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

共 1224 条记录，以下是81-90 订阅

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Positioning of the Research-Doctorate Programs in the American Higher Education Market: Universities Offering Electrical and Compuer Engineering Programs at the West Region

Positioning of the Research-Doctorate Programs in the Americ...

引用

IIAI International conference on Advanced Applied Informatics (IIAIAAI)

作者： Soichiro Aihara Shibaura Institute of Technology Center for Promotion of Educational Innovation Saitama Japan

ISBN: (纸本)9781467389860

The purpose of this study is to visualize positioning of the research-doctoral programs in the American three-dimensional higher education market structure. This study is a secondary analysis of data by the National Research Council, A data-Based Assessment of Research-Doctorate Programs in the United States (2011). This database assess doctoral programs with three-dimensional indicators, those are Research Activity, Student Support & Outcomes, and Diversity. This means that we can postulate research-doctoral programs in the America have positioning in search of niche in the three-dimensional higher education market structure. IR officers develop their management plan for positioning in this market structure. Prospective doctoral student make an attendance choice with the positioning of programs in this market structure. In this study, the positioning visualize to the 27 universities which offer the Electronical and Computer Engineering programs that is one of a subfield of Engineering at the West region. As the threshold of 80-position of the research activities, it is possible to divide the universities into two groups: Group 1 and Group2. Group1 is research-oriented universities. There is correlation between research productivity and education productivity. Group2 is education-oriented universities. There are many state universities and there are no correlation between research productivity and education productivity. As to Diversity, there are universities at both Groups. It seems to, however, universities that diversity is at upper rank are also Student Support & Outcomes is at upper rank.

关键词： Education Productivity Medical services Computers Correlation Presses data visualization

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Building MD Analytical Stars Using a Visual Linked data Query Builder 6th

引用

6th International Joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K)

作者： Nebot, Victoria Berlanga, Rafael Univ Jaume 1 Comp Languages & Syst Campus Riu Sec S-N Castellon de La Plana 12071 Spain

ISBN: (纸本)9783319258409;9783319258393

In this paper we present the foundations and a prototype tool for Linked data (ld) analysis and visualization. The goal is to provide users with a tool enabling them to easily analyze Linked data without knowledge of the SPARQL query language. The success of the multidimensional (md) model for data analysis has been mainly due to its simplicity. The md model views data in terms of dimensions and measures. Therefore, we propose the notion of md analytical stars as the foundation to query ld. These stars are md conceptual patterns that summarize ld (i.e., dimensions and measures). We have developed a tool that enables the user to graphically build md analytical stars as queries by suggesting possible dimensions and measures from a ld set. The query is automatically translated to SPARQL and executed. visualization of results as charts, tables, etc. is performed using web-based technologies. We show the prototype tool and a running example.

关键词： Linked data RDF Multidimensional models Linked data querying

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Enabling SDMX-based Retrieval and Spatio-statistical analysis of National Census and Related datasets 11

Enabling SDMX-based Retrieval and Spatio-statistical Analysi...

引用

IEEE International conference On eScience

作者： Hunter, Jane Azeezullah, Imran Ward, Nigel Barker, Ross Shyy, Tung-Kai Beer, Chris Girvan, Stuart Nairn, Alister Branson, Merry Stimson, Robert Dentrinos, James Galang, Gerson Wallace, Stewart Pettit, Chris Univ Queensland Sch ITEE Brisbane Qld Australia Australian Bur Stat Canberra ACT Australia Univ Melbourne Australian Urban Res Infrastruct Network Melbourne Vic Australia

ISBN: (纸本)9781467393256

This paper describes a collaborative project between the Australian Urban Research Infrastructure Network (AURIN), the Australian Bureau of Statistics (ABS), the University of Queensland eResearch Lab and a number of social science research centres across Australia - that provides programmatic access to ABS Census data sets to enable its reuse within a range of research projects. The project successfully demonstrates machine-to-machine access to 2011 Census data through a federated data hub model that dynamically delivers statistical datasets to the research community. Using an SDMX web services approach, combined with advanced data analytics and visualization services available through the AURIN workbench, social scientists are able to manipulate and visualize national census data overlaid with other related data sets through a sophisticated mapping interface. Integrated statistical analysis services (R-based) also enable social scientists to quantify correlations between different demographic and socio-economic parameters. A number of socio-economic use-cases are presented that illustrate how the system enables researchers to understand and quantify changes in industry sectors, labor force needs, employment, population needs and disadvantage, over space and time. The paper also outlines problems and limitations revealed through the demonstrator projects, lessons learnt and areas that will require further effort to deliver optimum access to national census data sets and associated e-social science infrastructure for both the Australian and global social science community.

关键词： e-social science spatio-statistical analytics SDMX census data socio-economics demographics

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Mobile service for open data visualization on geo-based images

Mobile service for open data visualization on geo-based imag...

