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Annual conference of the International-Association-for-Mathematical-Geology

作者： Grunsky, E de Kemp, E Geol Survey Canada Ottawa ON K1A 0E8 Canada

ISBN: (纸本)0973422017

Characterization of the spatial distribution, shape properties and preferred orientation of structural elements at a wide range of scales is at the heart of tectonic analysis. This study attempts to explore a virtual 3-D reconstruction of mylonite microfabric in order to determine what new analysis opportunities are available and what, if any, problems are encountered in this kind of study. From the primary data of scanned and digitized serial sections of a mylonitic sample, a dense 3-D voxel-based model was constructed. We present various visualizations of the model and highlight issues relating to data density, porphyroclast classification by intensity thresholding, interpolation and representation. The goal of providing a geologist with a better environment to characterize the cumulative strain fabric from hand sample-sized objects was kept in mind. At the same time, an opportunity to develop better approaches to characterizing natural vector fields at all scales may emerge from this study.

关键词： visualization

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Mapping the contemporary terrorism research domain: Researchers, publications, and institutions analysis

Mapping the contemporary terrorism research domain: Research...

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IEEE International conference on Intelligence and Security Informatics (ISI 2005)

作者： Reid, E Chen, HC Univ Arizona Dept Management Infomat Syst Tucson AZ 85721 USA

ISBN: (纸本)3540259996

The ability to map the contemporary terrorism research domain involves mining, analyzing, charting, and visualizing a research area according to experts, institutions, topics, publications, and social networks. As the increasing flood of new, diverse, and disorganized digital terrorism studies continues, the application of domain visualization techniques are increasingly critical for understanding the growth of scientific research, tracking the dynamics of the field, discovering potential new areas of research, and creating a big picture of the field's intellectual structure as well as challenges. In this paper, we present an overview of contemporary terrorism research by applying domain visualization techniques to the literature and author citation data from the years 1965 to 2003. The data were gathered from ten databases such as the ISI Web of Science then analyzed using an integrated knowledge mapping framework that includes selected techniques such as self-organizing map (SOM), content map analysis, and co-citation analysis. The analysis revealed (1) 42 key terrorism researchers and their institutional affiliations;(2) their influential publications;(3) a shift from focusing on terrorism as a low-intensity conflict to an emphasis on it as a strategic threat to world powers with increased focus on Osama Bin Laden;and (4) clusters of terrorism researchers who work in similar research areas as identified by co-citation and block-modeling maps.

关键词： Social aspects

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Accuracy of MLP based data visualization used in oil prices forecasting task

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13th International conference on Image analysis and Processing

作者： Raudys, A Inst Math & Informat LT-08633 Vilnius Lithuania

ISBN: (纸本)3540288694

We investigate accuracy, neural network complexity and sample size problem in multilayer perceptron (MLP) based (neuro-linear) feature extraction. For feature extraction we use weighted sums calculated in hidden units of the MLP based classifier. Extracted features are utilized for data visualisation in 2D and 3D spaces and interactive formation of the pattern classes. We show analytically how complexity of feature extraction algorithm depends on the number of hidden units. Sample size-complexity relations investigated in this paper showed that reliability of the neuro-linear feature extraction could become extremely low if number of new features is too high. Visual interactive inspection of data projection may help an investigator to look differently at the forecasting problem of the financial time series.

关键词： feature extraction data mapping sample size neural network

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Explorative data analysis based on self-organizing maps and automatic map analysis

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8th Biennial Meeting of the International Work-conference on Artificial Neural Networks

作者： Franzmeier, M Witkowski, U Rückert, U Univ Paderborn Heinz Nixdorf Inst Paderborn Germany

ISBN: (纸本)3540262083

In the field of explorative data analysis self-organizing maps have been used successfully for a lot of applications. In our case, we apply the self-organizing map for the analysis of semiconductor fabrication data by training recorded high dimensional data sets. Usually, the training result is displayed by using appropriate visualization techniques and the results are evaluated manually. Especially for large data sets an automated post-processing of the training result is essential. In this paper an automatic training result analysis based on specific image processing is introduced. Dependencies between components maps are calculated by structure overlapping analysis based on the segmentation of component maps. This novel method has been integrated into the data analysis software DanI, that simulates self-organizing maps for data analysis with several pre-processing and post-processing capabilities.

