41 resultados para VISUALIZATION


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Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the network

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The chemical composition of sediments and rocks, as well as their distribution at theMartian surface, represent a long term archive of processes, which have formed theplanetary surface. A survey of chemical compositions by means of Compositional DataAnalysis represents a valuable tool to extract direct evidence for weathering processesand allows to quantify weathering and sedimentation rates. clr-biplot techniques areapplied for visualization of chemical relationships across the surface (“chemical maps”).The variability among individual suites of data is further analyzed by means of clr-PCA,in order to extract chemical alteration vectors between fresh rocks and their crusts andfor an assessment of different source reservoirs accessible to soil formation. Bothtechniques are applied to elucidate the influence of remote weathering by combinedanalysis of several soil forming branches. Vector analysis in the Simplex provides theopportunity to study atmosphere surface interactions, including the role andcomposition of volcanic gases

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Durant el projecte s'ha planificat i dut a terme la creació i verificació d'un APP que simula una aplicació comercial senzilla. S'ha seleccionat una localització, el centre comercial l'Illa Diagonal, s'ha calibrat seguint les instruccions de WiFiSLAM, s'ha creat un APP que integra la visualització de la posició sobre plànol basada en el SDK de WiFiSLAM amb funcions de càlcul de distàncies i s'han fet proves per acotar la fiabilitat de la solució, la seva exactitud i la seva precisió.

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Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

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Perceptual maps have been used for decades by market researchers to illuminatethem about the similarity between brands in terms of a set of attributes, to position consumersrelative to brands in terms of their preferences, or to study how demographic and psychometricvariables relate to consumer choice. Invariably these maps are two-dimensional and static. Aswe enter the era of electronic publishing, the possibilities for dynamic graphics are opening up.We demonstrate the usefulness of introducing motion into perceptual maps through fourexamples. The first example shows how a perceptual map can be viewed in three dimensions,and the second one moves between two analyses of the data that were collected according todifferent protocols. In a third example we move from the best view of the data at the individuallevel to one which focuses on between-group differences in aggregated data. A final exampleconsiders the case when several demographic variables or market segments are available foreach respondent, showing an animation with increasingly detailed demographic comparisons.These examples of dynamic maps use several data sets from marketing and social scienceresearch.

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This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

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We consider the joint visualization of two matrices which have common rowsand columns, for example multivariate data observed at two time pointsor split accord-ing to a dichotomous variable. Methods of interest includeprincipal components analysis for interval-scaled data, or correspondenceanalysis for frequency data or ratio-scaled variables on commensuratescales. A simple result in matrix algebra shows that by setting up thematrices in a particular block format, matrix sum and difference componentscan be visualized. The case when we have more than two matrices is alsodiscussed and the methodology is applied to data from the InternationalSocial Survey Program.

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The case of two transition tables is considered, that is two squareasymmetric matrices of frequencies where the rows and columns of thematrices are the same objects observed at three different timepoints. Different ways of visualizing the tables, either separatelyor jointly, are examined. We generalize an existing idea where asquare matrix is descomposed into symmetric and skew-symmetric partsto two matrices, leading to a decomposition into four components: (1)average symmetric, (2) average skew-symmetric, (3) symmetricdifference from average, and (4) skew-symmetric difference fromaverage. The method is illustrated with an artificial example and anexample using real data from a study of changing values over threegenerations.

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DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (~5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. Availability: The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp

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BACKGROUND: DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. RESULTS: We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i) exhaustive population-genetic analyses including those based on the coalescent theory; ii) analysis adapted to the shallow data generated by the high-throughput genome projects; iii) use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv) identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v) visualization of the results integrated with current genome annotations in commonly available genome browsers. CONCLUSION: VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.

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In this paper we present the ViRVIG Institute, a recently created institution that joins two well-known research groups: MOVING in Barcelona, and GGG in Girona. Our main research topics are Virtual Reality devices and interaction techniques, complex data models, realistic materials and lighting, geometry processing, and medical image visualization. We briefly introduce the history of both research groups and present some representative projects. Finally, we sketch our lines for future research

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There is a concern that agriculture will no longer be able to meet, on a global scale, the growing demand for food. Facing such a challenge requires new patterns of thinking in the context of complexity and sustainability sciences. This paper, focused on the social dimension of the study and management of agricultural systems, suggests that rethinking the study of agricultural systems entails analyzing them as complex socio-ecological systems, as well as considering the differing thinking patterns of diverse stakeholders. The intersubjective nature of knowledge, as studied by different philosophical schools, needs to be better integrated into the study and management of agricultural systems than it is done so far, forcing us to accept that there are no simplistic solutions, and to seek a better understanding of the social dimension of agriculture. Different agriculture related problems require different policy and institutional approaches. Finally, the intersubjective nature of knowledge asks for the visualization of different framings and the power relations taking place in the decision-making process. Rethinking management of agricultural systems implies that policy making should be shaped by different principles: learning, flexibility, adaptation, scale-matching, participation, diversity enhancement and precaution hold the promise to significantly improve current standard management procedures.

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This work investigates novel alternative means of interaction in a virtual environment (VE).We analyze whether humans can remap established body functions to learn to interact with digital information in an environment that is cross-sensory by nature and uses vocal utterances in order to influence (abstract) virtual objects. We thus establish a correlation among learning, control of the interface, and the perceived sense of presence in the VE. The application enables intuitive interaction by mapping actions (the prosodic aspects of the human voice) to a certain response (i.e., visualization). A series of single-user and multiuser studies shows that users can gain control of the intuitive interface and learn to adapt to new and previously unseen tasks in VEs. Despite the abstract nature of the presented environment, presence scores were generally very high.

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BACKGROUND: DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. RESULTS: We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i) exhaustive population-genetic analyses including those based on the coalescent theory; ii) analysis adapted to the shallow data generated by the high-throughput genome projects; iii) use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv) identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v) visualization of the results integrated with current genome annotations in commonly available genome browsers. CONCLUSION: VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.

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This work investigates novel alternative means of interaction in a virtual environment (VE).We analyze whether humans can remap established body functions to learn to interact with digital information in an environment that is cross-sensory by nature and uses vocal utterances in order to influence (abstract) virtual objects. We thus establish a correlation among learning, control of the interface, and the perceived sense of presence in the VE. The application enables intuitive interaction by mapping actions (the prosodic aspects of the human voice) to a certain response (i.e., visualization). A series of single-user and multiuser studies shows that users can gain control of the intuitive interface and learn to adapt to new and previously unseen tasks in VEs. Despite the abstract nature of the presented environment, presence scores were generally very high.