Query-Driven Visualization and Analysis

Energy Technology Data Exchange (ETDEWEB)

Ruebel, Oliver; Bethel, E. Wes; Prabhat, Mr.; Wu, Kesheng

2012-11-01

This report focuses on an approach to high performance visualization and analysis, termed query-driven visualization and analysis (QDV). QDV aims to reduce the amount of data that needs to be processed by the visualization, analysis, and rendering pipelines. The goal of the data reduction process is to separate out data that is "scientifically interesting'' and to focus visualization, analysis, and rendering on that interesting subset. The premise is that for any given visualization or analysis task, the data subset of interest is much smaller than the larger, complete data set. This strategy---extracting smaller data subsets of interest and focusing of the visualization processing on these subsets---is complementary to the approach of increasing the capacity of the visualization, analysis, and rendering pipelines through parallelism. This report discusses the fundamental concepts in QDV, their relationship to different stages in the visualization and analysis pipelines, and presents QDV's application to problems in diverse areas, ranging from forensic cybersecurity to high energy physics.

Visualizing Series

Science.gov (United States)

Unal, Hasan

2008-01-01

The importance of visualisation and multiple representations in mathematics has been stressed, especially in a context of problem solving. Hanna and Sidoli comment that "Diagrams and other visual representations have long been welcomed as heuristic accompaniments to proof, where they not only facilitate the understanding of theorems and their…

MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

Science.gov (United States)

Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

2016-03-18

Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

VisIO: enabling interactive visualization of ultra-scale, time-series data via high-bandwidth distributed I/O systems

Energy Technology Data Exchange (ETDEWEB)

Mitchell, Christopher J [Los Alamos National Laboratory; Ahrens, James P [Los Alamos National Laboratory; Wang, Jun [UCF

2010-10-15

Petascale simulations compute at resolutions ranging into billions of cells and write terabytes of data for visualization and analysis. Interactive visuaUzation of this time series is a desired step before starting a new run. The I/O subsystem and associated network often are a significant impediment to interactive visualization of time-varying data; as they are not configured or provisioned to provide necessary I/O read rates. In this paper, we propose a new I/O library for visualization applications: VisIO. Visualization applications commonly use N-to-N reads within their parallel enabled readers which provides an incentive for a shared-nothing approach to I/O, similar to other data-intensive approaches such as Hadoop. However, unlike other data-intensive applications, visualization requires: (1) interactive performance for large data volumes, (2) compatibility with MPI and POSIX file system semantics for compatibility with existing infrastructure, and (3) use of existing file formats and their stipulated data partitioning rules. VisIO, provides a mechanism for using a non-POSIX distributed file system to provide linear scaling of 110 bandwidth. In addition, we introduce a novel scheduling algorithm that helps to co-locate visualization processes on nodes with the requested data. Testing using VisIO integrated into Para View was conducted using the Hadoop Distributed File System (HDFS) on TACC's Longhorn cluster. A representative dataset, VPIC, across 128 nodes showed a 64.4% read performance improvement compared to the provided Lustre installation. Also tested, was a dataset representing a global ocean salinity simulation that showed a 51.4% improvement in read performance over Lustre when using our VisIO system. VisIO, provides powerful high-performance I/O services to visualization applications, allowing for interactive performance with ultra-scale, time-series data.

Signs over time: Statistical and visual analysis of a longitudinal signed network

NARCIS (Netherlands)

de Nooy, W.

2008-01-01

This paper presents the design and results of a statistical and visual analysis of a dynamic signed network. In addition to prevalent approaches to longitudinal networks, which analyze series of cross-sectional data, this paper focuses on network data measured in continuous time in order to explain

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Visualization analysis and design

CERN Document Server

Munzner, Tamara

2015-01-01

Visualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques for spatial data, and visual analytics techniques for interweaving data transformation and analysis with interactive visual exploration. It emphasizes the careful validation of effectiveness and the consideration of function before form. The book breaks down visualization design according to three questions: what data users need to see, why users need to carry out their tasks, and how the visual representations proposed can be constructed and manipulated. It walks readers through the use of space and color to visually encode data in a view, the trade-offs between changing a single view and using multiple linked views, and the ways to reduce the amount of data shown in each view. The book concludes with six case stu...

The physiology analysis system: an integrated approach for warehousing, management and analysis of time-series physiology data.

Science.gov (United States)

McKenna, Thomas M; Bawa, Gagandeep; Kumar, Kamal; Reifman, Jaques

2007-04-01

The physiology analysis system (PAS) was developed as a resource to support the efficient warehousing, management, and analysis of physiology data, particularly, continuous time-series data that may be extensive, of variable quality, and distributed across many files. The PAS incorporates time-series data collected by many types of data-acquisition devices, and it is designed to free users from data management burdens. This Web-based system allows both discrete (attribute) and time-series (ordered) data to be manipulated, visualized, and analyzed via a client's Web browser. All processes occur on a server, so that the client does not have to download data or any application programs, and the PAS is independent of the client's computer operating system. The PAS contains a library of functions, written in different computer languages that the client can add to and use to perform specific data operations. Functions from the library are sequentially inserted into a function chain-based logical structure to construct sophisticated data operators from simple function building blocks, affording ad hoc query and analysis of time-series data. These features support advanced mining of physiology data.

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Data and Visualization Corridors: Report on the 1998 DVC Workshop Series

International Nuclear Information System (INIS)

Smith, Paul H.; van Rosendale, John

1998-01-01

The Department of Energy and the National Science Foundation sponsored a series of workshops on data manipulation and visualization of large-scale scientific datasets. Three workshops were held in 1998, bringing together experts in high-performance computing, scientific visualization, emerging computer technologies, physics, chemistry, materials science, and engineering. These workshops were followed by two writing and review sessions, as well as numerous electronic collaborations, to synthesize the results. The results of these efforts are reported here. Across the government, mission agencies are charged with understanding scientific and engineering problems of unprecedented complexity. The DOE Accelerated Strategic Computing Initiative, for example, will soon be faced with the problem of understanding the enormous datasets created by teraops simulations, while NASA already has a severe problem in coping with the flood of data captured by earth observation satellites. Unfortunately, scientific visualization algorithms, and high-performance display hardware and software on which they depend, have not kept pace with the sheer size of emerging datasets, which threaten to overwhelm our ability to conduct research. Our capability to manipulate and explore large datasets is growing only slowly, while human cognitive and visual perception are an absolutely fixed resource. Thus, there is a pressing need for new methods of handling truly massive datasets, of exploring and visualizing them, and of communicating them over geographic distances. This report, written by representatives from academia, industry, national laboratories, and the government, is intended as a first step toward the timely creation of a comprehensive federal program in data manipulation and scientific visualization. There is, at this time, an exciting confluence of ideas on data handling, compression, telepresence, and scientific visualization. The combination of these new ideas, which we refer to as

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

Science.gov (United States)

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

Time Series Analysis and Forecasting by Example

CERN Document Server

Bisgaard, Soren

2011-01-01

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in

SDSS Log Viewer: visual exploratory analysis of large-volume SQL log data

Science.gov (United States)

Zhang, Jian; Chen, Chaomei; Vogeley, Michael S.; Pan, Danny; Thakar, Ani; Raddick, Jordan

2012-01-01

User-generated Structured Query Language (SQL) queries are a rich source of information for database analysts, information scientists, and the end users of databases. In this study a group of scientists in astronomy and computer and information scientists work together to analyze a large volume of SQL log data generated by users of the Sloan Digital Sky Survey (SDSS) data archive in order to better understand users' data seeking behavior. While statistical analysis of such logs is useful at aggregated levels, efficiently exploring specific patterns of queries is often a challenging task due to the typically large volume of the data, multivariate features, and data requirements specified in SQL queries. To enable and facilitate effective and efficient exploration of the SDSS log data, we designed an interactive visualization tool, called the SDSS Log Viewer, which integrates time series visualization, text visualization, and dynamic query techniques. We describe two analysis scenarios of visual exploration of SDSS log data, including understanding unusually high daily query traffic and modeling the types of data seeking behaviors of massive query generators. The two scenarios demonstrate that the SDSS Log Viewer provides a novel and potentially valuable approach to support these targeted tasks.

KfK-seminar series on supercomputing und visualization from May till September 1992

International Nuclear Information System (INIS)

Hohenhinnebusch, W.

1993-05-01

During the period of may 1992 to september 1992 a series of seminars was held at KfK on several topics of supercomputing in different fields of application. The aim was to demonstrate the importance of supercomputing and visualization in numerical simulations of complex physical and technical phenomena. This report contains the collection of all submitted seminar papers. (orig./HP) [de

Clinical evaluation of a novel population-based regression analysis for detecting glaucomatous visual field progression.

Science.gov (United States)

Kovalska, M P; Bürki, E; Schoetzau, A; Orguel, S F; Orguel, S; Grieshaber, M C

2011-04-01

The distinction of real progression from test variability in visual field (VF) series may be based on clinical judgment, on trend analysis based on follow-up of test parameters over time, or on identification of a significant change related to the mean of baseline exams (event analysis). The aim of this study was to compare a new population-based method (Octopus field analysis, OFA) with classic regression analyses and clinical judgment for detecting glaucomatous VF changes. 240 VF series of 240 patients with at least 9 consecutive examinations available were included into this study. They were independently classified by two experienced investigators. The results of such a classification served as a reference for comparison for the following statistical tests: (a) t-test global, (b) r-test global, (c) regression analysis of 10 VF clusters and (d) point-wise linear regression analysis. 32.5 % of the VF series were classified as progressive by the investigators. The sensitivity and specificity were 89.7 % and 92.0 % for r-test, and 73.1 % and 93.8 % for the t-test, respectively. In the point-wise linear regression analysis, the specificity was comparable (89.5 % versus 92 %), but the sensitivity was clearly lower than in the r-test (22.4 % versus 89.7 %) at a significance level of p = 0.01. A regression analysis for the 10 VF clusters showed a markedly higher sensitivity for the r-test (37.7 %) than the t-test (14.1 %) at a similar specificity (88.3 % versus 93.8 %) for a significant trend (p = 0.005). In regard to the cluster distribution, the paracentral clusters and the superior nasal hemifield progressed most frequently. The population-based regression analysis seems to be superior to the trend analysis in detecting VF progression in glaucoma, and may eliminate the drawbacks of the event analysis. Further, it may assist the clinician in the evaluation of VF series and may allow better visualization of the correlation between function and structure owing to VF

Predictive Factors in OCT Analysis for Visual Outcome in Exudative AMD

Directory of Open Access Journals (Sweden)

Maria-Andreea Gamulescu

2012-01-01

Full Text Available Background. Reliable predictive factors for therapy outcome may enable treating physicians to counsel their patients more efficiently concerning probability of improvement or time point of discontinuation of a certain therapy. Methods. This is a retrospective analysis of 87 patients with exudative age-related macular degeneration who received three monthly intravitreal ranibizumab injections. Visual acuity before initiation of intravitreal therapy and 4–6 weeks after last intravitreal injection was compared and related to the preoperative visualisation of continuity of the outer retinal layers as assessed by OCT: external limiting membrane (ELM, inner photoreceptor segments (IPS, junction between inner and outer segments (IS/OS, and outer photoreceptor segments (OPS. Results. Visual acuity increased in 40 of 87 (46.0% patients, it remained stable in 25 (28.7%, and 22 (25.3% patients had decreased visual acuity four to six weeks after triple intravitreal ranibizumab injections. No statistically significant predictive value could be demonstrated for grade of continuity of outer retinal layers concerning visual acuity development. Conclusions. In our series of AMD patients, grade of continuity of outer retinal layers was not a significant predictive value for visual acuity development after triple ranibizumab injections.

EPIPOI: A user-friendly analytical tool for the extraction and visualization of temporal parameters from epidemiological time series

Directory of Open Access Journals (Sweden)

Alonso Wladimir J

2012-11-01

Full Text Available Abstract Background There is an increasing need for processing and understanding relevant information generated by the systematic collection of public health data over time. However, the analysis of those time series usually requires advanced modeling techniques, which are not necessarily mastered by staff, technicians and researchers working on public health and epidemiology. Here a user-friendly tool, EPIPOI, is presented that facilitates the exploration and extraction of parameters describing trends, seasonality and anomalies that characterize epidemiological processes. It also enables the inspection of those parameters across geographic regions. Although the visual exploration and extraction of relevant parameters from time series data is crucial in epidemiological research, until now it had been largely restricted to specialists. Methods EPIPOI is freely available software developed in Matlab (The Mathworks Inc that runs both on PC and Mac computers. Its friendly interface guides users intuitively through useful comparative analyses including the comparison of spatial patterns in temporal parameters. Results EPIPOI is able to handle complex analyses in an accessible way. A prototype has already been used to assist researchers in a variety of contexts from didactic use in public health workshops to the main analytical tool in published research. Conclusions EPIPOI can assist public health officials and students to explore time series data using a broad range of sophisticated analytical and visualization tools. It also provides an analytical environment where even advanced users can benefit by enabling a higher degree of control over model assumptions, such as those associated with detecting disease outbreaks and pandemics.

Highly comparative time-series analysis: the empirical structure of time series and their methods.

Science.gov (United States)

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Modeling, analysis, and visualization of anisotropy

CERN Document Server

Özarslan, Evren; Hotz, Ingrid

2017-01-01

This book focuses on the modeling, processing and visualization of anisotropy, irrespective of the context in which it emerges, using state-of-the-art mathematical tools. As such, it differs substantially from conventional reference works, which are centered on a particular application. It covers the following topics: (i) the geometric structure of tensors, (ii) statistical methods for tensor field processing, (iii) challenges in mapping neural connectivity and structural mechanics, (iv) processing of uncertainty, and (v) visualizing higher-order representations. In addition to original research contributions, it provides insightful reviews. This multidisciplinary book is the sixth in a series that aims to foster scientific exchange between communities employing tensors and other higher-order representations of directionally dependent data. A significant number of the chapters were co-authored by the participants of the workshop titled Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization,...

SPATIOTEMPORAL VISUALIZATION OF TIME-SERIES SATELLITE-DERIVED CO2 FLUX DATA USING VOLUME RENDERING AND GPU-BASED INTERPOLATION ON A CLOUD-DRIVEN DIGITAL EARTH

Directory of Open Access Journals (Sweden)

S. Wu

2017-10-01

Full Text Available The ocean carbon cycle has a significant influence on global climate, and is commonly evaluated using time-series satellite-derived CO2 flux data. Location-aware and globe-based visualization is an important technique for analyzing and presenting the evolution of climate change. To achieve realistic simulation of the spatiotemporal dynamics of ocean carbon, a cloud-driven digital earth platform is developed to support the interactive analysis and display of multi-geospatial data, and an original visualization method based on our digital earth is proposed to demonstrate the spatiotemporal variations of carbon sinks and sources using time-series satellite data. Specifically, a volume rendering technique using half-angle slicing and particle system is implemented to dynamically display the released or absorbed CO2 gas. To enable location-aware visualization within the virtual globe, we present a 3D particlemapping algorithm to render particle-slicing textures onto geospace. In addition, a GPU-based interpolation framework using CUDA during real-time rendering is designed to obtain smooth effects in both spatial and temporal dimensions. To demonstrate the capabilities of the proposed method, a series of satellite data is applied to simulate the air-sea carbon cycle in the China Sea. The results show that the suggested strategies provide realistic simulation effects and acceptable interactive performance on the digital earth.

Visualization of and Software for Omnibus Test Based Change Detected in a Time Series of Polarimetric SAR Data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Conradsen, Knut; Skriver, Henning

2017-01-01

Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution and a factorization of this test statistic with associated p-values, change analysis in a time series of multilook polarimetric SAR data...... in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change occurs. Using airborne EMISAR and spaceborne RADARSAT-2 data this paper focuses on change detection based on the p-values, on visualization of change at pixel as well as segment level......, and on computer software....

Visibility Graph Based Time Series Analysis.

Science.gov (United States)

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Visibility Graph Based Time Series Analysis.

Directory of Open Access Journals (Sweden)

Mutua Stephen

Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

RESEARCH ON THE INTENSITY ANALYSIS AND RESULT VISUALIZATION OF CONSTRUCTION LAND IN URBAN PLANNING

Directory of Open Access Journals (Sweden)

J. Cui

2017-09-01

Full Text Available As a fundamental work of urban planning, the intensity analysis of construction land involves many repetitive data processing works that are prone to cause errors or data precision loss, and the lack of efficient methods and tools to visualizing the analysis results in current urban planning. In the research a portable tool is developed by using the Model Builder technique embedded in ArcGIS to provide automatic data processing and rapid result visualization for the works. A series of basic modules provided by ArcGIS are linked together to shape a whole data processing chain in the tool. Once the required data is imported, the analysis results and related maps and graphs including the intensity values and zoning map, the skyline analysis map etc. are produced automatically. Finally the tool is installation-free and can be dispatched quickly between planning teams.

Interactive Web-based Visualization of Atomic Position-time Series Data

Science.gov (United States)

Thapa, S.; Karki, B. B.

