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Testing of uniformity of seven Lathyrus species using Bennett's and Miller's methods

EUPHYTICA 2016年第1期208卷 123-128页

作者： Zawieja, Bogna Rybinski, Wojciech Nowosad, Kamila Piesik, Dariusz Bocianowski, Jan Poznan Univ Life Sci Dept Math & Stat Methods Wojska Polskiego 28 PL-60637 Poznan Poland Polish Acad Sci Inst Plant Genet Poznan Poland Wroclaw Univ Environm & Life Sci Dept Genet Plant Breeding & Seed Prod Wroclaw Poland UTP Univ Sci & Technol Dept Entomol & Mol Phytopathol Bydgoszcz Poland

In this paper we focused on uniformity of seven Lathyrus species: Lathyrus aphaca, L. cicero, L. clymenum, L. hirsutus, L. ochrus, L. sativus and L. tingitanus. Two statistical methods, the Bennett's and the Miller's were compared. In both methods, coefficient of variation for evaluation of the uniformity of crop varieties was used. Four quantitative traits were analyzed: length of the pod, width of the pod, weight of seeds from the pod and 100 seed weight. The results of the study demonstrated that, the Bennett's method is less restrictive (lesser species were found to be uniform in analyzed traits) compared to the Miller's one.

关键词： Coefficient of variation Lathyrus species parallel coordinate plot Quantitative traits Uniformity

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Quantitative Exploration of Large Medieval Manuscripts Data for the Codicological Research 6

Quantitative Exploration of Large Medieval Manuscripts Data ...

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6th IEEE Symposium on Large Data Analysis and Visualization (LDAV)

作者： Chandna, Swati Rindone, Francesca Dachsbacher, Carsten Stotzka, Rainer Karlsruhe Inst Technol Inst Data Proc & Elect Karlsruhe Germany Karlsruhe Inst Technol Inst Visualizat & Data Anal Karlsruhe Germany

ISBN: (纸本)9781509056590

Quantitative exploration is gaining in importance for the analysis of the digitized medieval manuscripts. While codicologists can collect such massive amounts of heterogeneous datasets digitized in high-resolution, they still lack efficient and intuitive means to explore data and answer domain-specific research questions. A new approach is needed to enable codicologists with the quantitative exploration of large of data. This paper presents a concept of a fully integrated system to enable a quantitative exploration of various layout features and their uncertainties over a large collection of medieval manuscripts. It is composed of three main components: data handling that ingests large amounts of data into a data repository, feature extraction that extracts various layout features of the manuscripts and quantitative exploration for visual analysis. In addition to this, we introduce new visualization approaches, i.e. the superimposition plot and the manuscript montage plot in combination with the parallel coordinate plot to explore structural layout features of 170,000 manuscript pages with more than 2.5 million measurements of these layout features. Our approach supports codicologists to see the overall structure of the manuscript at a single glimpse, explore heterogeneous layout features and convey uncertainties. We demonstrate typical use-case scenarios of our collaborators in codicological research where our system has enabled them to answer domain-specific questions for analysis of the medieval manuscripts data for the first time.

关键词： medieval manuscripts visualization codicology data handling feature extraction parallel coordinate plot quantitative exploration uncertainties knowledge discovery

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Do choropleth maps linked with parallel coordinates facilitate an understanding of multivariate spatial characteristics?

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CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE 2014年第5期41卷 413-429页

作者： Opach, Tomasz Rod, Jan Ketil Norwegian Univ Sci & Technol Dept Geog NO-7491 Trondheim Norway

Our study has three objectives. We want to investigate (1) whether choropleth maps linked with parallel coordinates help people understand the locations of vulnerable places and the factors making these places vulnerable, (2) whether sparklines that imitate the polylines from a parallel coordinate plot support the understanding of the information provided in that plot, and (3) whether a multiple-view geovisualization approach might be intuitive and useful also for nonexperts. Although we base our work on the functionalities available in the tool called 'ViewExposed,' we intend to outline more general conclusions on whether multiple linked views facilitate the understanding of multivariate spatial characteristics. An empirical study with 53 individuals was conducted to obtain insights on these objectives. Our task-based assessment considered the ways in which participants understood the dynamic linking capabilities. Some of the key findings are as follows: (1) even nonexpert users are able to use parallel coordinates linked with choropleth maps;however, only those with extensive inference-making abilities will do so efficiently;(2) parallel coordinates sparklines work as an independent component facilitating the understanding of multivariate data;and (3) the intuitive nature of a multiple-view geovisualization tool is not enough to encourage people to use it.

