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检索条件"任意字段=Conference on Visualization and Data Analysis 2011"

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Concurrency control techniques for a multimedia database system

Concurrency control techniques for a multimedia database sys...

引用

Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Cosmin Stoica Spahiu Faculty of Automation Computers and Electronics University of Craiova Craiova Dolj Romania

The paper presents the concurrency control methods used to provide simultaneous access to databases, in a multimedia relational database management system. This is an original system that integrates methods for extracting visual characteristics (color and texture characteristics) from images and for executing content-based visual queries. In order to accomplish this, it was defined an original new data type called IMAGE. This data type is used to store the images along with the characteristics extracted and other important information. The problems that should be handled refers to process multiple requests and access the same set of data in a concurrent environment. The databases must be protected with a synchronization algorithm to ensure that the information doesn't get corrupted when multiple clients' requests access concurrently the same set of data.

关键词： Servers Multimedia databases Concurrent computing Image color analysis visualization Multimedia communication

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One efficient compression method used on WebGIS

One efficient compression method used on WebGIS

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International conference on Geoinformatics

作者： Yanwei Zhao Zhenlin Cheng Hui Dong Jinyun Fang Chinese Academy of Sciences Beijing Beijing CN Institute of Computing Technology Chinese Academy and Sciences Beijing China

The features of mass spatial data and the limit of Internet bandwidth are key issues which restrict the WebGIS application performance. How to implement efficient vector data compression is important during the stage of data transmission. To get high compression ratio, we propose one multilevel vector data compression method which combine lossy compression and lossless compression technology. According to the resolution of the map, we ignore some vector coordinates based on visualization. Moreover, we apply coding technique to geographic coordinates to achieve higher compression ratio. After illustrating the design and implementation of this method, we conduct experiments to compare the performance of traditional compression technique and the proposed method. The result shows the significant compression ratio (about 90%) which enhance the data transmission efficiency to a large extent.

关键词： Encoding Geometry data compression Internet Algorithm design and analysis Geographic Information Systems Software

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Observation-level interaction with statistical models for visual analytics

Observation-level interaction with statistical models for vi...

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IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Alex Endert Chao Han Dipayan Maiti Leanna House Scotland Leman Chris North Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Statistics Virginia Polytechnic Institute and State University Blacksburg VA USA

In visual analytics, sensemaking is facilitated through interactive visual exploration of data. Throughout this dynamic process, users combine their domain knowledge with the dataset to create insight. Therefore, visual analytic tools exist that aid sensemaking by providing various interaction techniques that focus on allowing users to change the visual representation through adjusting parameters of the underlying statistical model. However, we postulate that the process of sensemaking is not focused on a series of parameter adjustments, but instead, a series of perceived connections and patterns within the data. Thus, how can models for visual analytic tools be designed, so that users can express their reasoning on observations (the data), instead of directly on the model or tunable parameters? Observation level (and thus “observation”) in this paper refers to the data points within a visualization. In this paper, we explore two possible observation-level interactions, namely exploratory and expressive, within the context of three statistical methods, Probabilistic Principal Component analysis (PPCA), Multidimensional Scaling (MDS), and Generative Topographic Mapping (GTM). We discuss the importance of these two types of observation level interactions, in terms of how they occur within the sensemaking process. Further, we present use cases for GTM, MDS, and PPCA, illustrating how observation level interaction can be incorporated into visual analytic tools.

