normal College of Anhui Province. A. total 350 available responses were analyzed. We identified three results from this study: (1) learners show positive attitudes towards L-L web-based interaction learning. And the form of network application which they like best and use most frequently is finishing homework through group cooperation. (2) During the process of finishing homework learners actively seek for and sort out materials, to which comparatively deep analysis is made. And L-I web-based interaction learning are also comparatively active. (3) The spontaneous learning ability and knowledge techniques of the learners have striking predication to successful web-based learning, and the predication effect of the visual style, hearing style and acting style are not striking. © 2006 IEEE.

关键词： Learning systems

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xAnVi - An Extensible visualization and analysis Framework

xAnVi - An Extensible Visualization and Analysis Framework

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International conference on Information visualisation (IV)

作者： J. Griebsch O. Arafat W. Koska Technical University Munich Garching Germany

xAnVi is an extensible framework for the analysis and visualization of graphs. The framework consists of a small core to manage resources, plugins and extension points and an arbitrarily expandable set of plugins to provide the actual application functionality. This paper describes the design approach to create a modular bioinformatics toolkit/framework for: research involving the dynamic and interactive visualization of graphs and networks; and biological networks analyses. In addition, two plugins for the interactive exploration of hierarchical networks are presented. The toolkit is available through the toolkit homepage (http://***/personen/griebsch/xanvi)

关键词： data visualization Algorithm design and analysis Proteins Biological information theory IP networks Graphical user interfaces Resource management Bioinformatics visual databases data mining

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ViEWNet: visual exploration of Region-Wide Traffic Networks

ViEWNet: Visual Exploration of Region-Wide Traffic Networks

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International conference on data Engineering

作者： H.-P. Kriegel P. Kunath M. Pfeifle M. Renz University of Munich (LMU) Germany

Location-based services and data mining algorithms analyzing objects moving on a complex traffic network are becoming increasingly important. In this paper, we introduce a new approach which effectively and efficiently detects dense areas in spatial networks. In an offline phase, we generate a hierarchical partitioning of the traffic network. Thereby, static entities like roads and buildings are likely to be in the same partitioning if they are close to each other according to their network distance. In the online phase, our prototype ViEWNet allows the effective and efficient monitoring of objects moving on a spatial network. Based on a clear visualization of the traffic intensity in each network cell, the user can easily detect hierarchies of dense areas by our powerful prototype ViEWNet.

关键词： Telecommunication traffic Prototypes visualization Network servers data mining Partitioning algorithms data analysis Algorithm design and analysis Roads Monitoring

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A Multiple-Perspective, Interactive Approach for Web Information Extraction and exploration

A Multiple-Perspective, Interactive Approach for Web Informa...

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International conference on data Engineering Workshops

作者： Naureen Moon Ya-Wen Hsu R. Singh Department of Computer Science San Francisco State University San Francisco CA USA

While increasing amounts of complex information are becoming available on the web, there is, beyond keywordbased search and listing of results, a paucity of user interface paradigms and implementations that support interaction, exploration, and assimilation of information. This paper describes our design of a novel framework to address this deficiency. The proposed framework supports both direct search behavior as well as more exploratory search strategies through multiple-perspective visualization and interaction with search results. The approach is developed around the twin themes of supporting data context and facilitating effective interactions between users and data. The system supports data context through determination of semantic correlations between web pages and extraction of the spatio-temporal data contained therein. A multipleperspective environment is then used to display semantic and spatio-temporal relationships as well as to provide intuitive views of the data, specifically through web page thumbnail, map, and timeline modules. The environment supports direct interactions with the data through a reflective interface by which user selections in any one panel highlight the corresponding information in other panels. In this environment, visual cues and explicit facilities to model space and time aid in recognition, querying, and exploration of information as well as in representation and reasoning with complex relationships (such as spatio-temporal, causal, evolutionary) in the data. Experimental studies of a quantitative and qualitative nature demonstrate the efficacy of the system in facilitating both information extraction and discovery.

关键词： data mining Web pages Moon User interfaces Pattern analysis Navigation Computer science data visualization Displays Indexing

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visualizing Concept Associations Using Concept Density Maps

Visualizing Concept Associations Using Concept Density Maps

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International conference on Information visualisation (IV)

作者： N.J. van Eck F. Frasincar J. van den Berg Faculty of Economics Erasmus University Rotterdam Rotterdam Netherlands

The concept mapping algorithm proposed in an earlier paper is one of the dimensionality reduction techniques that can be used for knowledge domain visualization. Using this algorithm to visualize large knowledge domains may not always provide a good overview of the domain due to visual cluttering of concepts. In this paper, we propose to apply kernel density estimation to the visualization of concept maps in order to be able to better explore large knowledge domains. Kernel density estimation proves to be useful for the identification of concept clusters at different levels of detail. In addition to the visual exploration of large knowledge domains, we are also able to visually verify the hypothesis that the concept mapping algorithm places related concepts close to each other. The flexibility and effectiveness of our approach is validated by applying the proposed technique to different visualization scenarios for the field of computational intelligence

关键词： data mining data visualization Frequency Kernel Information analysis Clustering algorithms Computational intelligence Humans

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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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International conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Xinwei Xue Thomas C. Henderson School of Computing University of Utah Salt Lake UT USA Faculty of School of Computing University of Utah Salt Lake UT USA

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

关键词： Video recording Feature extraction Motion analysis data visualization data analysis Covariance matrix Eigenvalues and eigenfunctions Animal behavior Image segmentation Intelligent systems

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Text Map Explorer: a Tool to Create and Explore Document Maps

Text Map Explorer: a Tool to Create and Explore Document Map...