引用

International conference on Intelligent Earth Observing and Applications (IEOAs)

作者： Lee, Kiwon Kim, Kwangseob Kang, Sanggoo Hansung Univ Dept Informat Syst Engn Samseon Dong 2 Ga Seoul 02876 South Korea

ISBN: (纸本)9781510600492

Since the early 2010s, governments in most countries have adopted and promoted open data policy and open data platform. Korea are in the same situation, and government and public organizations have operated the public-accessible open data portal systems since 2011. The number of open data and data type have been increasing every year. These trends are more expandable or extensible on mobile environments. The purpose of this study is to design and implement a mobile application service to visualize various typed or formatted public open data with geo-based images on the mobile web. Open data cover downloadable data sets or open-accessible data application programming interface API. Geo-based images mean multi-sensor satellite imageries which are referred in geo-coordinates and matched with digital map sets. System components for mobile service are fully based on open sources and open development environments without any commercialized tools: PostgreSQL for database management system, OTB for remote sensing image processing, GDAL for data conversion, GeoServer for application server, OpenLayers for mobile web mapping, R for data analysis and D3. js for web-based data graphic processing. Mobile application in client side was implemented by using HTML5 for cross browser and cross platform. The result shows many advantageous points such as linking open data and geo-based data, integrating open data and open source, and demonstrating mobile applications with open data. It is expected that this approach is cost effective and process efficient implementation strategy for intelligent earth observing data.

关键词： open data visualization open source mobile web mapping

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A vessel segmentation method for MRA data based on probabilistic mixture model

A vessel segmentation method for MRA data based on probabili...

引用

2015 IET International conference on Biomedical Image and Signal Processing, ICBISP 2015

作者： Lu, Pei Wang, Cheng Zhou, Shoujun Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781785610448

Accurate segmentation and visualization of cerebral vessels have important significance to the diagnosis and treatment of relevant brain diseases. However, some segmentation algorithms are only competent for the standard data. In this paper, a segmentation method based on probabilistic mixture model is proposed to solve clinical problems. Through histogram analysis of the magnetic resonance angiography (MRA) data offered by Guangzhou General Hospital of the Chinese PLA, a mixture model formed by six probabilistic distributions (one Exponential, one Rayleigh, and four Normal distributions) was built to fit the histogram curve. Least squares and expectation maximization (EM) algorithms have been used for parameters estimation. At last, the segmentation was enhanced by maximum a posteriori probability (MAP) and Markov random field (MRF) algorithm. The effectiveness of the proposed method has been validated by segmentation tests on a series of clinical MRA data with good performance.

关键词： Normal distribution

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Enabling SDMX-based Retrieval and Spatio-statistical analysis of National Census and Related datasets

Enabling SDMX-based Retrieval and Spatio-statistical Analysi...

引用

IEEE International conference on e-Science and Grid Computing

作者： Jane Hunter Imran Azeezullah Nigel Ward Ross Barker Tung-Kai Shyy Chris Beer Stuart Girvan Alister Nairn Merry Branson Robert Stimson James Dentrinos Gerson Galang Stewart Wallace Chris Pettit School of ITEE The University of Queensland Brisbane The Australian Bureau of Statistics Canberra Australia Australian Urban Research Infrastructure Network University of Melbourne Melbourne Australia

This paper describes a collaborative project between the Australian Urban Research Infrastructure Network (AURIN), the Australian Bureau of Statistics (ABS), the University of Queensland eResearch Lab and a number of social science research centres across Australia - that provides programmatic access to ABS Census data sets to enable its re-use within a range of research projects. The project successfully demonstrates machine-to-machine access to 2011 Census data through a federated data hub model that dynamically delivers statistical datasets to the research community. Using an SDMX web services approach, combined with advanced data analytics and visualization services available through the AURIN workbench, social scientists are able to manipulate and visualize national census data overlaid with other related data sets through a sophisticated mapping interface. Integrated statistical analysis services (R-based) also enable social scientists to quantify correlations between different demographic and socio-economic parameters. A number of socio-economic use-cases are presented that illustrate how the system enables researchers to understand and quantify changes in industry sectors, labor force needs, employment, population needs and disadvantage, over space and time. The paper also outlines problems and limitations revealed through the demonstrator projects, lessons learnt and areas that will require further effort to deliver optimum access to national census data sets and associated e-social science infrastructure for both the Australian and global social science community.

关键词： Australia data visualization Employment Web services Metadata Portals Industries

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Research of Large-Scale and Complex Agricultural data Classification Algorithms Based on the Spatial Variability

Research of Large-Scale and Complex Agricultural Data Classi...