2017-12-01

Extracting and interpreting the information contained in large sets of time-varying three dimensional positional data for the constituent atoms of simulated material is a challenging task. We have recently implemented a web-based visualization system to analyze the position-time series data extracted from the local or remote hosts. It involves a pre-processing step for data reduction, which involves skipping uninteresting parts of the data uniformly (at full atomic configuration level) or non-uniformly (at atomic species level or individual atom level). Atomic configuration snapshot is rendered using the ball-stick representation and can be animated by rendering successive configurations. The entire atomic dynamics can be captured as the trajectories by rendering the atomic positions at all time steps together as points. The trajectories can be manipulated at both species and atomic levels so that we can focus on one or more trajectories of interest, and can be also superimposed with the instantaneous atomic structure. The implementation was done using WebGL and Three.js for graphical rendering, HTML5 and Javascript for GUI, and Elasticsearch and JSON for data storage and retrieval within the Grails Framework. We have applied our visualization system to the simulation datatsets for proton-bearing forsterite (Mg2SiO4) - an abundant mineral of Earths upper mantle. Visualization reveals that protons (hydrogen ions) incorporated as interstitials are much more mobile than protons substituting the host Mg and Si cation sites. The proton diffusion appears to be anisotropic with high mobility along the x-direction, showing limited discrete jumps in other two directions.

Visual Analysis of Air Traffic Data

Science.gov (United States)

Albrecht, George Hans; Pang, Alex

2012-01-01

In this paper, we present visual analysis tools to help study the impact of policy changes on air traffic congestion. The tools support visualization of time-varying air traffic density over an area of interest using different time granularity. We use this visual analysis platform to investigate how changing the aircraft separation volume can reduce congestion while maintaining key safety requirements. The same platform can also be used as a decision aid for processing requests for unmanned aerial vehicle operations.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

Developing a functioning visualization and analysis system for performance assessment

International Nuclear Information System (INIS)

Jones, M.L.

1992-01-01

Various commercial software packages and customized programs provide the ability to analyze and visualize the geology of Yucca Mountain. Starting with sparse, irregularly spaced data a series of gridded models has been developed representing the thermal/mechanical units within the mountain. Using computer aided design (CAD) software and scientific visualization software, the units can be manipulated, analyzed, and graphically displayed. The outputs are typically gridded terrain models, along with files of three-dimensional coordinates, distances, and other dimensional values. Contour maps, profiles, and shaded surfaces are the output for visualization

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions.

Science.gov (United States)

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-09-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.

Interactive Visualization and Analysis of Geospatial Data Sets - TrikeND-iGlobe

Science.gov (United States)

Rosebrock, Uwe; Hogan, Patrick; Chandola, Varun

2013-04-01

The visualization of scientific datasets is becoming an ever-increasing challenge as advances in computing technologies have enabled scientists to build high resolution climate models that have produced petabytes of climate data. To interrogate and analyze these large datasets in real-time is a task that pushes the boundaries of computing hardware and software. But integration of climate datasets with geospatial data requires considerable amount of effort and close familiarity of various data formats and projection systems, which has prevented widespread utilization outside of climate community. TrikeND-iGlobe is a sophisticated software tool that bridges this gap, allows easy integration of climate datasets with geospatial datasets and provides sophisticated visualization and analysis capabilities. The objective for TrikeND-iGlobe is the continued building of an open source 4D virtual globe application using NASA World Wind technology that integrates analysis of climate model outputs with remote sensing observations as well as demographic and environmental data sets. This will facilitate a better understanding of global and regional phenomenon, and the impact analysis of climate extreme events. The critical aim is real-time interactive interrogation. At the data centric level the primary aim is to enable the user to interact with the data in real-time for the purpose of analysis - locally or remotely. TrikeND-iGlobe provides the basis for the incorporation of modular tools that provide extended interactions with the data, including sub-setting, aggregation, re-shaping, time series analysis methods and animation to produce publication-quality imagery. TrikeND-iGlobe may be run locally or can be accessed via a web interface supported by high-performance visualization compute nodes placed close to the data. It supports visualizing heterogeneous data formats: traditional geospatial datasets along with scientific data sets with geographic coordinates (NetCDF, HDF, etc

Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother

On-line analysis of reactor noise using time-series analysis

International Nuclear Information System (INIS)

McGevna, V.G.

1981-10-01

A method to allow use of time series analysis for on-line noise analysis has been developed. On-line analysis of noise in nuclear power reactors has been limited primarily to spectral analysis and related frequency domain techniques. Time series analysis has many distinct advantages over spectral analysis in the automated processing of reactor noise. However, fitting an autoregressive-moving average (ARMA) model to time series data involves non-linear least squares estimation. Unless a high speed, general purpose computer is available, the calculations become too time consuming for on-line applications. To eliminate this problem, a special purpose algorithm was developed for fitting ARMA models. While it is based on a combination of steepest descent and Taylor series linearization, properties of the ARMA model are used so that the auto- and cross-correlation functions can be used to eliminate the need for estimating derivatives. The number of calculations, per iteration varies lineegardless of the mee 0.2% yield strength displayed anisotropy, with axial and circumferential values being greater than radial. For CF8-CPF8 and CF8M-CPF8M castings to meet current ASME Code S acid fuel cells

The foundations of modern time series analysis

CERN Document Server

Mills, Terence C

2011-01-01

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

Visual Analysis of Cloud Computing Performance Using Behavioral Lines.

Science.gov (United States)

Muelder, Chris; Zhu, Biao; Chen, Wei; Zhang, Hongxin; Ma, Kwan-Liu

2016-02-29

Cloud computing is an essential technology to Big Data analytics and services. A cloud computing system is often comprised of a large number of parallel computing and storage devices. Monitoring the usage and performance of such a system is important for efficient operations, maintenance, and security. Tracing every application on a large cloud system is untenable due to scale and privacy issues. But profile data can be collected relatively efficiently by regularly sampling the state of the system, including properties such as CPU load, memory usage, network usage, and others, creating a set of multivariate time series for each system. Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper, we present a visual based analysis approach to understanding and analyzing the performance and behavior of cloud computing systems. Our design is based on similarity measures and a layout method to portray the behavior of each compute node over time. When visualizing a large number of behavioral lines together, distinct patterns often appear suggesting particular types of performance bottleneck. The resulting system provides multiple linked views, which allow the user to interactively explore the data by examining the data or a selected subset at different levels of detail. Our case studies, which use datasets collected from two different cloud systems, show that this visual based approach is effective in identifying trends and anomalies of the systems.

IDP camp evolvement analysis in Darfur using VHSR optical satellite image time series and scientific visualization on virtual globes

Science.gov (United States)

Tiede, Dirk; Lang, Stefan

2010-11-01

In this paper we focus on the application of transferable, object-based image analysis algorithms for dwelling extraction in a camp for internally displaced people (IDP) in Darfur, Sudan along with innovative means for scientific visualisation of the results. Three very high spatial resolution satellite images (QuickBird: 2002, 2004, 2008) were used for: (1) extracting different types of dwellings and (2) calculating and visualizing added-value products such as dwelling density and camp structure. The results were visualized on virtual globes (Google Earth and ArcGIS Explorer) revealing the analysis results (analytical 3D views,) transformed into the third dimension (z-value). Data formats depend on virtual globe software including KML/KMZ (keyhole mark-up language) and ESRI 3D shapefiles streamed as ArcGIS Server-based globe service. In addition, means for improving overall performance of automated dwelling structures using grid computing techniques are discussed using examples from a similar study.

Enabling dynamic network analysis through visualization in TVNViewer

Directory of Open Access Journals (Sweden)

Curtis Ross E

2012-08-01

Full Text Available Abstract Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer, a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

Enabling dynamic network analysis through visualization in TVNViewer

Science.gov (United States)

2012-01-01

Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space. PMID:22897913

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...

Visual modeling in an analysis of multidimensional data

Science.gov (United States)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Metoprolol-induced visual hallucinations: a case series

Directory of Open Access Journals (Sweden)

Goldner Jonathan A

2012-02-01

Full Text Available Abstract Introduction Metoprolol is a widely used beta-adrenergic blocker that is commonly prescribed for a variety of cardiovascular syndromes and conditions. While central nervous system adverse effects have been well-described with most beta-blockers (especially lipophilic agents such as propranolol, visual hallucinations have been only rarely described with metoprolol. Case presentations Case 1 was an 84-year-old Caucasian woman with a history of hypertension and osteoarthritis, who suffered from visual hallucinations which she described as people in her bedroom at night. They would be standing in front of the bed or sitting on chairs watching her when she slept. Numerous medications were stopped before her physician realized the metoprolol was the causative agent. The hallucinations resolved only after discontinuation of this medication. Case 2 was a 62-year-old Caucasian man with an inferior wall myocardial infarction complicated by cardiac arrest, who was successfully resuscitated and discharged from the hospital on metoprolol. About 18 months after discharge, he related to his physician that he had been seeing dead people at night. He related his belief that since he 'had died and was brought back to life', he was now seeing people from the after-life. Upon discontinuation of the metoprolol the visual disturbances resolved within several days. Case 3 was a 68 year-old Caucasian woman with a history of severe hypertension and depression, who reported visual hallucinations at night for years while taking metoprolol. These included awakening during the night with people in her bedroom and seeing objects in her room turn into animals. After a new physician switched her from metoprolol to atenolol, the visual hallucinations ceased within four days. Conclusion We suspect that metoprolol-induced visual hallucinations may be under-recognized and under-reported. Patients may frequently fail to acknowledge this adverse effect believing that they

5D Task Analysis Visualization Tool, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The creation of a five-dimensional task analysis visualization (5D-TAV) software tool for Task Analysis and Workload Planning using multi-dimensional visualization...

Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

Software for hydrogeologic time series analysis, interfacing data with physical insight

NARCIS (Netherlands)

Asmuth, Jos R. von; Maas, K.; Knotters, M.; Bierkens, M.F.P.; Bakker, M.; Olsthoorn, T.; Cirkel, D.; Leunk, I.; Schaars, F.; Asmuth, Daniel C. von

2012-01-01

The program Menyanthes combines a variety of functions for managing, editing, visualizing, analyzing and modeling hydrogeologic time series. Menyanthes was initially developed within the scope of the PhD research of the first author, whose primary aimwas the integration of data and

Infantile nystagmus and visual deprivation

DEFF Research Database (Denmark)

Fledelius, Hans C; Jensen, Hanne

2014-01-01

PURPOSE: To evaluate whether effects of early foveal motor instability due to infantile nystagmus might compare to those of experimental visual deprivation on refraction in a childhood series. METHODS: This was a retrospective analysis of data from the Danish Register for Blind and Weaksighted Ch...

Integrating sentiment analysis and term associations with geo-temporal visualizations on customer feedback streams

Science.gov (United States)

Hao, Ming; Rohrdantz, Christian; Janetzko, Halldór; Keim, Daniel; Dayal, Umeshwar; Haug, Lars-Erik; Hsu, Mei-Chun

2012-01-01

Twitter currently receives over 190 million tweets (small text-based Web posts) and manufacturing companies receive over 10 thousand web product surveys a day, in which people share their thoughts regarding a wide range of products and their features. A large number of tweets and customer surveys include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for determining customer sentiments. To explore high-volume customer feedback streams, we integrate three time series-based visual analysis techniques: (1) feature-based sentiment analysis that extracts, measures, and maps customer feedback; (2) a novel idea of term associations that identify attributes, verbs, and adjectives frequently occurring together; and (3) new pixel cell-based sentiment calendars, geo-temporal map visualizations and self-organizing maps to identify co-occurring and influential opinions. We have combined these techniques into a well-fitted solution for an effective analysis of large customer feedback streams such as for movie reviews (e.g., Kung-Fu Panda) or web surveys (buyers).

Mathematical foundations of time series analysis a concise introduction

CERN Document Server

Beran, Jan

2017-01-01

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

Science.gov (United States)

Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V

2018-04-01

A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.

HEPVIS96 workshop on visualization in high-energy physics. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Taylor, L; Vandoni, C E [eds.

1997-01-29

This report constitutes the formal proceedings of the HEPVIS96 workshop on visualization in high-energy physics, which was held at CERN from 2nd to 4th of September 1996. The workshop, which is in the HEPVVIS series, covered the topics of event visualization, computer graphics technologies and standards, and data analysis and visualization in high-energy physics. (orig.).

HEPVIS96 workshop on visualization in high-energy physics. Proceedings

International Nuclear Information System (INIS)

Taylor, L.; Vandoni, C.E.

1997-01-01

This report constitutes the formal proceedings of the HEPVIS96 workshop on visualization in high-energy physics, which was held at CERN from 2nd to 4th of September 1996. The workshop, which is in the HEPVVIS series, covered the topics of event visualization, computer graphics technologies and standards, and data analysis and visualization in high-energy physics. (orig.)

The Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT): Data Analysis and Visualization for Geoscience Data

Energy Technology Data Exchange (ETDEWEB)

Williams, Dean [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Doutriaux, Charles [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Sean [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Shipman, Galen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Miller, Ross [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Steed, Chad [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Krishnan, Harinarayan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Silva, Claudio [NYU Polytechnic School of Engineering, New York, NY (United States); Chaudhary, Aashish [Kitware, Inc., Clifton Park, NY (United States); Bremer, Peer-Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pugmire, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Childs, Hank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Prabhat, Mr. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States); Bauer, Andrew [Kitware, Inc., Clifton Park, NY (United States); Pletzer, Alexander [Tech-X Corp., Boulder, CO (United States); Poco, Jorge [NYU Polytechnic School of Engineering, New York, NY (United States); Ellqvist, Tommy [NYU Polytechnic School of Engineering, New York, NY (United States); Santos, Emanuele [Federal Univ. of Ceara, Fortaleza (Brazil); Potter, Gerald [NASA Johnson Space Center, Houston, TX (United States); Smith, Brian [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Maxwell, Thomas [NASA Johnson Space Center, Houston, TX (United States); Kindig, David [Tech-X Corp., Boulder, CO (United States); Koop, David [NYU Polytechnic School of Engineering, New York, NY (United States)

2013-05-01

To support interactive visualization and analysis of complex, large-scale climate data sets, UV-CDAT integrates a powerful set of scientific computing libraries and applications to foster more efficient knowledge discovery. Connected through a provenance framework, the UV-CDAT components can be loosely coupled for fast integration or tightly coupled for greater functionality and communication with other components. This framework addresses many challenges in the interactive visual analysis of distributed large-scale data for the climate community.

The analysis of time series: an introduction

National Research Council Canada - National Science Library

Chatfield, Christopher

1989-01-01

.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...

A Hierarchical Visualization Analysis Model of Power Big Data

Science.gov (United States)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

Real-time visualization and analysis of airflow field by use of digital holography

Science.gov (United States)

Di, Jianglei; Wu, Bingjing; Chen, Xin; Liu, Junjiang; Wang, Jun; Zhao, Jianlin

2013-04-01

The measurement and analysis of airflow field is very important in fluid dynamics. For airflow, smoke particles can be added to visually observe the turbulence phenomena by particle tracking technology, but the effect of smoke particles to follow the high speed airflow will reduce the measurement accuracy. In recent years, with the advantage of non-contact, nondestructive, fast and full-field measurement, digital holography has been widely applied in many fields, such as deformation and vibration analysis, particle characterization, refractive index measurement, and so on. In this paper, we present a method to measure the airflow field by use of digital holography. A small wind tunnel model made of acrylic glass is built to control the velocity and direction of airflow. Different shapes of samples such as aircraft wing and cylinder are placed in the wind tunnel model to produce different forms of flow field. With a Mach-Zehnder interferometer setup, a series of digital holograms carrying the information of airflow filed distributions in different states are recorded by CCD camera and corresponding holographic images are numerically reconstructed from the holograms by computer. Then we can conveniently obtain the velocity or pressure information of the airflow deduced from the quantitative phase information of holographic images and visually display the airflow filed and its evolution in the form of a movie. The theory and experiment results show that digital holography is a robust and feasible approach for real-time visualization and analysis of airflow field.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2008-01-01

An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

Topological data analysis for scientific visualization

CERN Document Server

Tierny, Julien

2017-01-01

Combining theoretical and practical aspects of topology, this book delivers a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a thorough but intuitive manner, with many high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in details, and their application is carefully illustrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis, for lecturers, students and researchers.

Development of Visualization Tools for ZPPR-15 Analysis

International Nuclear Information System (INIS)

Lee, Min Jae; Kim, Sang Ji

2014-01-01

ZPPR-15 cores consist of various drawer masters that have great heterogeneity. In order to build a proper homogenization strategy, the geometry of the drawer masters should be carefully analyzed with a visualization. Additionally, a visualization of drawer masters and the core configuration is necessary for minimizing human error during the input processing. For this purpose, visualization tools for a ZPPR-15 analysis has been developed based on a Perl script. In the following section, the implementation of visualization tools will be described and various visualization samples for both drawer masters and ZPPR-15 cores will be demonstrated. Visualization tools for drawer masters and a core configuration were successfully developed for a ZPPR-15 analysis. The visualization tools are expected to be useful for understanding ZPPR-15 experiments, and finding deterministic models of ZPPR-15. It turned out that generating VTK files is handy but the application of VTK files is powerful with the aid of the VISIT program

The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

Directory of Open Access Journals (Sweden)

ZHU Qing

2017-10-01

Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

SUBSURFACE VISUAL ALARM SYSTEM ANALYSIS

International Nuclear Information System (INIS)

D.W. Markman

2001-01-01

The ''Subsurface Fire Hazard Analysis'' (CRWMS M andO 1998, page 61), and the document, ''Title III Evaluation Report for the Surface and Subsurface Communication System'', (CRWMS M andO 1999a, pages 21 and 23), both indicate the installed communication system is adequate to support Exploratory Studies Facility (ESF) activities with the exception of the mine phone system for emergency notification purposes. They recommend the installation of a visual alarm system to supplement the page/party phone system The purpose of this analysis is to identify data communication highway design approaches, and provide justification for the selected or recommended alternatives for the data communication of the subsurface visual alarm system. This analysis is being prepared to document a basis for the design selection of the data communication method. This analysis will briefly describe existing data or voice communication or monitoring systems within the ESF, and look at how these may be revised or adapted to support the needed data highway of the subsurface visual alarm. system. The existing PLC communication system installed in subsurface is providing data communication for alcove No.5 ventilation fans, south portal ventilation fans, bulkhead doors and generator monitoring system. It is given that the data communication of the subsurface visual alarm system will be a digital based system. It is also given that it is most feasible to take advantage of existing systems and equipment and not consider an entirely new data communication system design and installation. The scope and primary objectives of this analysis are to: (1) Briefly review and describe existing available data communication highways or systems within the ESF. (2) Examine technical characteristics of an existing system to disqualify a design alternative is paramount in minimizing the number of and depth of a system review. (3) Apply general engineering design practices or criteria such as relative cost, and degree

Time Series Analysis of Insar Data: Methods and Trends

Science.gov (United States)

Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique

2015-01-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

Science.gov (United States)

Van Norman, Ethan R; Christ, Theodore J

2016-10-01

Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Visualization and Analysis of Complex Covert Networks

DEFF Research Database (Denmark)

Memon, Bisharat

systems that are covert and hence inherently complex. My Ph.D. is positioned within the wider framework of CrimeFighter project. The framework envisions a number of key knowledge management processes that are involved in the workflow, and the toolbox provides supporting tools to assist human end......This report discusses and summarize the results of my work so far in relation to my Ph.D. project entitled "Visualization and Analysis of Complex Covert Networks". The focus of my research is primarily on development of methods and supporting tools for visualization and analysis of networked......-users (intelligence analysts) in harvesting, filtering, storing, managing, structuring, mining, analyzing, interpreting, and visualizing data about offensive networks. The methods and tools proposed and discussed in this work can also be applied to analysis of more generic complex networks....