关键词： data visualization data models Visual analytics Analytical models Principal component analysis Layout

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Scene Segmentation Assisted by Stereo Vision

Scene Segmentation Assisted by Stereo Vision

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International conference on 3D Imaging, Modeling, Processing, visualization and Transmission (3DIMPVT)

作者： Carlo Dal Mutto Pietro Zanuttigh Guido M. Cortelazzo Stefano Mattoccia Department of Information Engineering (DEI) University of Padova Padova Italy Department of Electronics Computer Science and Systems(DEIS) University of Bologna Bologna Italy

Stereo vision systems for 3D reconstruction have been deeply studied and are nowadays capable to provide a reasonably accurate estimate of the 3D geometry of a framed scene. They are commonly used to merely extract the 3D structure of the scene. However, a great variety of applications is not interested in the geometry itself, but rather in scene analysis operations, among which scene segmentation is a very important one. Classically, scene segmentation has been tackled by means of color information only, but it turns out to be a badly conditioned image processing operation which remains very challenging. This paper proposes a new framework for scene segmentation where color information is assisted by 3D geometry data, obtained by stereo vision techniques. This approach resembles in some way what happens inside our brain, where the two different views coming from the eyes are used to recognize the various object in the scene and by exploiting a pair of images instead of just one allows to greatly improve the segmentation quality and robustness. Clearly the performance of the approach is dependent on the specific stereo vision algorithm used in order to extract the geometry information. This paper investigates which stereo vision algorithms are best suited to this kind of analysis. Experimental results confirm the effectiveness of the proposed framework and allow to properly rank stereo vision systems on the basis of their performances when applied to the scene segmentation problem.

关键词： Image color analysis Geometry Clustering algorithms Stereo vision Three dimensional displays Image segmentation Algorithm design and analysis

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Visual Fire Detection Based on data Mining Technique

Visual Fire Detection Based on Data Mining Technique

引用

International conference on Robot, Vision and Signal Processing (RVSP)

作者： Yu-Chiang Li Wei-Cheng Wu Computer Science and Information Engineering Southern Taiwan University Tainan Taiwan

Fire protection is a very important issue in social security. An effective fire detection system, which can early detect fire and alarm warning, is necessary. Visual fire detection is useful in conditions, in which conventional fire detectors cannot be employed. This study proposes an effective fire detection method, which combines the statistical fire color model and the sequential pattern mining to detect the fire in an image. Experimental results show that the proposed methods can effectively detect fire. The detection accuracy of the proposed hybrid method is better than the Celik's method for images.

关键词： Fires Image color analysis data mining visualization Quantization Real time systems Sensors

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Emergent: A knowledge discovery tool for understanding emerging industry structure

Emergent: A knowledge discovery tool for understanding emerg...

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conference on Human System Interactions, HSI

作者： Erik Noyes Leonidas Deligiannidis Babson College Wellesley MA USA Wentworth Institute of Technology Boston MA USA

This paper presents a visual analytics tool to understand the emergence and structure of the nanotechnology industry. According to the U.S. National Science Foundation (NSF), the global nanotechnology industry is expected to grow to $1 trillion in 2010 and drive dramatic innovation and wealth creation in industries as diverse as energy, computing and biotechnology. Nanotech entrepreneurs, analysts and investors alike need tools to understand the emerging structure of the industry because firm competitive positions in the industry impact ventures' survival, growth and profitability. Particularly, nanotech ventures compete from different initial “strategic footprints” in the industry which ease or complicate entry into new growth businesses. In fact, the emergence of the nanotechnology industry is the story of interweaving with-and penetration into-different adjoining industries. Exploiting the world's largest database on consumer-focused nanotechnology products, this paper demonstrates a visual analytics tool, Emergent, that can show the emerging structure of the industry and ventures' varying strategic footprints within this forming multi-industry terrain. The tool is interactive, scalable, and adaptable to relational data from other industries. Business applications of Emergent include industry analysis, strategic planning and entrepreneurial opportunity identification.

关键词： Industries Nanotechnology Commercialization Business visualization Automotive engineering data visualization

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Predicting Researchers' Future Activities Using visualization System for Co-authorship Networks

Predicting Researchers' Future Activities Using Visualizatio...