关键词： sparklines choropleth map geographic visualization interactive cartography parallel coordinate plot

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A parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data

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TECHNOMETRICS 2013年第4期55卷 513-523页

作者： Chen, Wei-Chen Ostrouchov, George Pugmire, David Prabhat Wehner, Michael Univ Tennessee Dept Ecol & Evolutionary Biol Knoxville TN 37996 USA Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN 37831 USA Univ Calif Berkeley Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA

We develop a parallel expectation-maximization (EM) algorithm for multivariate Gaussian mixture models and use it to perform model-based clustering of a large climate dataset. Three variants of the EM algorithm are reformulated in parallel and a new variant that is faster is presented. All are implemented using the single program, multiple data programming model, which is able to take advantage of the combined collective memory of large distributed computer architectures to process larger datasets. Displays of the estimated mixture model rather than the data allow us to explore multivariate relationships in a way that scales to arbitrary size data. We study the performance of our methodology on simulated data and apply our methodology to a high-resolution climate dataset produced by the community atmosphere model (CAM5). This article has supplementary material online.

关键词： parallel computing parallel coordinate plot Spatial time series Unsupervised learning

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Improving the visualization of the Pareto-optimal front for the multi-response optimization of chromatographic determinations

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ANALYTICA CHIMICA ACTA 2011年第2期687卷 129-136页

作者： Ortiz, M. C. Sarabia, L. A. Sanchez, M. S. Arroyo, D. Univ Burgos Fac Sci Dep Chem Burgos 09001 Spain Univ Burgos Fac Sci Dep Math & Computat Burgos 09001 Spain

The paper shows tools to visualize and more easily interpret the effect that some experimental factors may exert on analytical responses of interest when optimization of several responses is needed. It is based on an adaptation of the parallel coordinate plot, a tool for graphical representation of points in multidimensional spaces that, theoretically and contrary to the usual Cartesian plots, does not have limits in the dimension of the points being depicted. The joint use of the Pareto-optimal solutions and their visualization allows a deeper knowledge about the problem at hand as well as the wise selection of the conditions of experimental factors for achieving specific goals about the responses. Although the methodology is for a general use, the procedure, its interpretation and usefulness is shown with several analytical cases in chromatography. The first one refers to the experimental conditions to obtain simultaneously the maximum allowable area for both the peak of the malachite green and its metabolite leucomalachite green in fish by liquid chromatography with tandem mass spectrometry detection (LC-MS/MS). The second one is about the simultaneous determination of steroid hormones estrone and 17-alpha-ethinylestradiol by gas chromatography-mass spectrometry (GC/MS). In the last case, the chromatographic separation by GC/MS of the diastereoisomers, alpha- and beta-estradiol is needed taking into account that these hormones have the same mass fragments. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Chromatography Pareto-optimal front Multiresponse optimization parallel coordinate plot Hormones Fungicides

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Yet another visualization of the Iris data: The bridge plot

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Model Assisted Statistics and Applications 2011年第1期6卷 11-16页

作者： Kozak, Marcin Department of Experimental Design and Bioinformatics Warsaw University of Life Sciences 02-776 Warsaw Nowoursynowska 159 Poland

The bridge plot is used to visualize the famous Iris data. With the help of trellis system to condition the data on species, the plot presents four iris flower traits in their original units within a single panel. Such a plot can be employed when among four variables there are two groups each consisting of two variables having the same and comparable units. © 2011 - IOS Press and the authors. All rights reserved.