Visual physics analysis VISPA

International Nuclear Information System (INIS)

Actis, Oxana; Brodski, Michael; Erdmann, Martin; Fischer, Robert; Hinzmann, Andreas; Mueller, Gero; Muenzer, Thomas; Plum, Matthias; Steggemann, Jan; Winchen, Tobias; Klimkovich, Tatsiana

2010-01-01

VISPA is a development environment for high energy physics analyses which enables physicists to combine graphical and textual work. A physics analysis cycle consists of prototyping, performing, and verifying the analysis. The main feature of VISPA is a multipurpose window for visual steering of analysis steps, creation of analysis templates, and browsing physics event data at different steps of an analysis. VISPA follows an experiment-independent approach and incorporates various tools for steering and controlling required in a typical analysis. Connection to different frameworks of high energy physics experiments is achieved by using different types of interfaces. We present the look-and-feel for an example physics analysis at the LHC and explain the underlying software concepts of VISPA.

Glyph-Based Video Visualization for Semen Analysis

KAUST Repository

Duffy, Brian

2015-08-01

© 2013 IEEE. The existing efforts in computer assisted semen analysis have been focused on high speed imaging and automated image analysis of sperm motility. This results in a large amount of data, and it is extremely challenging for both clinical scientists and researchers to interpret, compare and correlate the multidimensional and time-varying measurements captured from video data. In this work, we use glyphs to encode a collection of numerical measurements taken at a regular interval and to summarize spatio-temporal motion characteristics using static visual representations. The design of the glyphs addresses the needs for (a) encoding some 20 variables using separable visual channels, (b) supporting scientific observation of the interrelationships between different measurements and comparison between different sperm cells and their flagella, and (c) facilitating the learning of the encoding scheme by making use of appropriate visual abstractions and metaphors. As a case study, we focus this work on video visualization for computer-aided semen analysis, which has a broad impact on both biological sciences and medical healthcare. We demonstrate that glyph-based visualization can serve as a means of external memorization of video data as well as an overview of a large set of spatiotemporal measurements. It enables domain scientists to make scientific observation in a cost-effective manner by reducing the burden of viewing videos repeatedly, while providing them with a new visual representation for conveying semen statistics.

Visualization and Data Analysis for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

Automated Box-Cox Transformations for Improved Visual Encoding.

Science.gov (United States)

Maciejewski, Ross; Pattath, Avin; Ko, Sungahn; Hafen, Ryan; Cleveland, William S; Ebert, David S

2013-01-01

The concept of preconditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assumptions of statistical inference procedures, as well as making the data more symmetric and easier to visualize and interpret. In this paper, we explore the use of the Box-Cox family of power transformations to semiautomatically adjust visual parameters. We focus on time-series scaling, axis transformations, and color binning for choropleth maps. We illustrate the usage of this transformation through various examples, and discuss the value and some issues in semiautomatically using these transformations for more effective data visualization.

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

Energy Technology Data Exchange (ETDEWEB)

Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Silva, Claudio [New York Univ. (NYU), NY (United States). Computer Science and Engineering Dept.

2013-09-30

For the past three years, a large analysis and visualization effort—funded by the Department of Energy’s Office of Biological and Environmental Research (BER), the National Aeronautics and Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA)—has brought together a wide variety of industry-standard scientific computing libraries and applications to create Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) to serve the global climate simulation and observational research communities. To support interactive analysis and visualization, all components connect through a provenance application–programming interface to capture meaningful history and workflow. Components can be loosely coupled into the framework for fast integration or tightly coupled for greater system functionality and communication with other components. The overarching goal of UV-CDAT is to provide a new paradigm for access to and analysis of massive, distributed scientific data collections by leveraging distributed data architectures located throughout the world. The UV-CDAT framework addresses challenges in analysis and visualization and incorporates new opportunities, including parallelism for better efficiency, higher speed, and more accurate scientific inferences. Today, it provides more than 600 users access to more analysis and visualization products than any other single source.

Relating interesting quantitative time series patterns with text events and text features

Science.gov (United States)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other

Evaluation of Visual Field Progression in Glaucoma: Quasar Regression Program and Event Analysis.

Science.gov (United States)

Díaz-Alemán, Valentín T; González-Hernández, Marta; Perera-Sanz, Daniel; Armas-Domínguez, Karintia

2016-01-01

To determine the sensitivity, specificity and agreement between the Quasar program, glaucoma progression analysis (GPA II) event analysis and expert opinion in the detection of glaucomatous progression. The Quasar program is based on linear regression analysis of both mean defect (MD) and pattern standard deviation (PSD). Each series of visual fields was evaluated by three methods; Quasar, GPA II and four experts. The sensitivity, specificity and agreement (kappa) for each method was calculated, using expert opinion as the reference standard. The study included 439 SITA Standard visual fields of 56 eyes of 42 patients, with a mean of 7.8 ± 0.8 visual fields per eye. When suspected cases of progression were considered stable, sensitivity and specificity of Quasar, GPA II and the experts were 86.6% and 70.7%, 26.6% and 95.1%, and 86.6% and 92.6% respectively. When suspected cases of progression were considered as progressing, sensitivity and specificity of Quasar, GPA II and the experts were 79.1% and 81.2%, 45.8% and 90.6%, and 85.4% and 90.6% respectively. The agreement between Quasar and GPA II when suspected cases were considered stable or progressing was 0.03 and 0.28 respectively. The degree of agreement between Quasar and the experts when suspected cases were considered stable or progressing was 0.472 and 0.507. The degree of agreement between GPA II and the experts when suspected cases were considered stable or progressing was 0.262 and 0.342. The combination of MD and PSD regression analysis in the Quasar program showed better agreement with the experts and higher sensitivity than GPA II.

A Fresh Look at Spatio-Temporal Remote Sensing Data: Data Formats, Processing Flow, and Visualization

Science.gov (United States)

Gens, R.

2017-12-01

With increasing number of experimental and operational satellites in orbit, remote sensing based mapping and monitoring of the dynamic Earth has entered into the realm of `big data'. Just the Landsat series of satellites provide a near continuous archive of 45 years of data. The availability of such spatio-temporal datasets has created opportunities for long-term monitoring diverse features and processes operating on the Earth's terrestrial and aquatic systems. Processes such as erosion, deposition, subsidence, uplift, evapotranspiration, urbanization, land-cover regime shifts can not only be monitored and change can be quantified using time-series data analysis. This unique opportunity comes with new challenges in management, analysis, and visualization of spatio-temporal datasets. Data need to be stored in a user-friendly format, and relevant metadata needs to be recorded, to allow maximum flexibility for data exchange and use. Specific data processing workflows need to be defined to support time-series analysis for specific applications. Value-added data products need to be generated keeping in mind the needs of the end-users, and using best practices in complex data visualization. This presentation systematically highlights the various steps for preparing spatio-temporal remote sensing data for time series analysis. It showcases a prototype workflow for remote sensing based change detection that can be generically applied while preserving the application-specific fidelity of the datasets. The prototype includes strategies for visualizing change over time. This has been exemplified using a time-series of optical and SAR images for visualizing the changing glacial, coastal, and wetland landscapes in parts of Alaska.

Nonlinear time series analysis of the human electrocardiogram

International Nuclear Information System (INIS)

Perc, Matjaz

2005-01-01

We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method

BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data

Directory of Open Access Journals (Sweden)

Madeira Sara C

2009-07-01

Full Text Available Abstract Background The ability to monitor changes in expression patterns over time, and to observe the emergence of coherent temporal responses using expression time series, is critical to advance our understanding of complex biological processes. Biclustering has been recognized as an effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms. The general biclustering problem is NP-hard. In the case of time series this problem is tractable, and efficient algorithms can be used. However, there is still a need for specialized applications able to take advantage of the temporal properties inherent to expression time series, both from a computational and a biological perspective. Findings BiGGEsTS makes available state-of-the-art biclustering algorithms for analyzing expression time series. Gene Ontology (GO annotations are used to assess the biological relevance of the biclusters. Methods for preprocessing expression time series and post-processing results are also included. The analysis is additionally supported by a visualization module capable of displaying informative representations of the data, including heatmaps, dendrograms, expression charts and graphs of enriched GO terms. Conclusion BiGGEsTS is a free open source graphical software tool for revealing local coexpression of genes in specific intervals of time, while integrating meaningful information on gene annotations. It is freely available at: http://kdbio.inesc-id.pt/software/biggests. We present a case study on the discovery of transcriptional regulatory modules in the response of Saccharomyces cerevisiae to heat stress.

SVIP-N 1.0: An integrated visualization platform for neutronics analysis

International Nuclear Information System (INIS)

Luo Yuetong; Long Pengcheng; Wu Guoyong; Zeng Qin; Hu Liqin; Zou Jun

2010-01-01

Post-processing is an important part of neutronics analysis, and SVIP-N 1.0 (scientific visualization integrated platform for neutronics analysis) is designed to ease post-processing of neutronics analysis through visualization technologies. Main capabilities of SVIP-N 1.0 include: (1) ability of manage neutronics analysis result; (2) ability to preprocess neutronics analysis result; (3) ability to visualization neutronics analysis result data in different way. The paper describes the system architecture and main features of SVIP-N, some advanced visualization used in SVIP-N 1.0 and some preliminary applications, such as ITER.

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

Visual interface for space and terrestrial analysis

Science.gov (United States)

Dombrowski, Edmund G.; Williams, Jason R.; George, Arthur A.; Heckathorn, Harry M.; Snyder, William A.

1995-01-01

The management of large geophysical and celestial data bases is now, more than ever, the most critical path to timely data analysis. With today's large volume data sets from multiple satellite missions, analysts face the task of defining useful data bases from which data and metadata (information about data) can be extracted readily in a meaningful way. Visualization, following an object-oriented design, is a fundamental method of organizing and handling data. Humans, by nature, easily accept pictorial representations of data. Therefore graphically oriented user interfaces are appealing, as long as they remain simple to produce and use. The Visual Interface for Space and Terrestrial Analysis (VISTA) system, currently under development at the Naval Research Laboratory's Backgrounds Data Center (BDC), has been designed with these goals in mind. Its graphical user interface (GUI) allows the user to perform queries, visualization, and analysis of atmospheric and celestial backgrounds data.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Interactive Correlation Analysis and Visualization of Climate Data

Energy Technology Data Exchange (ETDEWEB)

Ma, Kwan-Liu [Univ. of California, Davis, CA (United States)

2016-09-21

The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.

Analysis of series resonant converter with series-parallel connection

Science.gov (United States)

Lin, Bor-Ren; Huang, Chien-Lan

2011-02-01

In this study, a parallel inductor-inductor-capacitor (LLC) resonant converter series-connected on the primary side and parallel-connected on the secondary side is presented for server power supply systems. Based on series resonant behaviour, the power metal-oxide-semiconductor field-effect transistors are turned on at zero voltage switching and the rectifier diodes are turned off at zero current switching. Thus, the switching losses on the power semiconductors are reduced. In the proposed converter, the primary windings of the two LLC converters are connected in series. Thus, the two converters have the same primary currents to ensure that they can supply the balance load current. On the output side, two LLC converters are connected in parallel to share the load current and to reduce the current stress on the secondary windings and the rectifier diodes. In this article, the principle of operation, steady-state analysis and design considerations of the proposed converter are provided and discussed. Experiments with a laboratory prototype with a 24 V/21 A output for server power supply were performed to verify the effectiveness of the proposed converter.

Nonlinear time series analysis with R

CERN Document Server

Huffaker, Ray; Rosa, Rodolfo

2017-01-01

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...

Sustainability of Italian budgetary policies: a time series analysis (1862-2013

Directory of Open Access Journals (Sweden)

Gordon L. Brady

2017-12-01

Full Text Available In this paper, we analyze the sustainability of Italian public finances using a unique database covering the period 1862-2013. This paper focuses on empirical tests for the sustainability and solvency of fiscal policies. A necessary but not sufficient condition implies that the growth rate of public debt should in the limit be smaller than the asymptotic rate of interest. In addition, the debt-to-GDP ratio must eventually stabilize at a steady-state level. The results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1. However, some breaks in the series emerge, given internal and external crises (wars, oil shocks, regime changes, institutional reforms. Therefore, the empirical analysis is conducted for the entire period, as well as two sub‐periods (1862‐1913 and 1947‐2013. Moreover, anecdotal evidence and visual inspection of the series confirm our results. Furthermore, we conduct tests on cointegration, which evidence that a long-run relationship between public expenditure and revenues is found only for the first sub-period (1862-1913. In essence, the paper’s results reveal that Italy have sustainability problems in the Republican age.

Exclusively visual analysis of classroom group interactions

Science.gov (United States)

Tucker, Laura; Scherr, Rachel E.; Zickler, Todd; Mazur, Eric

2016-12-01

Large-scale audiovisual data that measure group learning are time consuming to collect and analyze. As an initial step towards scaling qualitative classroom observation, we qualitatively coded classroom video using an established coding scheme with and without its audio cues. We find that interrater reliability is as high when using visual data only—without audio—as when using both visual and audio data to code. Also, interrater reliability is high when comparing use of visual and audio data to visual-only data. We see a small bias to code interactions as group discussion when visual and audio data are used compared with video-only data. This work establishes that meaningful educational observation can be made through visual information alone. Further, it suggests that after initial work to create a coding scheme and validate it in each environment, computer-automated visual coding could drastically increase the breadth of qualitative studies and allow for meaningful educational analysis on a far greater scale.

Exclusively visual analysis of classroom group interactions

Directory of Open Access Journals (Sweden)

Laura Tucker

2016-11-01

Full Text Available Large-scale audiovisual data that measure group learning are time consuming to collect and analyze. As an initial step towards scaling qualitative classroom observation, we qualitatively coded classroom video using an established coding scheme with and without its audio cues. We find that interrater reliability is as high when using visual data only—without audio—as when using both visual and audio data to code. Also, interrater reliability is high when comparing use of visual and audio data to visual-only data. We see a small bias to code interactions as group discussion when visual and audio data are used compared with video-only data. This work establishes that meaningful educational observation can be made through visual information alone. Further, it suggests that after initial work to create a coding scheme and validate it in each environment, computer-automated visual coding could drastically increase the breadth of qualitative studies and allow for meaningful educational analysis on a far greater scale.

Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

Time-Series Analysis: A Cautionary Tale

Science.gov (United States)

Damadeo, Robert

2015-01-01

Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

DIY Solar Market Analysis Webinar Series: Solar Resource and Technical

Science.gov (United States)

Series: Solar Resource and Technical Potential DIY Solar Market Analysis Webinar Series: Solar Resource and Technical Potential Wednesday, June 11, 2014 As part of a Do-It-Yourself Solar Market Analysis Potential | State, Local, and Tribal Governments | NREL DIY Solar Market Analysis Webinar

Allan deviation analysis of financial return series

Science.gov (United States)

Hernández-Pérez, R.

2012-05-01

We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.

Software for Graph Analysis and Visualization

Directory of Open Access Journals (Sweden)

M. I. Kolomeychenko

2014-01-01

Full Text Available This paper describes the software for graph storage, analysis and visualization. The article presents a comparative analysis of existing software for analysis and visualization of graphs, describes the overall architecture of application and basic principles of construction and operation of the main modules. Furthermore, a description of the developed graph storage oriented to storage and processing of large-scale graphs is presented. The developed algorithm for finding communities and implemented algorithms of autolayouts of graphs are the main functionality of the product. The main advantage of the developed software is high speed processing of large size networks (up to millions of nodes and links. Moreover, the proposed graph storage architecture is unique and has no analogues. The developed approaches and algorithms are optimized for operating with big graphs and have high productivity.

Visual Analysis of Inclusion Dynamics in Two-Phase Flow.