引用

The 9th International conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Hang Chen Guifen Chen Lixia Cai Yuqin Yang College of Information Technology Jilin Agricultural University Institute of Scientific and Technical Information of Jilin

ISBN: (纸本)9783319483566

In the actual classification problems, as a result of lack of clear boundary information between classification objects, that could lead to loss of classification accuracy easily. Therefore, this article from the spatial patterns of the sample properties to proceed, fuzzy clustering algorithm is proposed based on the sensitivity of attribute weights, through using the attribute weights to improve the classification capability between confusing samples, that is for researching and analysing soil nutrient spatial data with consecutive years to collect in Nongan town. Then through the analysis of the visualization technology to realize the visualization of the algorithm. Experimental results show that introducing weights portray attribute information could reduce the objective function value, and effectively alleviate the phenomenon of boundary data that cannot distinguish. Ultimately to improve the classification accuracy. Meanwhile, use of MATLAB to form visualization of three-dimensional image. The results provide a basis for to improve the accuracy of data classification and clustering analysis of large and complex agricultural data.

关键词： Large-scale and complex data Spatial variation law Fuzzy clustering Soil nutrients Sensitive attribute weights soil nutrients agricultural statistics visualization Sorting algorithm data classification large sizes MATLAB

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Research of Terrain 3D visualization Method based on IDL and ArcEngine

Research of Terrain 3D Visualization Method based on IDL and...

引用

International conference on Information Science and Cloud Computing Companion (ISCC-C)

作者： Yang, Bin Gu, Xiumei Zhan, Jinfeng Li, MaoJiao Minist Educ East China Inst Technol Engn Res Ctr Nucl Technol Applicat Nanchang 330000 Jiangxi Peoples R China Southwest Univ Sci & Technol Coll Environm & Resource Mianyang 621000 Peoples R China

ISBN: (纸本)9781479952458

It is a very hot research topic in GIS, virtual reality, computer graphics, digital photogrammetry and other fields which should be researched on 3D terrain visualization. There is also an important part of the digital earth strategy in many fields in order to resolve some comprehensive problems. Trying to take advantage of IDL data processing and graphic display function and ArcEngine spatial analysis function, in the Visual C # 2005 under the environment of hybrid programming mechanism, using of component design and development of integrated development technologies analysis of terrain visualization application operating environment. It should realize the 3D digital terrain expression and spatial analysis function. The results show that the IDL and ArcEngine integrated development method applied to the 3D terrain visualization analysis software platform developed operability and extension force with strong, both in terms of space efficiency and image data analysis, development costs advantages.

关键词： 3D visualization formatting Digital terrain IDL ArcEngine Integrated development

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Learning to rank in person re-identification with metric ensembles

Learning to rank in person re-identification with metric ens...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Sakrapee Paisitkriangkrai Chunhua Shen Anton van den Hengel The University of Adelaide Australian Centre for Robotic Vision Australia

ISBN: (纸本)9781467369657

We propose an effective structured learning based approach to the problem of person re-identification which outperforms the current state-of-the-art on most benchmark data sets evaluated. Our framework is built on the basis of multiple low-level hand-crafted and high-level visual features. We then formulate two optimization algorithms, which directly optimize evaluation measures commonly used in person re-identification, also known as the Cumulative Matching Characteristic (CMC) curve. Our new approach is practical to many real-world surveillance applications as the re-identification performance can be concentrated in the range of most practical importance. The combination of these factors leads to a person re-identification system which outperforms most existing algorithms. More importantly, we advance state-of-the-art results on person re-identification by improving the rank-1 recognition rates from 40% to 50% on the iLIDS benchmark, 16% to 18% on the PRID2011 benchmark, 43% to 46% on the VIPeR benchmark, 34% to 53% on the CUHK01 benchmark and 21% to 62% on the CUHK03 benchmark.

关键词： Measurement Cameras Image color analysis visualization Benchmark testing Training Histograms

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Big data analysis with interactive visualization using R packages 14

Big data analysis with interactive visualization using R pac...

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3rd ASE International conference on Big data Science and Computing, BIGdataSCIENCE 2014

作者： Cho, Wonhee Varma, Mohan Krishna Lim, Yoojin Lee, Moonsoo Lee, Hwangro Choi, Eunmi Graduate School of Business IT Kookmin University Seoul Korea Republic of Dept. of Financial Information Security Graduate School Kookmin University Seoul Korea Republic of

ISBN: (纸本)9781450328913

Compared to the traditional data storing, processing, analyzing and visualization which have been performed, Big data requires evolutionary technologies of massive data processing on distributed and parallel systems, such as Hadoop system. Big data analytic systems, thus, have been popular to derive important decision making in various areas. However, visualization on analytic system faces various limitation due to the huge amount of data. This brings the necessity of interactive visualization techniques beyond the traditional static visualization. R has been used and improved for a big data analysis and mining tool. Also, R is supported with various and abundant packages for different targets with visualization. However interactive visualization packages are not easily found in the market. This paper compares and analyzes interactive web packages with visualization packages for R. This paper also proposes interactive web visualized analysis environment for big data with a combination of interactive web packages and visualization packages. In particular, Big data analysis techniques with sensed data are presented as the result by reflecting the decision view on sensing field. © Copyright 2014 ACM.

关键词： visualization

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