Existing static visualization techniques for eye-tracking data do not make it possible to easily compare temporal information, that is, gaze paths. We review existing techniques and then propose a new technique that t...
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A method is proposed for performing spectral gamut mapping, whereby spectral images can be altered to fit within an approximation of the spectral gamut of an output device. Principal component analysis (PCA) is perfor...
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ISBN:
(纸本)0819456403
A method is proposed for performing spectral gamut mapping, whereby spectral images can be altered to fit within an approximation of the spectral gamut of an output device. Principal component analysis (PCA) is performed on the spectral data, in order to reduce the dimensionality of the space in which the method is applied. The convex hull of the spectral device measurements in this space is computed, and the intersection between the gamut surface and a line from the center of the gamut towards the position of a given spectral reflectance curve is found. By moving the spectra that are outside the spectral gamut towards the center until the gamut is encountered, a spectral gamut mapping algorithm is defined. The spectral gamut is visualized by approximating the intersection of the gamut and a 2-dimensional plane. The resulting outline is shown along with the center of the gamut and the position of a spectral reflectance curve. The spectral gamut mapping algorithm is applied to spectral data from the Macbeth Color Checker and test images, and initial results show that the amount of clipping increases with the number of dimensions used.
Information Technologies (IT) are increasingly allowing for advances in monitoring and analysis of structural response. Sensor networks can provide real-time data streams, as a basis for system identification and deci...
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ISBN:
(纸本)0784407940
Information Technologies (IT) are increasingly allowing for advances in monitoring and analysis of structural response. Sensor networks can provide real-time data streams, as a basis for system identification and decision-making. Fusion of video-derived information along with motion and strain sensors is already showing much promise. An integrated analysis framework encompasses data acquisition, database archiving, and model-free/model-based system identification/data mining techniques, towards the development of practical decision-making tools. Within this framework, data from experiments continues to provide much needed physical insight, as a basis for calibration of appropriate numerical models. In this regard, large-scale parallel computing and powerful visualization tools of soil-structure systems are a necessity.
The number of ITSs being used daily is growing steadily. Consequently, huge amounts of interaction data are available, but dataanalysis is still very laborious. This paper describes the use of data mining processes t...
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ISBN:
(纸本)9781586035303
The number of ITSs being used daily is growing steadily. Consequently, huge amounts of interaction data are available, but dataanalysis is still very laborious. This paper describes the use of data mining processes to investigate student interaction with a constraint-based tutor. We discuss how statistical analyses, information visualization and machine learning algorithms can be used to discover interesting patterns in data, and how the findings can be used to improve the system.
This paper presents CorpusDRF, an open-source, digitized collection of regionalisms, their parts of speech and recognition rates, published in Dictionnaire des Regionalismes de France (DRF, "Dictionary of Regiona...
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ISBN:
(纸本)9791095546009
This paper presents CorpusDRF, an open-source, digitized collection of regionalisms, their parts of speech and recognition rates, published in Dictionnaire des Regionalismes de France (DRF, "Dictionary of Regionalisms of France") (Rezeau, 2001), enabling the visualization and analyses of the largest-scale study of French regionalisms in the 20th century using publicly available data. CorpusDRF was curated and checked manually against the entirety of the printed volume of more than 1000 pages. It contains all the entries in the DRF for which recognition rates in continental France were recorded from the surveys carried out from 1994 to 1996 and from 1999 to 2000. In this paper, in addition to introducing the corpus, we also offer some exploratory visualizations using an easy-to-use, freely available web application and compare the patterns in our analysis with that by (Goebl, 2005a) and (Goebl, 2007).
Lowering computational cost of dataanalysis and visualization techniques is an essential step towards including the user in the visualization. In this paper we present an improved algorithm for visual clustering of l...
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ISBN:
(纸本)0769523978
Lowering computational cost of dataanalysis and visualization techniques is an essential step towards including the user in the visualization. In this paper we present an improved algorithm for visual clustering of large multidimensional data sets. The original algorithm is an approach that deals efficiently with multi-dimensionality using various projections of the data in order to perform multispace clustering, pruning outliers through direct user interaction. The algorithm presented here, named HC-Enhanced (for Human-Computer enhanced), adds a scalability level to the approach without reducing clustering quality. Additionally, an algorithm to improve clusters is added to the approach. A number of test cases is presented with good results.
Worksheets are a new user-interface framework to support analysis of streaming data by combining streaming data queries with visualization objects in a composable document framework. A worksheet lets users work at hum...
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Today’s scientific simulations often generate huge amounts of data for data archival, dataanalysis, and visualization. These data are stored in high-performance distributed storages that consist of a network-oriente...
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We introduce the new nonlinear dimension reduction method: LTSA, in dealing with the difficulty of analyzing high-dimensional, nonlinear microarray data. Firstly, we analyze the applicability of the method and we prop...
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ISBN:
(纸本)0780391365
We introduce the new nonlinear dimension reduction method: LTSA, in dealing with the difficulty of analyzing high-dimensional, nonlinear microarray data. Firstly, we analyze the applicability of the method and we propose the reconstruction error of LTSA. The method is tested on Iris data set and acute leukemias microarray data. The results show good visualization performance. And LTSA outperforms PCA on determining the reduced dimension. There is only subtle change in the clustering correctness after dimension reduction by LTSA. It is evident that application of nonlinear dimension reduction techniques could have a promising perspective in microarray dataanalysis.
The visual analysis of lime dependent data is an essential task in many application fields. However, visualizing large time dependent data collected within a spatial context is still a challenging task. In this paper,...
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ISBN:
(纸本)0769523978
The visual analysis of lime dependent data is an essential task in many application fields. However, visualizing large time dependent data collected within a spatial context is still a challenging task. In this paper, we therefore describe an approach for visualizing spatio-temporal data on maps. The approach is based on two commonly used concepts: 3D information visualization and information hiding. These concepts are realized by means of novel embeddings of 3D icons into a map display for representing spatio-temporal data, and an integration of event-based methods for reducing the amount Of information to be represented. Our approach is capable of visualizing multiple time dependent attributes on maps, and of emphasizing the characteristics constituted by either linear or cyclic temporal dependencies.
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