914 resultados para high dimensional data, call detail records (CDR), wireless telecommunication industry
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Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e. g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high-dimensional data to 3D visual spaces, based on a generalization of the Least-Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework`s applicability for both visual exploration of multidimensional abstract (non-spatial) data as well as the feature space of multi-variate spatial data.
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In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N (2)) only if the complete set is simultaneously displayed.
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Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.
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Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Purpose: The aim of this paper was to analyze the influence of incorporation of disinfectants during the cast die stone-setting time. Setting time, linear dimensional stability, and reproduction details on casts were measured.Materials and Methods: Die stone type IV specimens with disinfection solutions (sodium hypochlorite 1%, glutaraldehyde 2%, chlorhexidine 2%) were incorporated in two concentrations (50%, 100%). The detail reproduction, dimensional stability, and setting time were tested in accordance with ADA recommendations.Results: Disinfecting solutions promoted an increase in setting time compared to control; sodium hypochlorite was responsible for the highest setting time. The addition of undiluted sodium hypochlorite 1.0% led to contraction during setting, but the groups with 50% diluted sodium hypochlorite 1.0% and undiluted chlorhexidine 2.0% resulted in intermediate values compared to the other groups, thus matching the control. The others did not demonstrate any effect on expansion. For detail reproduction, it was observed that the control group presented results similar to the others, except those where sodium hypochlorite was added.Conclusions The addition of sodium hypochlorite in both dilutions significantly altered, negatively, all the evaluated properties. But the addition of glutaraldehyde and chlorhexidine did not promote any significant alterations in the evaluated properties.
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The aim of this study was to evaluate the dimensional stability and detail reproduction of two silicones used for facial prosthesis, under the influence of chemical disinfection and storage time. Twenty-eight test specimens were obtained, half made of Silastic MDX 4-4210 silicone, and the other half of Silastic 732 RTV silicone. The test specimens were divided into 4 groups: Silastic 732 RTV and Silastic MDX 4-4210, with disinfection 3 times a week with Efferdent and without disinfection. Dimensional change was analyzed using an electronic comparison microscope and detail reproduction was observed under a stereo microscope, immediately and 2 months after the test specimens were made. Once the results were obtained, an analisis of variance (ANOVA) was applied, followed by the Tukey's Test with 1% confidence. The storage time factor had a statistical influence on dimensional stability: Silastic MDX 4-4210 had less contraction than Silastic 732 RTV. Chemical disinfection did not significantly alter the dimensional stability of the materials used. Regarding detail reproduction, no alteration of values was observed in any of the materials analyzed, regardless of storage period or disinfection.
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The aim of the present study was to evaluate the effect of disinfection and accelerated ageing on the dimensional stability and detail reproduction of a facial silicone with different types of nanoparticle. A total of 60 specimens were fabricated with Silastic MDX 4-4210 silicone and they were divided into three groups: colourless and pigmented with nanoparticles (make-up powder and ceramic powder). Half of the specimens of each group were disinfected with Efferdent tablets and half with neutral soap for 60 days. Afterwards, all specimens were subjected to accelerated ageing. Both dimensional stability and detail reproduction tests were performed after specimen fabrication (initial period), after chemical disinfection, and after accelerated ageing periods (252, 504 and 1008 hours). The dimensional stability test was conducted using AutoCAD software, while detail reproduction was analysed using a stereoscope magnifying glass. Dimensional stability values were statistically evaluated by analysis of variance (ANOVA) followed by Tukey's test (p < 0.01). Detail reproduction results were compared using a score. Chemical disinfection and also accelerated ageing affected the dimensional stability of the facial silicone with statistically significant results. The silicone's detail reproduction was not affected by these two factors regardless of nanoparticle type, disinfection and accelerated ageing. © 2012 Informa UK, Ltd.
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Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.
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In questa tesi vengono studiate alcune caratteristiche dei network a multiplex; in particolare l'analisi verte sulla quantificazione delle differenze fra i layer del multiplex. Le dissimilarita sono valutate sia osservando le connessioni di singoli nodi in layer diversi, sia stimando le diverse partizioni dei layer. Sono quindi introdotte alcune importanti misure per la caratterizzazione dei multiplex, che vengono poi usate per la costruzione di metodi di community detection . La quantificazione delle differenze tra le partizioni di due layer viene stimata utilizzando una misura di mutua informazione. Viene inoltre approfondito l'uso del test dell'ipergeometrica per la determinazione di nodi sovra-rappresentati in un layer, mostrando l'efficacia del test in funzione della similarita dei layer. Questi metodi per la caratterizzazione delle proprieta dei network a multiplex vengono applicati a dati biologici reali. I dati utilizzati sono stati raccolti dallo studio DILGOM con l'obiettivo di determinare le implicazioni genetiche, trascrittomiche e metaboliche dell'obesita e della sindrome metabolica. Questi dati sono utilizzati dal progetto Mimomics per la determinazione di relazioni fra diverse omiche. Nella tesi sono analizzati i dati metabolici utilizzando un approccio a multiplex network per verificare la presenza di differenze fra le relazioni di composti sanguigni di persone obese e normopeso.
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Three-dimensional (3D) models of teeth and soft and hard tissues are tessellated surfaces used for diagnosis, treatment planning, appliance fabrication, outcome evaluation, and research. In scientific publications or communications with colleagues, these 3D data are often reduced to 2-dimensional pictures or need special software for visualization. The portable document format (PDF) offers a simple way to interactively display 3D surface data without additional software other than a recent version of Adobe Reader (Adobe, San Jose, Calif). The purposes of this article were to give an example of how 3D data and their analyses can be interactively displayed in 3 dimensions in electronic publications, and to show how they can be exported from any software for diagnostic reports and communications among colleagues.