Science.gov (United States)

Karch, Grzegorz Karol; Beck, Fabian; Ertl, Moritz; Meister, Christian; Schulte, Kathrin; Weigand, Bernhard; Ertl, Thomas; Sadlo, Filip

2018-05-01

In single-phase flow visualization, research focuses on the analysis of vector field properties. In two-phase flow, in contrast, analysis of the phase components is typically of major interest. So far, visualization research of two-phase flow concentrated on proper interface reconstruction and the analysis thereof. In this paper, we present a novel visualization technique that enables the investigation of complex two-phase flow phenomena with respect to the physics of breakup and coalescence of inclusions. On the one hand, we adapt dimensionless quantities for a localized analysis of phase instability and breakup, and provide detailed inspection of breakup dynamics with emphasis on oscillation and its interplay with rotational motion. On the other hand, we present a parametric tightly linked space-time visualization approach for an effective interactive representation of the overall dynamics. We demonstrate the utility of our approach using several two-phase CFD datasets.

Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

Interactive Visual Analysis for Organic Photovoltaic Solar Cells

KAUST Repository

Abouelhassan, Amal A.

2017-12-05

Organic Photovoltaic (OPV) solar cells provide a promising alternative for harnessing solar energy. However, the efficient design of OPV materials that achieve better performance requires support by better-tailored visualization tools than are currently available, which is the goal of this thesis. One promising approach in the OPV field is to control the effective material of the OPV device, which is known as the Bulk-Heterojunction (BHJ) morphology. The BHJ morphology has a complex composition. Current BHJ exploration techniques deal with the morphologies as black boxes with no perception of the photoelectric current in the BHJ morphology. Therefore, this method depends on a trial-and-error approach and does not efficiently characterize complex BHJ morphologies. On the other hand, current state-of-the-art methods for assessing the performance of BHJ morphologies are based on the global quantification of morphological features. Accordingly, scientists in OPV research are still lacking a sufficient understanding of the best material design. To remove these limitations, we propose a new approach for knowledge-assisted visual exploration and analysis in the OPV domain. We develop new techniques for enabling efficient OPV charge transport path analysis. We employ, adapt, and develop techniques from scientific visualization, geometric modeling, clustering, and visual interaction to obtain new designs of visualization tools that are specifically tailored for the needs of OPV scientists. At the molecular scale, the user can use semantic rules to define clusters of atoms with certain geometric properties. At the nanoscale, we propose a novel framework for visual characterization and exploration of local structure-performance correlations. We also propose a new approach for correlating structural features to performance bottlenecks. We employ a visual feedback strategy that allows scientists to make intuitive choices about fabrication parameters. We furthermore propose a

The Statistical Analysis of Time Series

CERN Document Server

Anderson, T W

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

5D Task Analysis Visualization Tool Phase II, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The creation of a five-dimensional task analysis visualization (5D-TAV) software tool for Task Analysis and Workload Planning using multi-dimensional visualization...

Visual coherence for large-scale line-plot visualizations

KAUST Repository

Muigg, Philipp

2011-06-01

Displaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2x2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method. © 2011 The Author(s).

Visual coherence for large-scale line-plot visualizations

KAUST Repository

Muigg, Philipp; Hadwiger, Markus; Doleisch, Helmut; Grö ller, Eduard M.

2011-01-01

Displaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2x2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method. © 2011 The Author(s).

Research on Visual Analysis Methods of Terrorism Events

Science.gov (United States)

Guo, Wenyue; Liu, Haiyan; Yu, Anzhu; Li, Jing

2016-06-01

Under the situation that terrorism events occur more and more frequency throughout the world, improving the response capability of social security incidents has become an important aspect to test governments govern ability. Visual analysis has become an important method of event analysing for its advantage of intuitive and effective. To analyse events' spatio-temporal distribution characteristics, correlations among event items and the development trend, terrorism event's spatio-temporal characteristics are discussed. Suitable event data table structure based on "5W" theory is designed. Then, six types of visual analysis are purposed, and how to use thematic map and statistical charts to realize visual analysis on terrorism events is studied. Finally, experiments have been carried out by using the data provided by Global Terrorism Database, and the results of experiments proves the availability of the methods.

Data-driven security analysis, visualization and dashboards

CERN Document Server

Jacobs, Jay

2014-01-01

Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and ma

Learning Visualizations by Analogy: Promoting Visual Literacy through Visualization Morphing.

Science.gov (United States)

Ruchikachorn, Puripant; Mueller, Klaus

2015-09-01

We propose the concept of teaching (and learning) unfamiliar visualizations by analogy, that is, demonstrating an unfamiliar visualization method by linking it to another more familiar one, where the in-betweens are designed to bridge the gap of these two visualizations and explain the difference in a gradual manner. As opposed to a textual description, our morphing explains an unfamiliar visualization through purely visual means. We demonstrate our idea by ways of four visualization pair examples: data table and parallel coordinates, scatterplot matrix and hyperbox, linear chart and spiral chart, and hierarchical pie chart and treemap. The analogy is commutative i.e. any member of the pair can be the unfamiliar visualization. A series of studies showed that this new paradigm can be an effective teaching tool. The participants could understand the unfamiliar visualization methods in all of the four pairs either fully or at least significantly better after they observed or interacted with the transitions from the familiar counterpart. The four examples suggest how helpful visualization pairings be identified and they will hopefully inspire other visualization morphings and associated transition strategies to be identified.

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

Science.gov (United States)

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Science.gov (United States)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2011-01-01

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Computerized diagnostic data analysis and 3-D visualization

International Nuclear Information System (INIS)

Schuhmann, D.; Haubner, M.; Krapichler, C.; Englmeier, K.H.; Seemann, M.; Schoepf, U.J.; Gebicke, K.; Reiser, M.

1998-01-01

Purpose: To survey methods for 3D data visualization and image analysis which can be used for computer based diagnostics. Material and methods: The methods available are explained in short terms and links to the literature are presented. Methods which allow basic manipulation of 3D data are windowing, rotation and clipping. More complex methods for visualization of 3D data are multiplanar reformation, volume projections (MIP, semi-transparent projections) and surface projections. Methods for image analysis comprise local data transformation (e.g. filtering) and definition and application of complex models (e.g. deformable models). Results: Volume projections produce an impression of the 3D data set without reducing the data amount. This supports the interpretation of the 3D data set and saves time in comparison to any investigation which requires examination of all slice images. More advanced techniques for visualization, e.g. surface projections and hybrid rendering visualize anatomical information to a very detailed extent, but both techniques require the segmentation of the structures of interest. Image analysis methods can be used to extract these structures (e.g. an organ) from the image data. Discussion: At the present time volume projections are robust and fast enough to be used routinely. Surface projections can be used to visualize complex and presegmented anatomical features. (orig.) [de

Stochastic time series analysis of hydrology data for water resources

Science.gov (United States)

Sathish, S.; Khadar Babu, S. K.

2017-11-01

The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.

FluxVisualizer, a Software to Visualize Fluxes through Metabolic Networks

Directory of Open Access Journals (Sweden)

Tim Daniel Rose

2018-04-01

Full Text Available FluxVisualizer (Version 1.0, 2017, freely available at https://fluxvisualizer.ibgc.cnrs.fr is a software to visualize fluxes values on a scalable vector graphic (SVG representation of a metabolic network by colouring or increasing the width of reaction arrows of the SVG file. FluxVisualizer does not aim to draw metabolic networks but to use a customer’s SVG file allowing him to exploit his representation standards with a minimum of constraints. FluxVisualizer is especially suitable for small to medium size metabolic networks, where a visual representation of the fluxes makes sense. The flux distribution can either be an elementary flux mode (EFM, a flux balance analysis (FBA result or any other flux distribution. It allows the automatic visualization of a series of pathways of the same network as is needed for a set of EFMs. The software is coded in python3 and provides a graphical user interface (GUI and an application programming interface (API. All functionalities of the program can be used from the API and the GUI and allows advanced users to add their own functionalities. The software is able to work with various formats of flux distributions (Metatool, CellNetAnalyzer, COPASI and FAME export files as well as with Excel files. This simple software can save a lot of time when evaluating fluxes simulations on a metabolic network.

Spatial analysis statistics, visualization, and computational methods

CERN Document Server

Oyana, Tonny J

2015-01-01

An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...

Efficient Delivery and Visualization of Long Time-Series Datasets Using Das2 Tools

Science.gov (United States)

Piker, C.; Granroth, L.; Faden, J.; Kurth, W. S.

2017-12-01

For over 14 years the University of Iowa Radio and Plasma Wave Group has utilized a network transparent data streaming and visualization system for most daily data review and collaboration activities. This system, called Das2, was originally designed in support of the Cassini Radio and Plasma Wave Science (RPWS) investigation, but is now relied on for daily review and analysis of Voyager, Polar, Cluster, Mars Express, Juno and other mission results. In light of current efforts to promote automatic data distribution in space physics it seems prudent to provide an overview of our open source Das2 programs and interface definitions to the wider community and to recount lessons learned. This submission will provide an overview of interfaces that define the system, describe the relationship between the Das2 effort and Autoplot and will examine handling Cassini RPWS Wideband waveforms and dynamic spectra as examples of dealing with long time-series data sets. In addition, the advantages and limitations of the current Das2 tool set will be discussed, as well as lessons learned that are applicable to other data sharing initiatives. Finally, plans for future developments including improved catalogs to support 'no-software' data sources and redundant multi-server fail over, as well as new adapters for CSV (Comma Separated Values) and JSON (Javascript Object Notation) output to support Cassini closeout and the HAPI (Heliophysics Application Programming Interface) initiative are outlined.

Interactive Visual Analysis within Dynamic Ocean Models

Science.gov (United States)

Butkiewicz, T.

2012-12-01

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Science.gov (United States)

Maxwell, Thomas

2012-01-01

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

Science.gov (United States)

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

In situ visualization and data analysis for turbidity currents simulation

Science.gov (United States)

Camata, Jose J.; Silva, Vítor; Valduriez, Patrick; Mattoso, Marta; Coutinho, Alvaro L. G. A.

2018-01-01

Turbidity currents are underflows responsible for sediment deposits that generate geological formations of interest for the oil and gas industry. LibMesh-sedimentation is an application built upon the libMesh library to simulate turbidity currents. In this work, we present the integration of libMesh-sedimentation with in situ visualization and in transit data analysis tools. DfAnalyzer is a solution based on provenance data to extract and relate strategic simulation data in transit from multiple data for online queries. We integrate libMesh-sedimentation and ParaView Catalyst to perform in situ data analysis and visualization. We present a parallel performance analysis for two turbidity currents simulations showing that the overhead for both in situ visualization and in transit data analysis is negligible. We show that our tools enable monitoring the sediments appearance at runtime and steer the simulation based on the solver convergence and visual information on the sediment deposits, thus enhancing the analytical power of turbidity currents simulations.

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

Science.gov (United States)

Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

2012-07-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

Low-rank and sparse modeling for visual analysis

CERN Document Server

Fu, Yun

2014-01-01

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applic

Avogadro: an advanced semantic chemical editor, visualization, and analysis platform.

Science.gov (United States)

Hanwell, Marcus D; Curtis, Donald E; Lonie, David C; Vandermeersch, Tim; Zurek, Eva; Hutchison, Geoffrey R

2012-08-13

The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful

Avogadro: an advanced semantic chemical editor, visualization, and analysis platform

Directory of Open Access Journals (Sweden)

Hanwell Marcus D

2012-08-01

Full Text Available Abstract Background The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. Results The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Conclusions Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format

Metagenomics meets time series analysis: unraveling microbial community dynamics

NARCIS (Netherlands)

Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.

2015-01-01

The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic

Analysis and visualization of animal movement

NARCIS (Netherlands)

Shamoun-Baranes, J.; van Loon, E.E.; Purves, R.S.; Speckmann, B.; Weiskopf, D.; Camphuysen, C.J.

2012-01-01

The interdisciplinary workshop ‘Analysis and Visualization of Moving Objects’ was held at the Lorentz Centre in Leiden, The Netherlands, from 27 June to 1 July 2011. It brought together international specialists from ecology, computer science and geographical information science actively involved in

Equipment of visualization environment of a large-scale structural analysis system. Visualization using AVS/Express of an ADVENTURE system

International Nuclear Information System (INIS)

Miyazaki, Mikiya

2004-02-01

The data display work of visualization is done in many research fields, and a lot of special softwares for the specific purposes exist today. But such softwares have an interface to only a small number of solvers. In many simulations, data conversion for visualization software is required between analysis and visualization for the practical use. This report describes the equipment work of the data visualization environment where AVS/Express was installed in corresponding to many requests from the users of the large-scale structural analysis system which is prepared as an ITBL community software. This environment enables to use the ITBL visualization server as a visualization device after the computation on the ITBL computer. Moreover, a lot of use will be expected within the community in the ITBL environment by merging it into ITBL/AVS environment in the future. (author)

Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool

International Nuclear Information System (INIS)

Stukowski, Alexander

2010-01-01

The Open Visualization Tool (OVITO) is a new 3D visualization software designed for post-processing atomistic data obtained from molecular dynamics or Monte Carlo simulations. Unique analysis, editing and animations functions are integrated into its easy-to-use graphical user interface. The software is written in object-oriented C++, controllable via Python scripts and easily extendable through a plug-in interface. It is distributed as open-source software and can be downloaded from the website http://ovito.sourceforge.net/

Applied time series analysis and innovative computing

CERN Document Server

Ao, Sio-Iong

2010-01-01

This text is a systematic, state-of-the-art introduction to the use of innovative computing paradigms as an investigative tool for applications in time series analysis. It includes frontier case studies based on recent research.

Multiresolution analysis of Bursa Malaysia KLCI time series

Science.gov (United States)

Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

2017-05-01

In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

Toward a Shared Vocabulary for Visual Analysis: An Analytic Toolkit for Deconstructing the Visual Design of Graphic Novels

Science.gov (United States)

Connors, Sean P.

2012-01-01

Literacy educators might advocate using graphic novels to develop students' visual literacy skills, but teachers who lack a vocabulary for engaging in close analysis of visual texts may be reluctant to teach them. Recognizing this, teacher educators should equip preservice teachers with a vocabulary for analyzing visual texts. This article…

Production design and location in the Danish television drama series Arvingerne

DEFF Research Database (Denmark)

Ion Wille, Jakob; Waade, Anne Marit

2016-01-01

Television fiction is most often referred to as the writer’s medium, whereas feature film is generally perceived as the vision and work of the director. In this article we turn our focus to the role and function of the production design and locations in developing and conceptualising a television...... drama series. We use the drama series Arvingerne (The Legacy, DR, 2014-2015) to illustrate how design ideas can be developed at an early stage, in pre-pre-production, as part of a collective, creative process that includes the scriptwriter, the production designer and the producer. Our empirical study...... of the series draws on an analysis of in-house design/concept documents [1], interviews with the production designer Mia Stensgaard [2], and promotional material made for the series [3]. The paper also draws on visual analysis of the finished production. Our overall argument is that the importance of location...

The singular nature of auditory and visual scene analysis in autism.

Science.gov (United States)

Lin, I-Fan; Shirama, Aya; Kato, Nobumasa; Kashino, Makio

2017-02-19

Individuals with autism spectrum disorder often have difficulty acquiring relevant auditory and visual information in daily environments, despite not being diagnosed as hearing impaired or having low vision. Resent psychophysical and neurophysiological studies have shown that autistic individuals have highly specific individual differences at various levels of information processing, including feature extraction, automatic grouping and top-down modulation in auditory and visual scene analysis. Comparison of the characteristics of scene analysis between auditory and visual modalities reveals some essential commonalities, which could provide clues about the underlying neural mechanisms. Further progress in this line of research may suggest effective methods for diagnosing and supporting autistic individuals.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Author(s).

Fourier analysis of time series an introduction

CERN Document Server

Bloomfield, Peter

2000-01-01

A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample

A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems

Directory of Open Access Journals (Sweden)

Takanori Fujiwara

2018-03-01

Full Text Available The overall efficiency of an extreme-scale supercomputer largely relies on the performance of its network interconnects. Several of the state of the art supercomputers use networks based on the increasingly popular Dragonfly topology. It is crucial to study the behavior and performance of different parallel applications running on Dragonfly networks in order to make optimal system configurations and design choices, such as job scheduling and routing strategies. However, in order to study these temporal network behavior, we would need a tool to analyze and correlate numerous sets of multivariate time-series data collected from the Dragonfly’s multi-level hierarchies. This paper presents such a tool–a visual analytics system–that uses the Dragonfly network to investigate the temporal behavior and optimize the communication performance of a supercomputer. We coupled interactive visualization with time-series analysis methods to help reveal hidden patterns in the network behavior with respect to different parallel applications and system configurations. Our system also provides multiple coordinated views for connecting behaviors observed at different levels of the network hierarchies, which effectively helps visual analysis tasks. We demonstrate the effectiveness of the system with a set of case studies. Our system and findings can not only help improve the communication performance of supercomputing applications, but also the network performance of next-generation supercomputers. Keywords: Supercomputing, Parallel communication network, Dragonfly networks, Time-series data, Performance analysis, Visual analytics

PyPathway: Python Package for Biological Network Analysis and Visualization.

Science.gov (United States)

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

Time series analysis of ozone data in Isfahan

Science.gov (United States)

Omidvari, M.; Hassanzadeh, S.; Hosseinibalam, F.