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Information visualization 2006 (IV 2006)

作者： Fernando Vieira Paulovich Rosane Minghim Institute of Mathematics and Computer Science University of São Paulo Sao Paulo Brazil

This paper presents a tool, called Text Map Explorer, which can be used to create and explore document maps (visual representations of document collections). This tool is capable of grouping (and separating) documents by their contents, revealing to the user relationships amongst them. This paper also presents a novel multi-dimensional projection technique for text that reduces the quadratic time complexity of our previous approach to O(N{sup}(2/3)), keeping the same quality of maps. The technique creates a surface that reveals intrinsic patterns and support various kinds of exploration of a text collection.

关键词： Principal component analysis Mathematics Computer science Search engines data visualization Indexing Force measurement Self organizing feature maps Document handling Java

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The Tyzx DeepSea G2 Vision System, ATaskable, Embedded Stereo Camera

The Tyzx DeepSea G2 Vision System, ATaskable, Embedded Stere...

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IEEE Computer Society conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： J.I. Woodfill G. Gordon D. Jurasek T. Brown R. Buck Tyzx Inc. Menlo Park CA USA

Our goal is to build vision systems suitable for deployment in devices that operate in demanding dynamic, variably lit, real-world environments. For such systems to be successful, not only must they perform their visual analysis well and robustly, but they must also be small, cheap and consume little power. Further, since volume deployments of such vision systems are still nascent, the systems must be taskable -- flexible enough to support many different uses. We have met our goal with the Tyzx DeepSea G2 Stereo Vision System, an embedded stereo camera consisting of two CMOS imagers, a DeepSea ii stereo ASIC, an FPGA, a DSP/Co-processor and a PowerPC running Linux, connected to the Ethernet. It is made practically taskable by the definition of a set of configurable visual primitives supported by specific hardware acceleration. These primitives include stereo correlation, color and depth background modeling, and 2D and 3D quantized representations or projections of the range data. We have defined a common programming interface in which the visual primitives are available both in traditional workstation environments, supported in software, and on the G2 with hardware acceleration. Single G2s are deployed in mobile platforms such as robots and automobiles, while networks of G2s are deployed in tracking systems in public and private sites around the world.

关键词： Machine vision Cameras Hardware Acceleration Vehicle dynamics Performance analysis Robustness Stereo vision CMOS image sensors Application specific integrated circuits

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Motion Estimation to a Failed Satellite on Orbit using Stereo Vision and 3D Model Matching

Motion Estimation to a Failed Satellite on Orbit using Stere...

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International conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Fuyuto Terui Heihachiro Kamimura Shin' ichiro Nishida Japan Aerospace Exploration Agency Tokyo Japan

An algorithm is developed for estimating the motion (relative attitude and relative position) of large pieces of space debris, such as failed satellites. The algorithm is designed to be used by a debris removal system which would perform various operations on space debris such as observation, investigation, capture, repair, refuel and de-orbit. During these operations, the debris removal system must control its position and attitude simultaneously. Such six degree-of-freedom control becomes more difficult if the failed satellite is changing attitude, such as by nutation. The information required as feedback signals for such a controller is relative - position, velocity, attitude and angular velocity - and these are expected to be measured or estimated from image data. The algorithm uses a combination of stereo vision and 3D model matching, applying the ICP (iterative closest point) algorithm, and uses time series of images to increase the reliability of the relative attitude and position estimates. To evaluate the algorithm, a visual simulator is prepared to simulate the on-orbit optical environment in terrestrial experiments, and the motion of a miniature satellite model is estimated using images obtained from the simulator

关键词： Motion estimation Satellites Stereo vision Attitude control Iterative algorithms Space debris Algorithm design and analysis Control systems Feedback Angular velocity control

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Multi-scale data visualization for computational astrophysics and climate dynamics at Oak Ridge National Laboratory

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Journal of Physics: conference Series 2006年第1期46卷

作者： Sean Ahern Jamison R Daniel Jinzhu Gao George Ostrouchov Ross J Toedte Chaoli Wang Center for Computational Sciences Oak Ridge National Laboratory USA Department of Computer Science and Engineering Ohio State University USA

Computational astrophysics and climate dynamics are two principal application foci at the Center for Computational Sciences (CCS) at Oak Ridge National Laboratory (ORNL). We identify a dataset frontier that is shared by several SciDAC computational science domains and present an exploration of traditional production visualization techniques enhanced with new enabling research technologies such as advanced parallel occlusion culling and high resolution small multiples statistical analysis. In collaboration with our research partners, these techniques will allow the visual exploration of a new generation of peta-scale datasets that cross this data frontier along all axes.

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