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Computer and Computing Technologies in Agriculture V——5th IFIP TC 5/SIG 5.1 conference(CCTA2011) Part ii

作者： Feng Tan Xiaodan Ma Chun Wang Tingyi Shang College of Information Technology Heilongjiang Bayi Agricultural University College of Engineering Heilongjiang Bayi Agricultural University

ISBN: (纸本)9783642272776

In order to overcome the low diagnostic accuracy of traditional blast visual defects,set cold rice blast for example,four data groups has been acquainted through near infrared spectroscopy,the first group is healthy and diseased planting stock;the second group is three diseased levels of leaf blast;the third group is five diseased levels of grain blast;the forth group is four diseased levels of panicle blast,according to the analysis,we can know that different circumstances of plants had their own near-infrared spectral bands which made the preliminary basis for real-time detection of cold Rice blast.

关键词： Cold Rice Blast Near Infrared Spectroscopy Disease Detection

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Implementation on Remote Monitoring System of Oil Well

Implementation on Remote Monitoring System of Oil Well

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2011 International conference on Innovative Computing and Cloud Computing(ICCC 2011)

作者： BaoRong Zhong Hong Du Dept.of Computer Science Yangtze University Dept.of Elec Info Yangtze University

With the quick development of information and network technology, and wide use of Internet, building the information publish center in Web becomes the common demand from a great number of enterprises and customers. The production and management of modern enterprises rely heavily on the enterprise information integrated platform. The mass, important, sensitive data are gathered and stored. Making full use of these data becomes an extremely important link of the enterprise *** and technicians in oil field exploration and development have an excellent attention to the production information and working status of oil-pumping machine from oil well. The field information is an important basis of the productivity evaluation of single well, dynamic analysis of reservoir engineering in region, and production plan. Mud logging information will be recorded and transferred to research and management department timely, accurately, which directly related to progress and benefit of gas and oil production. Therefore, how to use the oil well information service system to provide reliable, timely information for the superior departments has been a priority of the agenda. data visualization on the web becomes a new focus. By studying and analyzing the oilfield data collection and visualization, the oil well information service system narrated in this paper established a relative perfect including the function of oil well data collection, transmission, and browsing online, etc. Flex provides rich components for the client development in data visualization, and the business logic layer developed by J2 EE technology, which is also a good choice. The paper designs an architecture which use Flex as the present layer development tools, Spring taking charge of developing the business logic layer and Hibernate realizing the data persistence layer. It has been found that this web application based on Flex and J2 EE technologies not only can provide an excellent visual picture

关键词： Oil Well Monitoring data Transmission Web Graph Publication Technical Framework

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Matching visual Saliency to Confidence in Plots of Uncertain data

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2010年第6期16卷 980-989页

作者： Feng, David Kwock, Lester Lee, Yueh Taylor, Russell M., ii Univ N Carolina Chapel Hill NC 27515 USA UNC Hosp Dept Radiol Chapel Hill NC USA

Conveying data uncertainty in visualizations is crucial for preventing viewers from drawing conclusions based on untrustworthy data points. This paper proposes a methodology for efficiently generating density plots of uncertain multivariate data sets that draws viewers to preattentively identify values of high certainty while not calling attention to uncertain values. We demonstrate how to augment scatter plots and parallel coordinates plots to incorporate statistically modeled uncertainty and show how to integrate them with existing multivariate analysis techniques, including outlier detection and interactive brushing. Computing high quality density plots can be expensive for large data sets, so we also describe a probabilistic plotting technique that summarizes the data without requiring explicit density plot computation. These techniques have been useful for identifying brain tumors in multivariate magnetic resonance spectroscopy data and we describe how to extend them to visualize ensemble data sets.