关键词： Self organizing maps

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Spectral analysis techniques applied to blasting vibration

Spectral analysis techniques applied to blasting vibration

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14th International Symposium on Mine Planning and Equipment Selection, MPES 2005 and the 5th International conference on Computer Applications in the Minerals Industries, CAMI 2005

作者： Aldaş, Gulsev Uyar Department of Geophysical Engineering Faculty of Engineering Ankara University Turkey

Much of blasting induced vibration analysis is concerned with the measurement and analysis of waveforms that express the variation of some measurable quantity as a function of distance or time. The quantity is the displacement of the ground surface as a function of time associated with the passage of seismic waves from a nearby explosion. The analysis of waveforms such as these represents an essential aspect of data processing and interpretation. Usually we think of vibration data as the variation with time of the amplitudes of various geophone outputs. However, it should be convenient to regard a vibration wave as the result of the superposition of many sinusoidal waves differing in frequency, amplitude and phase;the relative amplitudes and phases are regarded as functions of the frequency. This study covers some spectral analysis techniques, applied to blasting induced ground vibration data, including frequency filtering which will do the best job of converting an input into a desired output, fourier analysis involving transforming functions from the time domain to the frequency domain and stockwell analysis including representation of spectral component of a time series. Therefore it is possible to find a visualization method that will give a better way of displaying the high amplitudes and time duration of waveforms in low frequency zone. Moreover most convenient delay interval between each shot to overcome superposition is proposed.

关键词： Blasting

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Opportunity map: A visualization framework for fast identification of actionable knowledge

Opportunity map: A visualization framework for fast identifi...

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CIKM'05 - Proceedings of the 14th ACM International conference on Information and Knowledge Management

作者： Zhao, Kaidi Liu, Bing Tirpak, Thomas M. Xiao, Weimin Department of Computer Science University of Illinois at Chicago 851 S. Morgan Street Chicago IL 60607 United States Motorola Labs 1301 E. Algonquin Rd. Schaumburg IL 60196 United States

ISBN: (纸本)1595931406

data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interesting and actionable rules. Due to the subjective nature of "interestingness", human involvement in the analysis process is crucial. In this paper, we propose a novel visual data mining framework for the purpose of identifying actionable knowledge quickly and easily from discovered rules and data. This framework is called the Opportunity Map. It is inspired by some interesting ideas from Quality Engineering, in particular Quality Function Deployment (QFD) and the House of Quality. It associates summarized data or discovered rules with the application objective using an interactive matrix, which enables the user to quickly identify where the opportunities are. The proposed system can be used to visually analyze discovered rules, and other statistical properties of the data. The user can also interactively group actionable attributes and values, and see how they affect the targets of interest. Combined with drill-down and comparative analysis, the user can analyze rules and data at different levels of detail. The proposed visualization framework thus represents a systematic and yet flexible method of rule analysis. Applications of the system to large-scale data sets from our industrial partner have yielded promising results. Copyright 2005 ACM.

关键词： Knowledge engineering

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3D visualization techniques and its usefulness of eyeground images data sets generated by Optical Coherence Tomography

3D visualization techniques and its usefulness of eyeground ...

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11th International conference on Parallel and Distributed Systems

作者： Ito, F Doi, A Tokuda, M Faculty of Software and Information Science Iwate Prefectural University Japan Microtomography Corporation Japan

ISBN: (纸本)0769522815

Tomogram of eyeground images by Optical Coherence Tomography(OCT) are a set of the echo information on a minute portion by the scanning beam. These images contain many random noises and gap between images. Images of OCT are strongly influenced of the motion-induced artifacts during the image acquisition, pulsation by the living body organization. Therefore, it is difficult to form 3D volume images. In this research, a noise removal of 2D images and position alignment processing were performed as a pretreatment of 3D visualization. 3D images contribute to medical treatment Of eyeground disease and informed consent. We utilized a texture-based volume rendering technique, and evaluated the usefulness of the 3D eyeground model in the medical treatment of eyeground disease.