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IEEE WIC ACM International conference on Web Intelligence (WI)

作者： Takeshi Kurosawa Yasufumi Takama Graduate School of System Design Tokyo Metropolitan University Hino Tokyo Japan

This paper proposes a visualization system for getting insight into future research activities from co-authorship networks. A bibliographic network such as a co-authorship network and a citation network is important information for researchers when doing a research survey. In particular, there are many requests on research survey that relate with researchers' future activities, such as identification of remarkable of researchers including growing researchers and supervisors. Although a citation network has received many attentions from researchers, it is not suitable for such surveys because it reflects researchers' past activities. Since collaboration of researchers is essential for researchers' activities, co-authorship network is suitable for predicting future activities. In order to get insights into future research activities by discriminating growing research areas from grown-up areas, the proposed visualization system provides the function for identifying research areas and that for identifying time variation of both network structure and keyword distribution. As a basis for getting insights into future research activities, this paper focuses on the task of discriminating growing researchers from supervisors. The effectiveness of the proposed system is evaluated through the detailed analysis of two participants' analyzing process of InfoVis 2004 Contest dataset.

关键词： Collaboration visualization Color Educational institutions data visualization System analysis and design Brightness

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Protection security assessment using automated analysis

Protection security assessment using automated analysis

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IEEE PES Innovative Smart Grid Technologies conference Europe (ISGT Europe)

作者： Johann Jäger Thomas Bopp FAU University of Erlangen Germany Siemens AG Germany

Summary form only given. Protection security assessment of power grids becomes an important task in the course of a competitive energy business and distributed power generation based on renewable resources. The analysis of past blackouts studied by the North American Electric Reliability Council (NERC) shows that protection relays are involved in about 75% of all major disturbances. One reason for that is the non adequate adaption of the protection systems to the changing network conditions. In particular the relay hidden failures causes relay malfunctions and unintended supply interruptions in the past.

关键词： Security Relays data visualization Business Distributed power generation Reliability Numerical models

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A Novel Approach Based on Gestalt Psychology for Abstracting the Content of Large Execution Traces for Program Comprehension

A Novel Approach Based on Gestalt Psychology for Abstracting...

引用

IEEE International conference on Engineering of Complex Computer Systems

作者： Heidar Pirzadeh Abdelwahab Hamou-Lhadj Software Behaviour Analysis Lab Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

The analysis of execution traces can reveal important information about the behavioral aspects of complex software systems, hence reducing the time and effort it takes to understand and maintain them. Traces, however, tend to be considerably large which hinders their effective analysis. Existing traces analysis tools rely on some sort of visualization techniques to help software engineers make sense of trace content. Many of these techniques have been studied and found to be limited in many ways. In this paper, we present a novel trace analysis technique that automatically divides the content of a large trace into meaningful segments that correspond to the program's main execution phases such as initializing variables, performing a specific computation, etc. These phases can simplify significantly the exploration of large traces by allowing software engineers to first understand the content of a trace at a high-level before they decide to dig into the details. Our phase detection method is inspired by Gestalt laws that characterize the proximity, similarity, and continuity of the elements of a data space. We model these concepts in the context of execution traces and show how they can be used as gravitational forces that yield the formation of dense groups of trace elements, which indicate candidate phases. We applied our approach to two software systems. The results are very promising.

关键词： Gravity Phase detection Software Complexity theory visualization Context Psychology

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Accessing relevant images: Fuzzy K-Means

Accessing relevant images: Fuzzy K-Means

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International conference on Electronic Computer Technology

作者： Priya Premkumar J. Anitha Computer Science and Engineering Karunya University Coimbatore India

This paper uses Fuzzy K-Means clustering algorithm to access images from a collection of images. When using this algorithm one image can appear in more than one clusters unlike K-Means which is hard based grouping. The user can access images from an image search engine, picture library, trained data sets, etc. The images being accessed may have no association with what the user is actually looking for. Hence there is a necessity of providing the user more accurate collection of images which can be done through fuzzy K Means clustering.

关键词： Clustering algorithms visualization Partitioning algorithms Google Algorithm design and analysis Image color analysis Image retrieval

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