2008-07-01

Time series analysis used to investigate the stratospheric ozone formation and decomposition processes. Different time series methods are applied to detect the reason for extreme high ozone concentrations for each season. Data was convert into seasonal component and frequency domain, the latter has been evaluated by using the Fast Fourier Transform (FFT), spectral analysis. The power density spectrum estimated from the ozone data showed peaks at cycle duration of 22, 20, 36, 186, 365 and 40 days. According to seasonal component analysis most fluctuation was in 1999 and 2000, but the least fluctuation was in 2003. The best correlation between ozone and sun radiation was found in 2000. Other variables which are not available cause to this fluctuation in the 1999 and 2001. The trend of ozone is increasing in 1999 and is decreasing in other years.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

Science.gov (United States)

Nguyen, Hien D; Ullmann, Jeremy F P; McLachlan, Geoffrey J; Voleti, Venkatakaushik; Li, Wenze; Hillman, Elizabeth M C; Reutens, David C; Janke, Andrew L

2018-02-01

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

Educating "The Simpsons": Teaching Queer Representations in Contemporary Visual Media

Science.gov (United States)

Padva, Gilad

2008-01-01

This article analyzes queer representation in contemporary visual media and examines how the episode "Homer's Phobia" from Matt Groening's animation series "The Simpsons" can be used to deconstruct hetero- and homo-sexual codes of behavior, socialization, articulation, representation and visibility. The analysis is contextualized in the…

Multivariate time series analysis with R and financial applications

CERN Document Server

Tsay, Ruey S

2013-01-01

Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl

Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

Science.gov (United States)

Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

2018-05-01

Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

Multimodal genres in textbooks: are students being schooled for visual literacy?

Directory of Open Access Journals (Sweden)

Cláudia Graziano Paes de Barros

2012-11-01

Full Text Available In this paper, we discuss some issues involved in teaching and learning reading, especially schooling in visual literacy. We seek to observe the work developed with genres that combine verbal and visual languages, found in the reading activities of two high school textbook series for Portuguese language teaching. Our goal was to understand to what extent these activities contribute towards the development of reading skills needed to deal with the specificities of these genres. Therefore, we used the enunciative and discursive assumptions of the socio-historical approach of Bakhtin Circle, as well as the Social Semiotics perspective to understand multimodality. Data analysis revealed that the incidence of multimodal genres studied in the two textbook series is hardly representative. The didactic treatment these genres receive in reading activities does not favor the mobilization of specific reading skills and contributes little to students‟ visual literacy schooling.

Time series analysis methods and applications for flight data

CERN Document Server

Zhang, Jianye

2017-01-01

This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.

Perceptual stimulus-A Bayesian-based integration of multi-visual-cue approach and its application

Institute of Scientific and Technical Information of China (English)

XUE JianRu; ZHENG NanNing; ZHONG XiaoPin; PING LinJiang

2008-01-01

With the view that visual cue could be taken as a kind of stimulus, the study of the mechanism in the visual perception process by using visual cues in their probabilistic representation eventually leads to a class of statistical integration of multiple visual cues (IMVC) methods which have been applied widely in perceptual grouping, video analysis, and other basic problems in computer vision. In this paper, a survey on the basic ideas and recent advances of IMVC methods is presented, and much focus is on the models and algorithms of IMVC for video analysis within the framework of Bayesian estimation. Furthermore, two typical problems in video analysis, robust visual tracking and "switching problem" in multi-target tracking (MTT) are taken as test beds to verify a series of Bayesian-based IMVC methods proposed by the authors. Furthermore, the relations between the statistical IMVC and the visual per-ception process, as well as potential future research work for IMVC, are discussed.

Time series analysis and its applications with R examples

CERN Document Server

Shumway, Robert H

2017-01-01

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonli...

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Visual Field Preferences of Object Analysis for Grasping with One Hand

Directory of Open Access Journals (Sweden)

Ada eLe

2014-10-01

Full Text Available When we grasp an object using one hand, the opposite hemisphere predominantly guides the motor control of grasp movements (Davare et al. 2007; Rice et al. 2007. However, it is unclear whether visual object analysis for grasp control relies more on inputs (a from the contralateral than the ipsilateral visual field, (b from one dominant visual field regardless of the grasping hand, or (c from both visual fields equally. For bimanual grasping of a single object we have recently demonstrated a visual field preference for the left visual field (Le and Niemeier 2013a, 2013b, consistent with a general right-hemisphere dominance for sensorimotor control of bimanual grasps (Le et al., 2013. But visual field differences have never been tested for unimanual grasping. Therefore, here we asked right-handed participants to fixate to the left or right of an object and then grasp the object either with their right or left hand using a precision grip. We found that participants grasping with their right hand performed better with objects in the right visual field: maximum grip apertures (MGAs were more closely matched to the object width and were smaller than for objects in the left visual field. In contrast, when people grasped with their left hand, preferences switched to the left visual field. What is more, MGA scaling showed greater visual field differences compared to right-hand grasping. Our data suggest that, visual object analysis for unimanual grasping shows a preference for visual information from the ipsilateral visual field, and that the left hemisphere is better equipped to control grasps in both visual fields.

A Review of Pathway-Based Analysis Tools That Visualize Genetic Variants

Directory of Open Access Journals (Sweden)

Elisa Cirillo

2017-11-01

Full Text Available Pathway analysis is a powerful method for data analysis in genomics, most often applied to gene expression analysis. It is also promising for single-nucleotide polymorphism (SNP data analysis, such as genome-wide association study data, because it allows the interpretation of variants with respect to the biological processes in which the affected genes and proteins are involved. Such analyses support an interactive evaluation of the possible effects of variations on function, regulation or interaction of gene products. Current pathway analysis software often does not support data visualization of variants in pathways as an alternate method to interpret genetic association results, and specific statistical methods for pathway analysis of SNP data are not combined with these visualization features. In this review, we first describe the visualization options of the tools that were identified by a literature review, in order to provide insight for improvements in this developing field. Tool evaluation was performed using a computational epistatic dataset of gene–gene interactions for obesity risk. Next, we report the necessity to include in these tools statistical methods designed for the pathway-based analysis with SNP data, expressly aiming to define features for more comprehensive pathway-based analysis tools. We conclude by recognizing that pathway analysis of genetic variations data requires a sophisticated combination of the most useful and informative visual aspects of the various tools evaluated.

Geoscience data visualization and analysis using GeoMapApp

Science.gov (United States)

Ferrini, Vicki; Carbotte, Suzanne; Ryan, William; Chan, Samantha

2013-04-01

Increased availability of geoscience data resources has resulted in new opportunities for developing visualization and analysis tools that not only promote data integration and synthesis, but also facilitate quantitative cross-disciplinary access to data. Interdisciplinary investigations, in particular, frequently require visualizations and quantitative access to specialized data resources across disciplines, which has historically required specialist knowledge of data formats and software tools. GeoMapApp (www.geomapapp.org) is a free online data visualization and analysis tool that provides direct quantitative access to a wide variety of geoscience data for a broad international interdisciplinary user community. While GeoMapApp provides access to online data resources, it can also be packaged to work offline through the deployment of a small portable hard drive. This mode of operation can be particularly useful during field programs to provide functionality and direct access to data when a network connection is not possible. Hundreds of data sets from a variety of repositories are directly accessible in GeoMapApp, without the need for the user to understand the specifics of file formats or data reduction procedures. Available data include global and regional gridded data, images, as well as tabular and vector datasets. In addition to basic visualization and data discovery functionality, users are provided with simple tools for creating customized maps and visualizations and to quantitatively interrogate data. Specialized data portals with advanced functionality are also provided for power users to further analyze data resources and access underlying component datasets. Users may import and analyze their own geospatial datasets by loading local versions of geospatial data and can access content made available through Web Feature Services (WFS) and Web Map Services (WMS). Once data are loaded in GeoMapApp, a variety options are provided to export data and/or 2D/3D

A taylor series approach to survival analysis

International Nuclear Information System (INIS)

Brodsky, J.B.; Groer, P.G.

1984-09-01

A method of survival analysis using hazard functions is developed. The method uses the well known mathematical theory for Taylor Series. Hypothesis tests of the adequacy of many statistical models, including proportional hazards and linear and/or quadratic dose responses, are obtained. A partial analysis of leukemia mortality in the Life Span Study cohort is used as an example. Furthermore, a relatively robust estimation procedure for the proportional hazards model is proposed. (author)

Analysis and visualization of citation networks

CERN Document Server

Zhao, Dangzhi

2015-01-01

Citation analysis-the exploration of reference patterns in the scholarly and scientific literature-has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval.Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest

Occam's razor and petascale visual data analysis

Energy Technology Data Exchange (ETDEWEB)

Bethel, E Wes [Lawrence Berkeley National Laboratory (LBNL); Johnson, Chris [University of Utah; Ahern, Sean [ORNL; Bell, J. [Lawrence Berkeley National Laboratory (LBNL); Bremer, Peer-Timo [Lawrence Livermore National Laboratory (LLNL); Childs, Hank [Lawrence Livermore National Laboratory (LLNL); Cormier-Michel, E [unknown; Day, M. [Lawrence Berkeley National Laboratory (LBNL); Deines, E. [University of California, Davis; Fogal, T. [University of Utah; Garth, Christoph [unknown; Geddes, C.G.R. [unknown; Hagen, H [unknown; Hamann, Bernd [unknown; Hansen, Charles [University of Utah; Jacobsen, Janet [Lawrence Berkeley National Laboratory (LBNL); Joy, Kenneth [University of California, Davis; Kruger, J. [University of Utah; Meredith, Jeremy S [ORNL; Messmer, P [unknown; Ostrouchov, George [ORNL; Pascucci, Valerio [Lawrence Livermore National Laboratory (LLNL); Potter, K. [University of Utah; Prabhat, [Lawrence Berkeley National Laboratory (LBNL); Pugmire, Dave [ORNL; Ruebel, O [unknown; Sanderson, Allen [University of Utah; Silva, C. [University of Utah; Ushizima, D. [Lawrence Berkeley National Laboratory (LBNL); Weber, G. [Lawrence Berkeley National Laboratory (LBNL); Whitlock, B. [Lawrence Livermore National Laboratory (LLNL); Wu, K. [Lawrence Berkeley National Laboratory (LBNL)

2009-01-01

One of the central challenges facing visualization research is how to effectively enable knowledge discovery. An effective approach will likely combine application architectures that are capable of running on today's largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena.

Efficient analysis using custom interactive visualization tools at a Superfund site

International Nuclear Information System (INIS)

Williams, G.; Durham, L.

1992-01-01

Custom visualization analysis programs were developed and used to analyze contaminant transport calculations from a three-dimensional numerical groundwater flow model developed for a Department of Energy Superfund site. The site hydrogeology, which is highly heterogenous, includes both fractured limestone and dolomite and alluvium deposits. Three-dimensional interactive visualization techniques were used to understand and analyze the three-dimensional, double-porosity modeling results. A graphical object oriented programming environment was applied to efficiently develop custom visualization programs in a coarse-grained data structure language. Comparisons were made, using the results from the three-dimensional, finite-difference model, between traditional two-dimensional analyses (contour and vector plots) and interactive three-dimensional techniques. Subjective comparison areas include the accuracy of analysis, the ability to understand the results of three-dimensional contaminant transport simulation, and the capability to transmit the results of the analysis to the project management. In addition, a quantitative comparison was made on the time required to develop a thorough analysis of the modeling results. The conclusions from the comparative study showed that the visualization analysis provided an increased awareness of the contaminant transport mechanisms, provided new insights into contaminant migration, and resulted in a significant time savings

Efficient analysis using custom interactive visualization tools at a Superfund site

Energy Technology Data Exchange (ETDEWEB)

Williams, G. [Northwestern Univ., Evanston, IL (United States); Durham, L. [Argonne National Lab., IL (United States)

1992-12-01

Custom visualization analysis programs were developed and used to analyze contaminant transport calculations from a three-dimensional numerical groundwater flow model developed for a Department of Energy Superfund site. The site hydrogeology, which is highly heterogenous, includes both fractured limestone and dolomite and alluvium deposits. Three-dimensional interactive visualization techniques were used to understand and analyze the three-dimensional, double-porosity modeling results. A graphical object oriented programming environment was applied to efficiently develop custom visualization programs in a coarse-grained data structure language. Comparisons were made, using the results from the three-dimensional, finite-difference model, between traditional two-dimensional analyses (contour and vector plots) and interactive three-dimensional techniques. Subjective comparison areas include the accuracy of analysis, the ability to understand the results of three-dimensional contaminant transport simulation, and the capability to transmit the results of the analysis to the project management. In addition, a quantitative comparison was made on the time required to develop a thorough analysis of the modeling results. The conclusions from the comparative study showed that the visualization analysis provided an increased awareness of the contaminant transport mechanisms, provided new insights into contaminant migration, and resulted in a significant time savings.

Lecture notes for Advanced Time Series Analysis

DEFF Research Database (Denmark)

Madsen, Henrik; Holst, Jan

1997-01-01

A first version of this notes was used at the lectures in Grenoble, and they are now extended and improved (together with Jan Holst), and used in Ph.D. courses on Advanced Time Series Analysis at IMM and at the Department of Mathematical Statistics, University of Lund, 1994, 1997, ...

Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

Science.gov (United States)

Yujun, Yang; Jianping, Li; Yimei, Yang

This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.

Scientific & Intelligence Exascale Visualization Analysis System

Energy Technology Data Exchange (ETDEWEB)

2017-07-14

SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.

Sex differences in visual-spatial working memory: A meta-analysis.

Science.gov (United States)

Voyer, Daniel; Voyer, Susan D; Saint-Aubin, Jean

2017-04-01

Visual-spatial working memory measures are widely used in clinical and experimental settings. Furthermore, it has been argued that the male advantage in spatial abilities can be explained by a sex difference in visual-spatial working memory. Therefore, sex differences in visual-spatial working memory have important implication for research, theory, and practice, but they have yet to be quantified. The present meta-analysis quantified the magnitude of sex differences in visual-spatial working memory and examined variables that might moderate them. The analysis used a set of 180 effect sizes from healthy males and females drawn from 98 samples ranging in mean age from 3 to 86 years. Multilevel meta-analysis was used on the overall data set to account for non-independent effect sizes. The data also were analyzed in separate task subgroups by means of multilevel and mixed-effects models. Results showed a small but significant male advantage (mean d = 0.155, 95 % confidence interval = 0.087-0.223). All the tasks produced a male advantage, except for memory for location, where a female advantage emerged. Age of the participants was a significant moderator, indicating that sex differences in visual-spatial working memory appeared first in the 13-17 years age group. Removing memory for location tasks from the sample affected the pattern of significant moderators. The present results indicate a male advantage in visual-spatial working memory, although age and specific task modulate the magnitude and direction of the effects. Implications for clinical applications, cognitive model building, and experimental research are discussed.

Visual accumulation tube for size analysis of sands

Science.gov (United States)

Colby, B.C.; Christensen, R.P.

1956-01-01

The visual-accumulation-tube method was developed primarily for making size analyses of the sand fractions of suspended-sediment and bed-material samples. Because the fundamental property governing the motion of a sediment particle in a fluid is believed to be its fall velocity. the analysis is designed to determine the fall-velocity-frequency distribution of the individual particles of the sample. The analysis is based on a stratified sedimentation system in which the sample is introduced at the top of a transparent settling tube containing distilled water. The procedure involves the direct visual tracing of the height of sediment accumulation in a contracted section at the bottom of the tube. A pen records the height on a moving chart. The method is simple and fast, provides a continuous and permanent record, gives highly reproducible results, and accurately determines the fall-velocity characteristics of the sample. The apparatus, procedure, results, and accuracy of the visual-accumulation-tube method for determining the sedimentation-size distribution of sands are presented in this paper.

Exploratory Visual Analysis for Animal Movement Ecology

NARCIS (Netherlands)

Slingsby, A.; van Loon, E.

2016-01-01

Movement ecologists study animals' movement to help understand their behaviours and interactions with each other and the environment. Data from GPS loggers are increasingly important for this. These data need to be processed, segmented and summarised for further visual and statistical analysis,

JavaScript and jQuery for data analysis and visualization

CERN Document Server

Raasch, Jon; Ogievetsky, Vadim; Lowery, Joseph

2014-01-01

Go beyond design concepts-build dynamic data visualizations using JavaScript JavaScript and jQuery for Data Analysis and Visualization goes beyond design concepts to show readers how to build dynamic, best-of-breed visualizations using JavaScript-the most popular language for web programming. The authors show data analysts, developers, and web designers how they can put the power and flexibility of modern JavaScript libraries to work to analyze data and then present it using best-of-breed visualizations. They also demonstrate the use of each technique with real-world use cases, showing how to

Time series analysis of barometric pressure data

International Nuclear Information System (INIS)

La Rocca, Paola; Riggi, Francesco; Riggi, Daniele

2010-01-01

Time series of atmospheric pressure data, collected over a period of several years, were analysed to provide undergraduate students with educational examples of application of simple statistical methods of analysis. In addition to basic methods for the analysis of periodicities, a comparison of two forecast models, one based on autoregression algorithms, and the other making use of an artificial neural network, was made. Results show that the application of artificial neural networks may give slightly better results compared to traditional methods.

Visual Analysis for Nowcasting of Multidimensional Lightning Data

Directory of Open Access Journals (Sweden)

Stefan Peters

2013-08-01

Full Text Available Globally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted lightning cluster- and track features as well as analysis results have to be represented in the most appropriate way. Our paper introduces a framework which includes identification, tracking, nowcasting, and in particular visualization and statistical analysis of dynamic lightning data in three-dimensional space. The paper is specifically focused on enabling users to conduct the visual analysis of lightning data for the purpose of identification and interpretation of spatial-temporal patterns embedded in lightning data, and their dynamics. A graphic user interface (GUI is developed, wherein lightning tracks and predicted lightning clusters, including their prediction certainty, can be investigated within a 3D view or within a Space-Time-Cube. In contrast to previous work, our approach provides insight into the dynamics of past and predicted 3D lightning clusters and cluster features over time. We conclude that an interactive visual exploration in combination with a statistical analysis can provide new knowledge within lightning investigations and, thus, support decision-making in weather forecast or lightning damage prevention.