关键词： Image analysis

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Choices for tissue visualization with IR micro spectroscopy

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VIBRATIONAL SPECTROSCOPY 2005年第1-2期38卷 133-141页

作者： Gough, K Rak, M Bookatz, A Del Bigio, M Mai, S Westaway, D Univ Manitoba Dept Chem Winnipeg MB R3T 2N2 Canada Univ Manitoba Dept Pathol Winnipeg MB R3E 0W3 Canada Univ Manitoba Manitoba Inst Cell Biol Winnipeg MB R3E 0V9 Canada Univ Toronto Ctr Res Neurodegenerat Dis Toronto ON M5S 3H2 Canada

In this paper, we address some of the issues associated with infrared (IR) imaging, with reference to our work on brain tissue from the TgCRND8 mouse, a transgenic model of Alzheimer's disease (AD). AD is the most common cause of dementia in the aging population. One of the characteristic hallmarks of this chronic neurodegenerative disorder is the accumulation of plaques in the brain, usually visualized with histochemistry and immunostaining. Although these methods are extremely useful, they illustrate only certain aspects of the sample, require a great amount of tissue processing, and are highly dependent on experimental protocols and reagent quality. IR imaging provides information on multiple components, with a minimal amount of sample processing. However, in order to interpret the data successfully, the issues of spectral acquisition parameters, pre-processing, and spectral artifacts need to be considered. The methods commonly used to process the data, such as uni- and bi-variate spectral analysis, and multivariate methods, such as hierarchical cluster analysis, and some issues concerning the use of second derivatives of IR spectra are discussed. (c) 2005 Elsevier B.V. All rights reserved.

关键词： infrared microspectroscopy Alzheimer's disease spectral data processing second derivative

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Phase coherence theory for data-mining and analysis: Application studies in spectroscopy

Phase coherence theory for data-mining and analysis: Applica...

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Opto-Ireland 2005 conference

作者： Doyle, G McMillan, ND Murtagh, F O'Neill, M Riedel, S Perova, TS Unnikrishnan, S Moore, RA Inst Technol Carlow Carlow Ireland

ISBN: (纸本)0819458082

The paper investigates from the perspective of computer science the phase coherence theory (PCT) and phase coherent data-scatter (PCD-S). These techniques were originally developed for the area of optical tensiographic data mining and analysis but have a more general application in data mining. These developments have recently been augmented with the engineering of a software toolkit called TraceMiner. Although the toolkit was originally devised for tensiography it was developed to perform as a generic data mining and analysis application with PCT, PCD-S and a range of other data mining algorithms implemented. To date the toolkit has been utilised in its main application area, tensiography, but has also been applied to UV-visible spectroscopy. This work presents a critical investigation of the general utility of PCT, PCD-S and the toolkit for data mining and analysis. A new application of PCT and the TraceMiner software toolkit to Raman spectroscopy is presented with discussion of the relevant measures and the information provided by the toolkit. This provides more insight into the generic potential of the techniques for data mining. The analysis performed on theoretical Raman data is augmented with a study of experimental Raman data. Raman spectroscopy is used for composition and fault detection analysis in semiconductor surfaces. Finally, the utility of the PCT technique in comparison with traditional Raman spectroscopy methods is considered together with some more general applications in the field of imaging and machine vision.

关键词： Raman spectroscopy data mining data modeling visualization Spectroscopy Statistical analysis Computer science Semiconductors Algorithm development Software development

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Volumetric data analysis using Morse-Smale complexes

Volumetric data analysis using Morse-Smale complexes

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7th International conference on Shape Modeling and Applications

作者： Natarajan, V Pascucci, V Univ Calif Davis Inst Data Anal & Visualizat Davis CA 95616 USA

ISBN: (纸本)076952379X

The 3D Morse-Smale complex is a fundamental topological construct that partitions the domain of a real-valued function into regions having uniform gradient flow behavior In this paper, we consider the construction and selective presentation of cells of the Morse-Smale complex and their use in the analysis and visualization of scientific datasets. We take advantage of the fact that cells of different dimension often characterize different types of features present in the data. For example, critical points pinpoint changes in topology by showing where components of the level sets are created, destroyed or modified in genus. Edges of the Morse-Smale complex extract filament-like features that are not explicitly modeled in the original data. Interactive selection and rendering of portions of the Morse-Smale complex introduces fundamental data management challenges due to the unstructured nature of the complex even for structured inputs. We describe a data structure that stores the Morse-Smale complex and allows efficient selective traversal of regions of interest. Finally, we illustrate the practical use of this approach by applying it to cryo-electron microscopy data of protein molecules.

关键词： data reduction

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