关键词： Uncertainty visualization brushing scatter plots parallel coordinates multivariate data

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Interactive visualization of Hyperspectral Images of Historical Documents

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2010年第6期16卷 1441-1448页

作者： Kim, Seon Joo Zhuo, Shaojie Deng, Fanbo Fu, Chi-Wing Brown, Michael S. Natl Univ Singapore Singapore Singapore Nanyang Technol Univ Singapore 639798 Singapore

This paper presents an interactive visualization tool to study and analyze hyperspectral images (HSI) of historical documents. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for old and fragile documents. The NAN is actively capturing HSI of historical documents for use in a variety of tasks related to the analysis and management of archival collections, from ink and paper analysis to monitoring the effects of environmental aging. To assist their work, we have developed a comprehensive visualization tool that offers an assortment of visualization and analysis methods, including interactive spectral selection, spectral similarity analysis, time-varying data analysis and visualization, and selective spectral band fusion. This paper describes our visualization software and how it is used to facilitate the tasks needed by our collaborators. Evaluation feedback from our collaborators on how this tool benefits their work is included.

关键词： Hyperspectral visualization data exploration image fusion document processing and analysis

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visual SPEAKER MODEL exploration

VISUAL SPEAKER MODEL EXPLORATION

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International conference on Multimedia and Expo

作者： Beecks, Christian Stadelmann, Thilo Freisleben, Bernd Seidl, Thomas Rhein Westfal TH Aachen Data Management & Data Explorat Grp Aachen Germany Univ Marburg Dept Math & Comp Sci Marburg Germany

ISBN: (纸本)9781424474936

We present an interactive visualization system for the analysis of Gaussian mixture speaker models. The system exhibits the inner workings of the model intuitively by visualizing graphical representations of its parameters and of the underlying acoustical data at the same time. This enables the exploration of new modeling possibilities in the context of speaker clustering tasks.

关键词： speaker model analysis Gaussian mixture model Signature Quadratic Form distance visualization

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Vide: an editor for the visual exploration of raw data

Vide: an editor for the visual exploration of raw data

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conference on visualization and data analysis 2010

作者： Woerner, M. Reina, G. Grottel, S. Ertl, T. Univ Stuttgart Inst Visualizat & Interact Syst D-7000 Stuttgart Germany

ISBN: (纸本)9780819479235

The analysis of binary data remains a challenge, especially for large or potentially inconsistent files. Traditionally, hex editors only make limited use of semantic information available to the user. We present an editor that supports user-supplied semantic data definitions. This semantic information is used throughout the program to realize semantic data visualization and data exploration capabilities not present in similar systems. visualization and human-computer interaction techniques are applied. We show that this makes recognizing the structure of unknown or inconsistent data much more effective. Our approach demonstrates concepts that can be applied to the visual analysis of raw data in general.

关键词： Hex editor semantic lenses raw data diagnostics error recovery

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Interactive Vector Field Feature Identification

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2010年第6期16卷 1560-1568页

作者： Daniels, Joel, ii Anderson, Erik W. Nonato, Luis Gustavo Silva, Claudio T. Univ Utah Sch Comp Salt Lake City UT 84112 USA Univ Utah Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Univ Sao Paulo Inst Ciencias Matemat & Computacao BR-05508 Sao Paulo Brazil

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

关键词： Vector field data clustering feature classification high-dimensional data user interaction

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Adjustment of weak partial extraction data assuming metal ion adsorption: examples using bulk cyanide leach

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GEOCHEMISTRY-exploration ENVIRONMENT analysis 2010年第2期10卷 199-206页

作者： Rate, Andrew W. Hamon, Rebecca E. Bettenay, Leigh F. Gilkes, Robert J. Univ Western Australia Sch Earth & Environm Crawley WA 6009 Australia Inkanti Pty Ltd Subiaco WA 6008 Australia