Safety and effectiveness considerations for clinical studies of visual prosthetic devices

Science.gov (United States)

Cohen, Ethan D.

2007-03-01

With the advent of new designs of visual prostheses for the blind, FDA is faced with developing guidance for evaluating their engineering, safety and patient performance. Visual prostheses are considered significant risk medical devices, and their use in human clinical trials must be approved by FDA under an investigation device exemption (IDE). This paper contains a series of test topics and design issues that sponsors should consider in order to assess the safety and efficacy of their device. The IDE application includes a series of pre-clinical and clinical data sections. The pre-clinical section documents laboratory, animal and bench top performance tests of visual prostheses safety and reliability to support a human clinical trial. The materials used in constructing the implant should be biocompatible, sterile, corrosion resistant, and able to withstand any forces exerted on it during normal patient use. The clinical data section is composed of items related to patient-related evaluation of device performance. This section documents the implantation procedure, trial design, statistical analysis and how visual performance is assessed. Similar to cochlear implants, a visual prosthesis is expected to last in the body for many years, and good pre-clinical and clinical testing will help ensure its safety, durability and effectiveness.

Handbook of Time Series Analysis Recent Theoretical Developments and Applications

CERN Document Server

Schelter, Björn; Timmer, Jens

2006-01-01

This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest de

Visual Resource Analysis for Solar Energy Zones in the San Luis Valley

Energy Technology Data Exchange (ETDEWEB)

Sullivan, Robert [Argonne National Laboratory (ANL), Argonne, IL (United States). Environmental Science Division; Abplanalp, Jennifer M. [Argonne National Laboratory (ANL), Argonne, IL (United States). Environmental Science Division; Zvolanek, Emily [Argonne National Laboratory (ANL), Argonne, IL (United States). Environmental Science Division; Brown, Jeffery [Bureau of Land Management, Washington, DC (United States). Dept. of the Interior

2016-01-01

This report summarizes the results of a study conducted by Argonne National Laboratory’s (Argonne’s) Environmental Science Division for the U.S. Department of the Interior Bureau of Land Management (BLM). The study analyzed the regional effects of potential visual impacts of solar energy development on three BLM-designated solar energy zones (SEZs) in the San Luis Valley (SLV) in Colorado, and, based on the analysis, made recommendations for or against regional compensatory mitigation to compensate residents and other stakeholders for the potential visual impacts to the SEZs. The analysis was conducted as part of the solar regional mitigation strategy (SRMS) task conducted by BLM Colorado with assistance from Argonne. Two separate analyses were performed. The first analysis, referred to as the VSA Analysis, analyzed the potential visual impacts of solar energy development in the SEZs on nearby visually sensitive areas (VSAs), and, based on the impact analyses, made recommendations for or against regional compensatory mitigation. VSAs are locations for which some type of visual sensitivity has been identified, either because the location is an area of high scenic value or because it is a location from which people view the surrounding landscape and attach some level of importance or sensitivity to what is seen from the location. The VSA analysis included both BLM-administered lands in Colorado and in the Taos FO in New Mexico. The second analysis, referred to as the SEZ Analysis, used BLM visual resource inventory (VRI) and other data on visual resources in the former Saguache and La Jara Field Offices (FOs), now contained within the San Luis Valley FO (SLFO), to determine whether the changes in scenic values that would result from the development of utility-scale solar energy facilities in the SEZs would affect the quality and quantity of valued scenic resources in the SLV region as a whole. If the regional effects were judged to be significant, regional

Time-series analysis of Nigeria rice supply and demand: Error ...

African Journals Online (AJOL)

The study examined a time-series analysis of Nigeria rice supply and demand with a view to determining any long-run equilibrium between them using the Error Correction Model approach (ECM). The data used for the study represents the annual series of 1960-2007 (47 years) for rice supply and demand in Nigeria, ...

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

Neuron analysis of visual perception

Science.gov (United States)

Chow, K. L.

1980-01-01

The receptive fields of single cells in the visual system of cat and squirrel monkey were studied investigating the vestibular input affecting the cells, and the cell's responses during visual discrimination learning process. The receptive field characteristics of the rabbit visual system, its normal development, its abnormal development following visual deprivation, and on the structural and functional re-organization of the visual system following neo-natal and prenatal surgery were also studied. The results of each individual part of each investigation are detailed.

A novel water quality data analysis framework based on time-series data mining.

Science.gov (United States)

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Ideal Observer Analysis of Visual Working Memory

Science.gov (United States)

Sims, Chris R.; Jacobs, Robert A.; Knill, David C.

2012-01-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this article we develop an ideal observer analysis of human VWM by deriving the expected behavior of an optimally performing but limited-capacity memory system. This analysis is framed around…

Malware analysis using visualized image matrices.

Science.gov (United States)

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Malware Analysis Using Visualized Image Matrices

Directory of Open Access Journals (Sweden)

KyoungSoo Han

2014-01-01

Full Text Available This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

Science.gov (United States)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Nonlinear Time Series Analysis via Neural Networks

Science.gov (United States)

Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

Biological time series analysis using a context free language: applicability to pulsatile hormone data.

Directory of Open Access Journals (Sweden)

Dennis A Dean

Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.

Visual interrogation of gyrokinetic particle simulations

International Nuclear Information System (INIS)

Jones, Chad; Ma, K-L; Sanderson, Allen; Myers, Lee Roy Jr

2007-01-01

Gyrokinetic particle simulations are critical to the study of anomalous energy transport associated with plasma microturbulence in magnetic confinement fusion experiments. The simulations are conducted on massively parallel computers and produce large quantities of particles, variables, and time steps, thus presenting a formidable challenge to data analysis tasks. We present two new visualization techniques for scientists to improve their understanding of the time-varying, multivariate particle data. One technique allows scientists to examine correlations in multivariate particle data with tightly coupled views of the data in both physical space and variable space, and to visually identify and track features of interest. The second technique, built into SCIRun, allows scientists to perform range-based queries over a series of time slices and visualize the resulting particles using glyphs. The ability to navigate the multiple dimensions of the particle data, as well as query individual or a collection of particles, enables scientists to not only validate their simulations but also discover new phenomena in their data

Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Final Report

Energy Technology Data Exchange (ETDEWEB)

Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-05-19

A partnership across government, academic, and private sectors has created a novel system that enables climate researchers to solve current and emerging data analysis and visualization challenges. The Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) software project utilizes the Python application programming interface (API) combined with C/C++/Fortran implementations for performance-critical software that offers the best compromise between "scalability" and “ease-of-use.” The UV-CDAT system is highly extensible and customizable for high-performance interactive and batch visualization and analysis for climate science and other disciplines of geosciences. For complex, climate data-intensive computing, UV-CDAT’s inclusive framework supports Message Passing Interface (MPI) parallelism as well as taskfarming and other forms of parallelism. More specifically, the UV-CDAT framework supports the execution of Python scripts running in parallel using the MPI executable commands and leverages Department of Energy (DOE)-funded general-purpose, scalable parallel visualization tools such as ParaView and VisIt. This is the first system to be successfully designed in this way and with these features. The climate community leverages these tools and others, in support of a parallel client-server paradigm, allowing extreme-scale, server-side computing for maximum possible speed-up.

An Application of Multivariate Statistical Analysis for Query-Driven Visualization

Energy Technology Data Exchange (ETDEWEB)

Gosink, Luke J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Garth, Christoph [Univ. of California, Davis, CA (United States); Anderson, John C. [Univ. of California, Davis, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Joy, Kenneth I. [Univ. of California, Davis, CA (United States)

2011-03-01

Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent need in the scientific community for scalable analysis methods that can rapidly identify salient trends in scientific data. Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex datasets. This paper extends the utility of QDV strategies with a statistics-based framework that integrates non-parametric distribution estimation techniques with a new segmentation strategy to visually identify statistically significant trends and features within the solution space of a query. In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry. Our new segmentation strategy extends the distribution estimation analysis by visually conveying the individual importance of each variable to these regions of high statistical significance. We demonstrate the analysis benefits these two strategies provide and show how they may be used to facilitate the refinement of constraints over variables expressed in a user's query. We apply our method to datasets from two different scientific domains to demonstrate its broad applicability.

Growth And Export Expansion In Mauritius - A Time Series Analysis ...

African Journals Online (AJOL)

Growth And Export Expansion In Mauritius - A Time Series Analysis. ... RV Sannassee, R Pearce ... Using Granger Causality tests, the short-run analysis results revealed that there is significant reciprocal causality between real export earnings ...

Filling the Astronomical Void - A Visual Medium for a Visual Subject

Science.gov (United States)

Ryan, J.

1996-12-01

Astronomy is fundamentally a visual subject. The modern science of astronomy has at its foundation the ancient art of observing the sky visually. The visual elements of astronomy are arguably the most important. Every person in the entire world is affected by visually-observed astronomical phenomena such as the seasonal variations in daylight. However, misconceptions abound and the average person cannot recognize the simple signs in the sky that point to the direction, the hour and the season. Educators and astronomy popularizers widely lament that astronomy is not appreciated in our society. Yet, there is a remarkable dearth of popular literature for teaching the visual elements of astronomy. This is what I refer to as *the astronomical void.* Typical works use illustrations sparsely, relying most heavily on text-based descriptions of the visual astronomical phenomena. Such works leave significant inferential gaps to the inexperienced reader, who is unequipped for making astronomical observations. Thus, the astronomical void remains unfilled by much of the currently available literature. I therefore propose the introduction of a visually-oriented medium for teaching the visual elements of Astronomy. To this end, I have prepared a series of astronomy "comic strips" that are intended to fill the astronomical void. By giving the illustrations the central place, the comic strip medium permits the depiction of motion and other sequential activity, thus effectively representing astronomical phenomena. In addition to the practical advantages, the comic strip is a "user friendly" medium that is inviting and entertaining to a reader. At the present time, I am distributing a monthly comic strip entitled *Starman*, which appears in the newsletters of over 120 local astronomy organizations and on the web at http://www.cyberdrive.net/ starman. I hope to eventually publish a series of full-length books and believe that astronomical comic strips will help expand the perimeter of

Multiresolution and Explicit Methods for Vector Field Analysis and Visualization

Science.gov (United States)

Nielson, Gregory M.

1997-01-01

This is a request for a second renewal (3d year of funding) of a research project on the topic of multiresolution and explicit methods for vector field analysis and visualization. In this report, we describe the progress made on this research project during the second year and give a statement of the planned research for the third year. There are two aspects to this research project. The first is concerned with the development of techniques for computing tangent curves for use in visualizing flow fields. The second aspect of the research project is concerned with the development of multiresolution methods for curvilinear grids and their use as tools for visualization, analysis and archiving of flow data. We report on our work on the development of numerical methods for tangent curve computation first.

HydroDesktop: An Open Source GIS-Based Platform for Hydrologic Data Discovery, Visualization, and Analysis

Science.gov (United States)

Ames, D. P.; Kadlec, J.; Cao, Y.; Grover, D.; Horsburgh, J. S.; Whiteaker, T.; Goodall, J. L.; Valentine, D. W.

2010-12-01

A growing number of hydrologic information servers are being deployed by government agencies, university networks, and individual researchers using the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS). The CUAHSI HIS Project has developed a standard software stack, called HydroServer, for publishing hydrologic observations data. It includes the Observations Data Model (ODM) database and Water Data Service web services, which together enable publication of data on the Internet in a standard format called Water Markup Language (WaterML). Metadata describing available datasets hosted on these servers is compiled within a central metadata catalog called HIS Central at the San Diego Supercomputer Center and is searchable through a set of predefined web services based queries. Together, these servers and central catalog service comprise a federated HIS of a scale and comprehensiveness never previously available. This presentation will briefly review/introduce the CUAHSI HIS system with special focus on a new HIS software tool called "HydroDesktop" and the open source software development web portal, www.HydroDesktop.org, which supports community development and maintenance of the software. HydroDesktop is a client-side, desktop software application that acts as a search and discovery tool for exploring the distributed network of HydroServers, downloading specific data series, visualizing and summarizing data series and exporting these to formats needed for analysis by external software. HydroDesktop is based on the open source DotSpatial GIS developer toolkit which provides it with map-based data interaction and visualization, and a plug-in interface that can be used by third party developers and researchers to easily extend the software using Microsoft .NET programming languages. HydroDesktop plug-ins that are presently available or currently under development within the project and by third party

OpinionFlow: Visual Analysis of Opinion Diffusion on Social Media.

Science.gov (United States)

Wu, Yingcai; Liu, Shixia; Yan, Kai; Liu, Mengchen; Wu, Fangzhao

2014-12-01

It is important for many different applications such as government and business intelligence to analyze and explore the diffusion of public opinions on social media. However, the rapid propagation and great diversity of public opinions on social media pose great challenges to effective analysis of opinion diffusion. In this paper, we introduce a visual analysis system called OpinionFlow to empower analysts to detect opinion propagation patterns and glean insights. Inspired by the information diffusion model and the theory of selective exposure, we develop an opinion diffusion model to approximate opinion propagation among Twitter users. Accordingly, we design an opinion flow visualization that combines a Sankey graph with a tailored density map in one view to visually convey diffusion of opinions among many users. A stacked tree is used to allow analysts to select topics of interest at different levels. The stacked tree is synchronized with the opinion flow visualization to help users examine and compare diffusion patterns across topics. Experiments and case studies on Twitter data demonstrate the effectiveness and usability of OpinionFlow.

A New Conceptual Model for Business Ecosystem Visualization and Analysis

Directory of Open Access Journals (Sweden)

Luiz Felipe Hupsel Vaz

2013-01-01

Full Text Available This study has the objective of plotting the effects of network externalities and superstar software for the visualization and analysis of industry ecosystems. The output is made possible by gathering sales from a tracking website, associating each sale to a single consumer and by using a network visualization software. The result is a graph that shows strategic positioning of publishers and platforms, serving as a strategic tool for both academics and professionals. The approach is scalable to other industries and can be used to support analysis on mergers, acquisitions and alliances.

Time Series Analysis of Wheat Futures Reward in China

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

Different from the fact that the main researches are focused on single futures contract and lack of the comparison of different periods, this paper described the statistical characteristics of wheat futures reward time series of Zhengzhou Commodity Exchange in recent three years. Besides the basic statistic analysis, the paper used the GARCH and EGARCH model to describe the time series which had the ARCH effect and analyzed the persistence of volatility shocks and the leverage effect. The results showed that compared with that of normal one,wheat futures reward series were abnormality, leptokurtic and thick tail distribution. The study also found that two-part of the reward series had no autocorrelation. Among the six correlative series, three ones presented the ARCH effect. By using of the Auto-regressive Distributed Lag Model, GARCH model and EGARCH model, the paper demonstrates the persistence of volatility shocks and the leverage effect on the wheat futures reward time series. The results reveal that on the one hand, the statistical characteristics of the wheat futures reward are similar to the aboard mature futures market as a whole. But on the other hand, the results reflect some shortages such as the immatureness and the over-control by the government in the Chinese future market.

Integrated Visualization of Multi-sensor Ocean Data across the Web

Science.gov (United States)

Platt, F.; Thompson, C. K.; Roberts, J. T.; Tsontos, V. M.; Hin Lam, C.; Arms, S. C.; Quach, N.

2017-12-01

Whether for research or operational decision support, oceanographic applications rely on the visualization of multivariate in situ and remote sensing data as an integral part of analysis workflows. However, given their inherently 3D-spatial and temporally dynamic nature, the visual representation of marine in situ data in particular poses a challenge. The Oceanographic In situ data Interoperability Project (OIIP) is a collaborative project funded under the NASA/ACCESS program that seeks to leverage and enhance higher TRL (technology readiness level) informatics technologies to address key data interoperability and integration issues associated with in situ ocean data, including the dearth of effective web-based visualization solutions. Existing web tools for the visualization of key in situ data types - point, profile, trajectory series - are limited in their support for integrated, dynamic and coordinated views of the spatiotemporal characteristics of the data. Via the extension of the JPL Common Mapping Client (CMC) software framework, OIIP seeks to provide improved visualization support for oceanographic in situ data sets. More specifically, this entails improved representation of both horizontal and vertical aspects of these data, which inherently are depth resolved and time referenced, as well as the visual synchronization with relevant remotely-sensed gridded data products, such as sea surface temperature and salinity. Electronic tagging datasets, which are a focal use case for OIIP, provide a representative, if somewhat complex, visualization challenge in this regard. Critical to the achievement of these development objectives has been compilation of a well-rounded set of visualization use cases and requirements based on a series of end-user consultations aimed at understanding their satellite-in situ visualization needs. Here we summarize progress on aspects of the technical work and our approach.

Emotion processing in the visual brain: a MEG analysis.

Science.gov (United States)

Peyk, Peter; Schupp, Harald T; Elbert, Thomas; Junghöfer, Markus

2008-06-01

Recent functional magnetic resonance imaging (fMRI) and event-related brain potential (ERP) studies provide empirical support for the notion that emotional cues guide selective attention. Extending this line of research, whole head magneto-encephalogram (MEG) was measured while participants viewed in separate experimental blocks a continuous stream of either pleasant and neutral or unpleasant and neutral pictures, presented for 330 ms each. Event-related magnetic fields (ERF) were analyzed after intersubject sensor coregistration, complemented by minimum norm estimates (MNE) to explore neural generator sources. Both streams of analysis converge by demonstrating the selective emotion processing in an early (120-170 ms) and a late time interval (220-310 ms). ERF analysis revealed that the polarity of the emotion difference fields was reversed across early and late intervals suggesting distinct patterns of activation in the visual processing stream. Source analysis revealed the amplified processing of emotional pictures in visual processing areas with more pronounced occipito-parieto-temporal activation in the early time interval, and a stronger engagement of more anterior, temporal, regions in the later interval. Confirming previous ERP studies showing facilitated emotion processing, the present data suggest that MEG provides a complementary look at the spread of activation in the visual processing stream.