关键词： Original units parallel coordinate plot scatterplot matrix

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Mondrian

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WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS 2010年第5期2卷 606-612页

作者： Theus, Martin Univ Augsburg Dept Comp Oriented Stat & Data Anal D-86135 Augsburg Germany

Mondrian is a general-purpose statistical data-visualization system [Theus M. Interactive data visualization using Mondrian. J Stat Softw 2003, 7: 1-9]. It features outstanding visualization techniques for data of almost any kind, and has its particular strength compared to other tools when working with categorical data, geographical data, and large data sets. Data displays in Mondrian are interactive, i.e., plot parameters may be changed interactively resulting in an instantaneous update of the views. Furthermore, all plots in Mondrian are fully linked, i.e., any case selected or marked in a plot in Mondrian is highlighted in all other linked plots. Mondrian offers interactive queries, which show information of the data objects in any plot. (C) 2010 John Wiley & Sons, Inc.

关键词： exploratory data analysis statistical graphics selection and linked highlighting parallel coordinate plot mosaic plot

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Error detection in three-dimensional surface anthropometric data

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INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS 2009年第1期39卷 277-282页

作者： Park, Jinwoo Nam, Yunja Lee, Eunkyung Park, Sunmi Univ Suwon Dept Appl Stat Bongdam Eup Whasung Si South Korea Ewha Womans Univ Dept Stat Seoul South Korea Seoul Natl Univ Dept Clothing Text Seoul South Korea

In recent years, the use of three-dimensional surface anthropometry has facilitated the collection of anthropometric data. Given the importance of reducing errors and securing data quality, data checking procedures are necessary. After an influential study done by Fellegi, I.P., Holt, C. [1976. A systematic approach to automatic edit and imputation. journal of the American Statistical Association 71, 17-35], many survey organizations adopted data checking procedures to determine whether data are reliable or not. Detection of erroneous data is an essential part of data checking. An important feature of anthropometric data is that the data are continuous and multivariate and have strong correlations among variables. Because of the patterns of intermittent errors in multivariate data, data checking can be very complicated. The objective of this study is to propose an error detection procedure that uses a dynamic and interactive graphical method for anthropometric data. Furthermore, we present the results from applying this procedure to the data from the Korean National Anthropometric Survey, Size Korea 2004. Relevance to industry: Anthropometric data provide a valuable source of information to ergonomists and designers. The results of this study can help to increase the reliability of anthropometric data collected by three-dimensional measurement approaches. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Anthropometry Three-dimensional measurement Projection pursuit guided tour parallel coordinate plot Error detection

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CellProfiler Analyst: data exploration and analysis software for complex image-based screens

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BMC BIOINFORMATICS 2008年第1期9卷 482-482页

作者： Jones, Thouis R. Kang, In Han Wheeler, Douglas B. Lindquist, Robert A. Papallo, Adam Sabatini, David M. Golland, Polina Carpenter, Anne E. MIT & Harvard Broad Inst Cambridge MA 02142 USA Whitehead Inst Biomed Res Cambridge MA 02142 USA MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02142 USA MIT Dept Biol Cambridge MA 02142 USA

Background: Image-based screens can produce hundreds of measured features for each of hundreds of millions of individual cells in a single experiment. Results: Here, we describe CellProfiler Analyst, open-source software for the interactive exploration and analysis of multidimensional data, particularly data from high-throughput, image-based experiments. Conclusion: The system enables interactive data exploration for image-based screens and automated scoring of complex phenotypes that require combinations of multiple measured features per cell.

关键词： Additional Data File Cell Cycle Distribution Sequential Gating parallel coordinate plot Telophase Nucleus

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Optimization of principal component analysis in feature extraction

Optimization of principal component analysis in feature extr...

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IEEE International Conference on Mechatronics and Automation

作者： Gao Haibo Hong Wenxue Cui Jianxin Xu Yonghong Univ Yanshan Dept Biomed Engn Quihuangdao Hebei Peoples R China

ISBN: (纸本)9781424408276

A novel method for optimising the principal component analysis in feature extraction is proposed, which makes use of parallel coordinate plot for graphical presentation of multivariate information. The objectivity and automatization of above manual observation and filtering process is realized by algorithm. In supervised multivariate information classification, before feature extraction on principal component analysis, filtering the variable that has bigger variance and has little effect on classification by observing the parallel coordinate plot of the multivariate data, the eigenvector from principal component analysis will be more in favor of classification. We achieved better performance when using this method to test the vegetable oil data. We believe that this method can be used in many other feature extraction methods, and will obtain better performance than them.

关键词： multivariate information classification principal component analysis feature extraction parallel coordinate plot sorted overlap coefficient

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