Geochemical analysis of soils using partial extractions, purported to detect only a fraction of elements mobilized during dispersion, represents a useful exploration tool. Interpretation of partial extraction data is, however, subject to uncertainty because the effects of changing soil or sediment properties on extraction are poorly defined. In particular, soil properties which are known to affect the retention of metal ions (e.g. clay content, organic carbon content, pH) may provide useful parameters against which to calculate adjusted total and partial assay values and thereby enhance anomaly contrast in geochemical exploration. Bulk cyanide leach (BCL), a commonly-used weak partial extraction technique, reduces the nugget effect for Au and can provide higher anomaly contrast than total elemental analyses. For a range of elements (Ag, Au, Cd, Co, Cu, Mo, Ni, Pd and Zn), we conducted BCL, determinations, measured the same elements by NAA, XRF or aqua regia digest, and determined a range of soil chemical properties for traverses at 10 exploration prospects in Australia and Namibia. Raw total and BCL, data were compared with (i) concentration : soil parameter ratios, and (ii) adjusted BCL, values based on a simple model of trace element speciation in soils. Anomaly contrasts for raw and normalized or adjusted data were compared using an estimate of anomalism based on both quantitative and heuristic criteria. At prospects with soils containing detectable carbonate, normalization of total and BCL assays to carbonate content significantly improved multi-element anomaly contrast. Normalization to amorphous Fe or Mn oxide content, or total Al, K or Mg also significantly improved anomaly contrast at fewer prospects. Adjusting BCL, values using a simple adsorption model also showed limited success in improving anomaly contrast, and represents a useful framework for interpreting weak partial extraction data.

关键词： geochemical exploration trace elements precious metals base metals bulk cyanide leach

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High-performance astrophysical visualization using Splotch

High-performance astrophysical visualization using Splotch

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International conference on Computational Science (ICCS)

作者： Jin, Zhefan Krokos, Mel Rivi, Marzia Gheller, Claudio Dolag, Klaus Reinecke, Martin Univ Portsmouth Sch Creat Technol Winston Churchill Ave Portsmouth Hants England CINECA Reno Italy Max Planck Inst Astrophys Munich Germany

The scientific community is presently witnessing an unprecedented growth in the quality and quantity of data sets coming from simulations and real-world experiments. To access effectively and extract the scientific content of such large-scale data sets (often sizes are measured in hundreds or even millions of Gigabytes) appropriate tools are needed. visual data exploration and discovery is a robust approach for rapidly and intuitively inspecting large-scale data sets, e. g. for identifying new features and patterns or isolating small regions of interest within which to apply time-consuming algorithms. This paper presents a high performance parallelized implementation of Splotch, our previously developed visual data exploration and discovery algorithm for large-scale astrophysical data sets coming from particle-based simulations. Splotch has been improved in order to exploit modern massively parallel architectures, e. g. multicore CPUs and CUDA-enabled GPUs. We present performance and scalability benchmarks on a number of test cases, demonstrating the ability of our high performance parallelized Splotch to handle efficiently large-scale data sets, such as the outputs of the Millennium ii simulation, the largest cosmological simulation ever performed. (C) 2010 Published by Elsevier Ltd.

关键词： visual Discovery Splotch Numerical Simulations High-Performance visualization MPI CUDA-enabled GPUs Millenium ii Simulation

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visual analytics of a pandemic spread - VAST 2010 mini challenge 2 award: Thorough description of analytic process

Visual analytics of a pandemic spread - VAST 2010 mini chall...

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1st IEEE conference on visual Analytics Science and Technology, VAST 10

作者： Astefanoaie, Andrada Rohrdantz, Christian Bozianu, Rodica Schniertshauerk, Juergen Broghammer, Marc Spretke, David Jungnickel, Roland Bak, Peter University of Konstanz Haifa Research Lab I.B.M. Israel

ISBN: (纸本)9781424494866

In this paper, automated medical data analysis and visualisation are discussed. The task of the VAST 2010 Mini Challenge 2 was to characterize the spread of an epidemic outbreak. The analysis should take into consideration symptoms, mortality rates and temporal patterns of the disease. Finally, the outbreak should be compared across different locations searching for anomalies. For the preprocessing and the automated analysis of the data we used the Konstanz Information Miner (KINME), which is a modular data exploration platform that enables the user to visually create dataflows, the R software for statistical computing and some selfwritten Java programs for data preprocessing. For conducting the visual investigations we applied Many Eyes and Protovis, which compose scalable and customized views for datasets of interest.

关键词： Java Java program Konstanz information miner Many Eyes3 Protovis4 R2 software VAST 2010 mini challenge 2 automated data analysis data analysis data mining data preprocessing data visualisation disease pattern diseases medical administrative data processing modular data exploration platform mortality rates pandemic spread statistical computing visual analytics process

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