Topological data analysis of financial time series: Landscapes of crashes

Science.gov (United States)

Gidea, Marian; Katz, Yuri

2018-02-01

We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.

The Visual System

Medline Plus

Full Text Available ... for Kids >> The Visual System Listen All About Vision About the Eye Ask a Scientist Video Series ... Eye Health and Safety First Aid Tips Healthy Vision Tips Protective Eyewear Sports and Your Eyes Fun ...

Visual querying and analysis of large software repositories

NARCIS (Netherlands)

Voinea, Lucian; Telea, Alexandru

We present a software framework for mining software repositories. Our extensible framework enables the integration of data extraction from repositories with data analysis and interactive visualization. We demonstrate the applicability of the framework by presenting several case studies performed on

Visualization and Analysis-Oriented Reconstruction of Material Interfaces

Energy Technology Data Exchange (ETDEWEB)

Childs, Henry R.

2010-03-05

Reconstructing boundaries along material interfaces from volume fractions is a difficult problem, especially because the under-resolved nature of the input data allows for many correct interpretations. Worse, algorithms widely accepted as appropriate for simulation are inappropriate for visualization. In this paper, we describe a new algorithm that is specifically intended for reconstructing material interfaces for visualization and analysis requirements. The algorithm performs well with respect to memory footprint and execution time, has desirable properties in various accuracy metrics, and also produces smooth surfaces with few artifacts, even when faced with more than two materials per cell.

Time series analysis in astronomy: Limits and potentialities

DEFF Research Database (Denmark)

Vio, R.; Kristensen, N.R.; Madsen, Henrik

2005-01-01

In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a...

ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS

Directory of Open Access Journals (Sweden)

Z.-G. Zhou

2016-06-01

Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

Time series analysis of nuclear instrumentation in EBR-II

International Nuclear Information System (INIS)

Imel, G.R.

1996-01-01

Results of a time series analysis of the scaler count data from the 3 wide range nuclear detectors in the Experimental Breeder Reactor-II are presented. One of the channels was replaced, and it was desired to determine if there was any statistically significant change (ie, improvement) in the channel's response after the replacement. Data were collected from all 3 channels for 16-day periods before and after detector replacement. Time series analysis and statistical tests showed that there was no significant change after the detector replacement. Also, there were no statistically significant differences among the 3 channels, either before or after the replacement. Finally, it was determined that errors in the reactivity change inferred from subcritical count monitoring during fuel handling would be on the other of 20-30 cents for single count intervals

Stethoscope: A platform for interactive visual analysis of query execution plans

NARCIS (Netherlands)

M.M. Gawade (Mrunal); M.L. Kersten (Martin)

2012-01-01

textabstractSearching for the performance bottleneck in an execution trace is an error prone and time consuming activity. Existing tools oer some comfort by providing a visual representation of trace for analysis. In this paper we present the Stethoscope, an interactive visual tool to inspect and

Stethoscope: a platform for interactive visual analysis of query execution plans

NARCIS (Netherlands)

Gawade, M.; Kersten, M.

2012-01-01

Searching for the performance bottleneck in an execution trace is an error prone and time consuming activity. Existing tools offer some comfort by providing a visual representation of trace for analysis. In this paper we present the Stethoscope, an interactive visual tool to inspect and ana- lyze

Visual exploration and analysis of human-robot interaction rules

Science.gov (United States)

Zhang, Hui; Boyles, Michael J.

2013-01-01

We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming

Visualizing nD Point Clouds as Topological Landscape Profiles to Guide Local Data Analysis

Energy Technology Data Exchange (ETDEWEB)

Oesterling, Patrick [Univ. of Leipzig (Germany). Computer Science Dept.; Heine, Christian [Univ. of Leipzig (Germany). Computer Science Dept.; Federal Inst. of Technology (ETH), Zurich (Switzerland). Dept. of Computer Science; Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Scheuermann, Gerik [Univ. of Leipzig (Germany). Computer Science Dept.

2012-05-04

Analyzing high-dimensional point clouds is a classical challenge in visual analytics. Traditional techniques, such as projections or axis-based techniques, suffer from projection artifacts, occlusion, and visual complexity.We propose to split data analysis into two parts to address these shortcomings. First, a structural overview phase abstracts data by its density distribution. This phase performs topological analysis to support accurate and non-overlapping presentation of the high-dimensional cluster structure as a topological landscape profile. Utilizing a landscape metaphor, it presents clusters and their nesting as hills whose height, width, and shape reflect cluster coherence, size, and stability, respectively. A second local analysis phase utilizes this global structural knowledge to select individual clusters or point sets for further, localized data analysis. Focusing on structural entities significantly reduces visual clutter in established geometric visualizations and permits a clearer, more thorough data analysis. In conclusion, this analysis complements the global topological perspective and enables the user to study subspaces or geometric properties, such as shape.

Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

Science.gov (United States)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

Immersive Visual Data Analysis For Geoscience Using Commodity VR Hardware

Science.gov (United States)

Kreylos, O.; Kellogg, L. H.

2017-12-01

Immersive visualization using virtual reality (VR) display technology offers tremendous benefits for the visual analysis of complex three-dimensional data like those commonly obtained from geophysical and geological observations and models. Unlike "traditional" visualization, which has to project 3D data onto a 2D screen for display, VR can side-step this projection and display 3D data directly, in a pseudo-holographic (head-tracked stereoscopic) form, and does therefore not suffer the distortions of relative positions, sizes, distances, and angles that are inherent in 2D projection. As a result, researchers can apply their spatial reasoning skills to virtual data in the same way they can to real objects or environments. The UC Davis W.M. Keck Center for Active Visualization in the Earth Sciences (KeckCAVES, http://keckcaves.org) has been developing VR methods for data analysis since 2005, but the high cost of VR displays has been preventing large-scale deployment and adoption of KeckCAVES technology. The recent emergence of high-quality commodity VR, spearheaded by the Oculus Rift and HTC Vive, has fundamentally changed the field. With KeckCAVES' foundational VR operating system, Vrui, now running natively on the HTC Vive, all KeckCAVES visualization software, including 3D Visualizer, LiDAR Viewer, Crusta, Nanotech Construction Kit, and ProtoShop, are now available to small labs, single researchers, and even home users. LiDAR Viewer and Crusta have been used for rapid response to geologic events including earthquakes and landslides, to visualize the impacts of sealevel rise, to investigate reconstructed paleooceanographic masses, and for exploration of the surface of Mars. The Nanotech Construction Kit is being used to explore the phases of carbon in Earth's deep interior, while ProtoShop can be used to construct and investigate protein structures.

Quantitative analysis of gait in the visually impaired.

Science.gov (United States)

Nakamura, T

1997-05-01

In this comparative study concerning characteristics of independent walking by visually impaired persons, we used a motion analyser system to perform gait analysis of 15 late blind (age 36-54, mean 44.3 years), 15 congenitally blind (age 39-48, mean 43.8 years) and 15 sighted persons (age 40-50, mean 44.4 years) while walking a 10-m walkway. All subjects were male. Compared to the sighted, late blind and congenitally blind persons had a significantly slower walking speed, shorter stride length and longer time in the stance phase of gait. However, the relationships between gait parameters in the late and congenitally blind groups were maintained, as in the sighted group. In addition, the gait of the late blind showed a tendency to approximate the gait patterns of the congenitally blind as the duration of visual loss progressed. Based on these results we concluded that the gait of visually impaired persons, through its active use of non-visual sensory input, represents an attempt to adapt to various environmental conditions in order to maintain a more stable posture and to effect safe walking.

Phishing Detection: Analysis of Visual Similarity Based Approaches

Directory of Open Access Journals (Sweden)

Ankit Kumar Jain

2017-01-01

Full Text Available Phishing is one of the major problems faced by cyber-world and leads to financial losses for both industries and individuals. Detection of phishing attack with high accuracy has always been a challenging issue. At present, visual similarities based techniques are very useful for detecting phishing websites efficiently. Phishing website looks very similar in appearance to its corresponding legitimate website to deceive users into believing that they are browsing the correct website. Visual similarity based phishing detection techniques utilise the feature set like text content, text format, HTML tags, Cascading Style Sheet (CSS, image, and so forth, to make the decision. These approaches compare the suspicious website with the corresponding legitimate website by using various features and if the similarity is greater than the predefined threshold value then it is declared phishing. This paper presents a comprehensive analysis of phishing attacks, their exploitation, some of the recent visual similarity based approaches for phishing detection, and its comparative study. Our survey provides a better understanding of the problem, current solution space, and scope of future research to deal with phishing attacks efficiently using visual similarity based approaches.

NCL - a workhorse for data analysis and visualization in climate research

Science.gov (United States)

Meier-Fleischer, Karin; Boettinger, Michael; Haley, Mary

2015-04-01

Coupled earth system models are used for simulating the climate system. In the context of international climate assessment and model intercomparison projects, extensive simulation data sets are produced and have to be analyzed. Supercomputers and storage systems are used over years to perform the simulations, but the data analysis usually takes even more time. Different classes of tools are used for the analysis and visualization of these big data sets. In this PICO, we focus on NCL (NCAR Command Language), an interpreted language developed at the National Center for Atmospheric Research in Boulder, Colorado. NCL allows performing standard analysis operations and producing graphical output in batch mode loosely coupled with the simulations. Thus, for visual monitoring of their simulations, many of DKRZ's users have integrated NCL into their modeling workflows. We present application examples from the tutorial we have developed that focus on typical visualizations of climate model data. Since NCL supports rectilinear, curvilinear and even unstructured grids, it is well prepared to facilitate the visualization of today's climate model data without prior interpolation. NCL includes many features common to modern programming languages, such as types, variables, operators, expressions, conditional statements, loops, and functions and procedures. It provides more than 600 built-in functions specifically for climate model data, facilitating analysis of scalar and vector quantities as well as numerous state-of-the-art 2D visualization methods (contour lines, filled areas, markers, wind arrows or barbs, weather symbols and many more). Important for Earth scientists is also NCL's capability to display data together with the corresponding map background and a choice of the map projection.

Predicting long-term catchment nutrient export: the use of nonlinear time series models

Science.gov (United States)

Valent, Peter; Howden, Nicholas J. K.; Szolgay, Jan; Komornikova, Magda

2010-05-01

After the Second World War the nitrate concentrations in European water bodies changed significantly as the result of increased nitrogen fertilizer use and changes in land use. However, in the last decades, as a consequence of the implementation of nitrate-reducing measures in Europe, the nitrate concentrations in water bodies slowly decrease. This causes that the mean and variance of the observed time series also changes with time (nonstationarity and heteroscedascity). In order to detect changes and properly describe the behaviour of such time series by time series analysis, linear models (such as autoregressive (AR), moving average (MA) and autoregressive moving average models (ARMA)), are no more suitable. Time series with sudden changes in statistical characteristics can cause various problems in the calibration of traditional water quality models and thus give biased predictions. Proper statistical analysis of these non-stationary and heteroscedastic time series with the aim of detecting and subsequently explaining the variations in their statistical characteristics requires the use of nonlinear time series models. This information can be then used to improve the model building and calibration of conceptual water quality model or to select right calibration periods in order to produce reliable predictions. The objective of this contribution is to analyze two long time series of nitrate concentrations of the rivers Ouse and Stour with advanced nonlinear statistical modelling techniques and compare their performance with traditional linear models of the ARMA class in order to identify changes in the time series characteristics. The time series were analysed with nonlinear models with multiple regimes represented by self-exciting threshold autoregressive (SETAR) and Markov-switching models (MSW). The analysis showed that, based on the value of residual sum of squares (RSS) in both datasets, SETAR and MSW models described the time-series better than models of the

Multiscale visual quality assessment for cluster analysis with self-organizing maps

Science.gov (United States)

Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

2011-01-01

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

Parallel analysis tools and new visualization techniques for ultra-large climate data set

Energy Technology Data Exchange (ETDEWEB)

Middleton, Don [National Center for Atmospheric Research, Boulder, CO (United States); Haley, Mary [National Center for Atmospheric Research, Boulder, CO (United States)

2014-12-10

ParVis was a project funded under LAB 10-05: “Earth System Modeling: Advanced Scientific Visualization of Ultra-Large Climate Data Sets”. Argonne was the lead lab with partners at PNNL, SNL, NCAR and UC-Davis. This report covers progress from January 1st, 2013 through Dec 1st, 2014. Two previous reports covered the period from Summer, 2010, through September 2011 and October 2011 through December 2012, respectively. While the project was originally planned to end on April 30, 2013, personnel and priority changes allowed many of the institutions to continue work through FY14 using existing funds. A primary focus of ParVis was introducing parallelism to climate model analysis to greatly reduce the time-to-visualization for ultra-large climate data sets. Work in the first two years was conducted on two tracks with different time horizons: one track to provide immediate help to climate scientists already struggling to apply their analysis to existing large data sets and another focused on building a new data-parallel library and tool for climate analysis and visualization that will give the field a platform for performing analysis and visualization on ultra-large datasets for the foreseeable future. In the final 2 years of the project, we focused mostly on the new data-parallel library and associated tools for climate analysis and visualization.

Time series analysis in chaotic diode resonator circuit

Energy Technology Data Exchange (ETDEWEB)

Hanias, M.P. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)] e-mail: mhanias@teihal.gr; Giannaris, G. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Spyridakis, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Rigas, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)

2006-01-01

A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension {nu} and m {sub min}, respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated.

Time series analysis in chaotic diode resonator circuit

International Nuclear Information System (INIS)

Hanias, M.P.; Giannaris, G.; Spyridakis, A.; Rigas, A.

2006-01-01

A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension ν and m min , respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated

RVA. 3-D Visualization and Analysis Software to Support Management of Oil and Gas Resources

Energy Technology Data Exchange (ETDEWEB)

Keefer, Donald A. [Univ. of Illinois, Champaign, IL (United States); Shaffer, Eric G. [Univ. of Illinois, Champaign, IL (United States); Storsved, Brynne [Univ. of Illinois, Champaign, IL (United States); Vanmoer, Mark [Univ. of Illinois, Champaign, IL (United States); Angrave, Lawrence [Univ. of Illinois, Champaign, IL (United States); Damico, James R. [Univ. of Illinois, Champaign, IL (United States); Grigsby, Nathan [Univ. of Illinois, Champaign, IL (United States)

2015-12-01

A free software application, RVA, has been developed as a plugin to the US DOE-funded ParaView visualization package, to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed as an open-source plugin to the 64 bit Windows version of ParaView 3.14. RVA was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including

Notes on economic time series analysis system theoretic perspectives

CERN Document Server

Aoki, Masanao

1983-01-01

In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor­ ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of wha...

Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis

International Nuclear Information System (INIS)

Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui

2013-01-01

We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained

expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform.

Science.gov (United States)

Borrill, Philippa; Ramirez-Gonzalez, Ricardo; Uauy, Cristobal

2016-04-01

The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP's suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments. © 2016 American Society of Plant Biologists. All Rights Reserved.

Behavior analysis for elderly care using a network of low-resolution visual sensors

Science.gov (United States)

Eldib, Mohamed; Deboeverie, Francis; Philips, Wilfried; Aghajan, Hamid

2016-07-01

Recent advancements in visual sensor technologies have made behavior analysis practical for in-home monitoring systems. The current in-home monitoring systems face several challenges: (1) visual sensor calibration is a difficult task and not practical in real-life because of the need for recalibration when the visual sensors are moved accidentally by a caregiver or the senior citizen, (2) privacy concerns, and (3) the high hardware installation cost. We propose to use a network of cheap low-resolution visual sensors (30×30 pixels) for long-term behavior analysis. The behavior analysis starts by visual feature selection based on foreground/background detection to track the motion level in each visual sensor. Then a hidden Markov model (HMM) is used to estimate the user's locations without calibration. Finally, an activity discovery approach is proposed using spatial and temporal contexts. We performed experiments on 10 months of real-life data. We show that the HMM approach outperforms the k-nearest neighbor classifier against ground truth for 30 days. Our framework is able to discover 13 activities of daily livings (ADL parameters). More specifically, we analyze mobility patterns and some of the key ADL parameters to detect increasing or decreasing health conditions.

Visual behaviour analysis and driver cognitive model

Energy Technology Data Exchange (ETDEWEB)

Baujon, J.; Basset, M.; Gissinger, G.L. [Mulhouse Univ., (France). MIPS/MIAM Lab.

2001-07-01

Recent studies on driver behaviour have shown that perception - mainly visual but also proprioceptive perception - plays a key role in the ''driver-vehicle-road'' system and so considerably affects the driver's decision making. Within the framework of the behaviour analysis and studies low-cost system (BASIL), this paper presents a correlative, qualitative and quantitative study, comparing the information given by visual perception and by the trajectory followed. This information will help to obtain a cognitive model of the Rasmussen type according to different driver classes. Many experiments in real driving situations have been carried out for different driver classes and for a given trajectory profile, using a test vehicle and innovative, specially designed, real-time tools, such as the vision system or the positioning module. (orig.)

Interpretative Visual Analysis. Developments, State of the Art and Pending Problems

Directory of Open Access Journals (Sweden)

Bernt Schnettler

2008-09-01

Full Text Available he article offers a brief resume of recent developments in the field of interpretative visual analysis with emphasis on the German speaking area and the sociological discipline. It lays a special focus on hermeneutical and genre analysis and on research with audiovisual data. Far from constituting an already closed field, the authors stress the fact that methodological advances in qualitative research based in visual data still face a number of pending quests. This encompasses sequentiality, complexity and naturalness of videographic data, and extends to the respective methodological challenges for transcription, analysis and presentation of results. URN: urn:nbn:de:0114-fqs0803314

A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis.

Science.gov (United States)

Benítez, José Alberto; Labra, José Emilio; Quiroga, Enedina; Martín, Vicente; García, Isaías; Marqués-Sánchez, Pilar; Benavides, Carmen

2017-01-01

There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data.

Sensitivity analysis of machine-learning models of hydrologic time series

Science.gov (United States)

O'Reilly, A. M.

2017-12-01

Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.

Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

Science.gov (United States)

Ding, Feng; Keim, Elaine; Hearty, Thomas J.; Wei, Jennifer; Savtchenko, Andrey; Theobald, Michael; Vollmer, Bruce

2016-01-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

Remote Sensing Data Visualization, Fusion and Analysis via Giovanni

Science.gov (United States)

Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.

2007-01-01

We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.

Assessing Visualization: An analysis of Chilean teachers’ guidelines

DEFF Research Database (Denmark)

Andrade-Molina, Melissa; Díaz, Leonora

2018-01-01

, this importance seems to fade when it comes to assessing students while learning school mathematics and geometry. We conducted an analysis of the official guidelines for the assessment school mathematics in Chile. The analysis of two of those guides is considered here. The results revealed that these guidelines...... do not help teachers while assessing visualization in schools; rather its focus is embedded in a tradition of training that leads to a reduction of space....

VAAPA: a web platform for visualization and analysis of alternative polyadenylation.

Science.gov (United States)

Guan, Jinting; Fu, Jingyi; Wu, Mingcheng; Chen, Longteng; Ji, Guoli; Quinn Li, Qingshun; Wu, Xiaohui

2015-02-01

Polyadenylation [poly(A)] is an essential process during the maturation of most mRNAs in eukaryotes. Alternative polyadenylation (APA) as an important layer of gene expression regulation has been increasingly recognized in various species. Here, a web platform for visualization and analysis of alternative polyadenylation (VAAPA) was developed. This platform can visualize the distribution of poly(A) sites and poly(A) clusters of a gene or a section of a chromosome. It can also highlight genes with switched APA sites among different conditions. VAAPA is an easy-to-use web-based tool that provides functions of poly(A) site query, data uploading, downloading, and APA sites visualization. It was designed in a multi-tier architecture and developed based on Smart GWT (Google Web Toolkit) using Java as the development language. VAAPA will be a valuable addition to the community for the comprehensive study of APA, not only by making the high quality poly(A) site data more accessible, but also by providing users with numerous valuable functions for poly(A) site analysis and visualization. Copyright © 2014 Elsevier Ltd. All rights reserved.

Magnitude and Causes of Low Vision Disability (Moderate and Severe Visual Impairment) among Students of Al-Noor Institute for the Blind in Al-Hassa, Saudi Arabia: A case series.

Science.gov (United States)

Al-Wadani, Fahad; Khandekar, Rajiv; Al-Hussain, Muneera A; Alkhawaja, Ahmed A; Khan, Mohammed Sarfaraz; Alsulaiman, Ramzy A

2012-02-01

This study aimed to estimate the magnitude and causes of low vision disability (severe visual impairment [SVI] and moderate visual impairment [MVI]) among students at Al-Noor Institute for the Blind (NIB) in Al-Hassa, Saudi Arabia in 2006. An optometrist conducted refraction of 122 eyes of the 61 students (27 boys and 34 girls) with MVI (vision visual acuity was ≥6/18 and in 28 (23%) eyes, it was visual impairment in 16 (13.1%) and 9 (7.4%) eyes. These students were prescribed optical and non-optical low vision aids. Retinal disease was the main cause of SVI and MVI in our series. Some students at Al-Noor Institute for the Blind have curable low vision conditions. Rehabilitation of low vision disability should be different from that offered to the absolutely blind.

Visualization analysis of author collaborations in schizophrenia research.

Science.gov (United States)

Wu, Ying; Duan, Zhiguang

2015-02-19

Schizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research. This study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from Science Citation Index Expanded (SCI Expanded) via Web of Science. CiteSpace III, an information visualization and analysis software, was used to make a visual analysis. Collaborative author networks within the field of schizophrenia were determined using published documents. We found that external author collaboration networks were more scattered while potential author collaboration networks were more compact. Results from hierarchical clustering analysis showed that the main collaborative field was genetic research in schizophrenia. Based on the results, authors belonging to different institutions and in different countries should be encouraged to collaborate in schizophrenia research. This will help researchers focus their studies on key issues, and allow each other to offer reasonable suggestions for making polices and providing scientific evidence to effectively diagnose, prevent, and cure schizophrenia.

Mapping air temperature using time series analysis of LST : The SINTESI approach

NARCIS (Netherlands)

Alfieri, S.M.; De Lorenzi, F.; Menenti, M.

2013-01-01

This paper presents a new procedure to map time series of air temperature (Ta) at fine spatial resolution using time series analysis of satellite-derived land surface temperature (LST) observations. The method assumes that air temperature is known at a single (reference) location such as in gridded

Visual and statistical analysis of 18F-FDG PET in primary progressive aphasia

International Nuclear Information System (INIS)

Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge; Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis

2015-01-01

Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)

Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.

Science.gov (United States)

Bhandari, Siddhartha; Bergmann, Neil; Jurdak, Raja; Kusy, Branislav

2017-05-26

Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2 °C and forecasting RMSE less than 1 °C.

Mathematical methods in time series analysis and digital image processing

CERN Document Server

Kurths, J; Maass, P; Timmer, J

2008-01-01

The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

Fractal analysis and nonlinear forecasting of indoor 222Rn time series

International Nuclear Information System (INIS)

Pausch, G.; Bossew, P.; Hofmann, W.; Steger, F.

1998-01-01

Fractal analyses of indoor 222 Rn time series were performed using different chaos theory based measurements such as time delay method, Hurst's rescaled range analysis, capacity (fractal) dimension, and Lyapunov exponent. For all time series we calculated only positive Lyapunov exponents which is a hint to chaos, while the Hurst exponents were well below 0.5, indicating antipersistent behaviour (past trends tend to reverse in the future). These time series were also analyzed with a nonlinear prediction method which allowed an estimation of the embedding dimensions with some restrictions, limiting the prediction to about three relative time steps. (orig.)

Online social media analysis and visualization

CERN Document Server

Kawash, Jalal

2015-01-01

This edited volume addresses the vast challenges of adapting Online Social Media (OSM) to developing research methods and applications. The topics cover generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, behavior detection, mining social content for common trends, identifying and ranking social content sources, building friend-comprehension tools, and many others. Each of the ten chapters tackle one or more of these issues by proposing new analysis methods or new visualization techn

GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

Ovis: A Framework for Visual Analysis of Ocean Forecast Ensembles.

Science.gov (United States)

Höllt, Thomas; Magdy, Ahmed; Zhan, Peng; Chen, Guoning; Gopalakrishnan, Ganesh; Hoteit, Ibrahim; Hansen, Charles D; Hadwiger, Markus

2014-08-01

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis.The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures.Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea.

The role of hemifield sector analysis in multifocal visual evoked potential objective perimetry in the early detection of glaucomatous visual field defects

Directory of Open Access Journals (Sweden)

Mousa MF

2013-05-01

Full Text Available Mohammad F Mousa,1 Robert P Cubbidge,2 Fatima Al-Mansouri,1 Abdulbari Bener3,41Department of Ophthalmology, Hamad Medical Corporation, Doha, Qatar; 2School of Life and Health Sciences, Aston University, Birmingham, UK; 3Department of Medical Statistics and Epidemiology, Hamad Medical Corporation, Department of Public Health, Weill Cornell Medical College, Doha, Qatar; 4Department Evidence for Population Health Unit, School of Epidemiology and Health Sciences, University of Manchester, Manchester, UKObjective: The purpose of this study was to examine the effectiveness of a new analysis method of mfVEP objective perimetry in the early detection of glaucomatous visual field defects compared to the gold standard technique.Methods and patients: Three groups were tested in this study; normal controls (38 eyes, glaucoma patients (36 eyes, and glaucoma suspect patients (38 eyes. All subjects underwent two standard 24-2 visual field tests: one with the Humphrey Field Analyzer and a single mfVEP test in one session. Analysis of the mfVEP results was carried out using the new analysis ­protocol: the hemifield sector analysis protocol.Results: Analysis of the mfVEP showed that the signal to noise ratio (SNR difference between superior and inferior hemifields was statistically significant between the three groups (analysis of variance, P < 0.001 with a 95% confidence interval, 2.82, 2.89 for normal group; 2.25, 2.29 for glaucoma suspect group; 1.67, 1.73 for glaucoma group. The difference between superior and inferior hemifield sectors and hemi-rings was statistically significant in 11/11 pair of sectors and hemi-rings in the glaucoma patients group (t-test P < 0.001, statistically significant in 5/11 pairs of sectors and hemi-rings in the glaucoma suspect group (t-test P < 0.01, and only 1/11 pair was statistically significant (t-test P < 0.9. The sensitivity and specificity of the hemifield sector analysis protocol in detecting glaucoma was 97% and 86

Long-Term Visual Prognosis of Peripheral Multifocal Chorioretinitis

NARCIS (Netherlands)

Ossewaarde-van Norel, J; ten Dam-van Loon, NH; de Boer, JH; Rothova, A.

2015-01-01

Purpose To report on the clinical manifestations, complications, and long-term visual prognosis of patients with peripheral multifocal chorioretinitis and to search for predictors for a lower visual outcome. Design Retrospective consecutive observational case series. Methods setting: Institutional.

QS Spiral: Visualizing Periodic Quantified Self Data

DEFF Research Database (Denmark)

Larsen, Jakob Eg; Cuttone, Andrea; Jørgensen, Sune Lehmann

2013-01-01

In this paper we propose an interactive visualization technique QS Spiral that aims to capture the periodic properties of quantified self data and let the user explore those recurring patterns. The approach is based on time-series data visualized as a spiral structure. The interactivity includes ...

The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

International Nuclear Information System (INIS)

Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia

2001-01-01

Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components

Age-related macular degeneration with choroidal neovascularization in the setting of pre-existing geographic atrophy and ranibizumab treatment. Analysis of a case series and revision paper

Directory of Open Access Journals (Sweden)

Miguel Hage Amaro

2012-12-01

Full Text Available PURPOSE: To report the response of choroidal neovascularization (CNV to intravitreal ranibizumab treatment in the setting of age-related macular degeneration (AMD with extensive pre-existing geographic atrophy (GA and a revision paper. METHODS: This is a revision paper and a retrospective case series of 10 eyes in nine consecutive patients from a photographic database. The patients were actively treated with ranibizumab for neovascular AMD with extensive pre-existing GA. Patients were included if they had GA at or adjacent to the foveal center that was present before the development of CNV. The best corrected visual acuity and optical coherence tomography (OCT analysis of the central macular thickness were recorded for each visit. Serial injections of ranibizumab were administered until there was resolution of any subretinal fluid clinically or on OCT. Data over the entire follow-up period were analyzed for overall visual and OCT changes. All patients had been followed for at least 2 years since diagnosis. RESULTS: The patients received an average of 6 ± 3 intravitreal injections over the treatment period. Eight eyes had reduced retinal thickening on OCT. On average, the central macular thickness was reduced by 94 ± 101 µm. Eight eyes had improvement of one or more lines of vision, where as one eye had dramatic vision loss and one had no change. The average treatment outcome for all patients was -0.07 ± 4.25 logMAR units, which corresponded to a gain of 0.6 ± 4.4 lines of Snellen acuity. The treatment resulted in a good anatomic response with the disappearance of the subretinal fluid, improved visual acuity, and stabilized final visual results. CONCLUSION: The results of this case series suggest that the use of an intravitreal anti-vascular endothelial growth factor (VEGF agent (ranibizumab for CNV in AMD with extensive pre-existing GA is effective. Our results are not as striking as published results from large-scale trials of anti

An Evaluation of a Computer-Based Training on the Visual Analysis of Single-Subject Data

Science.gov (United States)

Snyder, Katie

2013-01-01

Visual analysis is the primary method of analyzing data in single-subject methodology, which is the predominant research method used in the fields of applied behavior analysis and special education. Previous research on the reliability of visual analysis suggests that judges often disagree about what constitutes an intervention effect. Considering…

VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

Science.gov (United States)

Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

2017-10-02

Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Data Analysis and Visualization (IDAV) and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,' ' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

Energy Technology Data Exchange (ETDEWEB)

Ruebel, Oliver [Technical Univ. of Darmstadt (Germany)

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research covered in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

International Nuclear Information System (INIS)

Ruebel, Oliver

2009-01-01

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research covered in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle

FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data.

Directory of Open Access Journals (Sweden)

Takeru Uchiyama

Full Text Available Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree, a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the "Functional Tree map", a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree's analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree's capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree's capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research.

Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data

Directory of Open Access Journals (Sweden)

Heiko Balzter

2015-03-01

Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the

Time series analysis of gold production in Malaysia

Science.gov (United States)

Muda, Nora; Hoon, Lee Yuen

2012-05-01

Gold is a soft, malleable, bright yellow metallic element and unaffected by air or most reagents. It is highly valued as an asset or investment commodity and is extensively used in jewellery, industrial application, dentistry and medical applications. In Malaysia, gold mining is limited in several areas such as Pahang, Kelantan, Terengganu, Johor and Sarawak. The main purpose of this case study is to obtain a suitable model for the production of gold in Malaysia. The model can also be used to predict the data of Malaysia's gold production in the future. Box-Jenkins time series method was used to perform time series analysis with the following steps: identification, estimation, diagnostic checking and forecasting. In addition, the accuracy of prediction is tested using mean absolute percentage error (MAPE). From the analysis, the ARIMA (3,1,1) model was found to be the best fitted model with MAPE equals to 3.704%, indicating the prediction is very accurate. Hence, this model can be used for forecasting. This study is expected to help the private and public sectors to understand the gold production scenario and later plan the gold mining activities in Malaysia.

Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

Directory of Open Access Journals (Sweden)

Ting-quan Deng

2014-01-01

Full Text Available In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios.

ConnectomeExplorer: Query-guided visual analysis of large volumetric neuroscience data

KAUST Repository

Beyer, Johanna

2013-12-01

This paper presents ConnectomeExplorer, an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy (EM) data sets in connectomics research. Our system incorporates a knowledge-based query algebra that supports the interactive specification of dynamically evaluated queries, which enable neuroscientists to pose and answer domain-specific questions in an intuitive manner. Queries are built step by step in a visual query builder, building more complex queries from combinations of simpler queries. Our application is based on a scalable volume visualization framework that scales to multiple volumes of several teravoxels each, enabling the concurrent visualization and querying of the original EM volume, additional segmentation volumes, neuronal connectivity, and additional meta data comprising a variety of neuronal data attributes. We evaluate our application on a data set of roughly one terabyte of EM data and 750 GB of segmentation data, containing over 4,000 segmented structures and 1,000 synapses. We demonstrate typical use-case scenarios of our collaborators in neuroscience, where our system has enabled them to answer specific scientific questions using interactive querying and analysis on the full-size data for the first time. © 1995-2012 IEEE.

Barcode server: a visualization-based genome analysis system.

Directory of Open Access Journals (Sweden)

Fenglou Mao

Full Text Available We have previously developed a computational method for representing a genome as a barcode image, which makes various genomic features visually apparent. We have demonstrated that this visual capability has made some challenging genome analysis problems relatively easy to solve. We have applied this capability to a number of challenging problems, including (a identification of horizontally transferred genes, (b identification of genomic islands with special properties and (c binning of metagenomic sequences, and achieved highly encouraging results. These application results inspired us to develop this barcode-based genome analysis server for public service, which supports the following capabilities: (a calculation of the k-mer based barcode image for a provided DNA sequence; (b detection of sequence fragments in a given genome with distinct barcodes from those of the majority of the genome, (c clustering of provided DNA sequences into groups having similar barcodes; and (d homology-based search using Blast against a genome database for any selected genomic regions deemed to have interesting barcodes. The barcode server provides a job management capability, allowing processing of a large number of analysis jobs for barcode-based comparative genome analyses. The barcode server is accessible at http://csbl1.bmb.uga.edu/Barcode.

The singular nature of auditory and visual scene analysis in autism

OpenAIRE

Lin, I.-Fan; Shirama, Aya; Kato, Nobumasa; Kashino, Makio

2017-01-01

Individuals with autism spectrum disorder often have difficulty acquiring relevant auditory and visual information in daily environments, despite not being diagnosed as hearing impaired or having low vision. Resent psychophysical and neurophysiological studies have shown that autistic individuals have highly specific individual differences at various levels of information processing, including feature extraction, automatic grouping and top-down modulation in auditory and visual scene analysis...

Visualization of fuel rod burnup analysis by Scilab

International Nuclear Information System (INIS)

Tsai, Chiung-Wen

2013-01-01

The goal of this technical note is to provide an alternative, the freeware Scilab, by which means we may construct custom GUIs and distribute them without extra constrains and cost. A post-processor has been constructed by Scilab to visualize the fuel rod burnup analysis data calculated by FRAPCON-3.4. This post-processor incorporates a graphical user interface (GUI), providing users a rapid overview of the characteristics of the numerical results with 2-D and 3-D graphs, as well as the animations of fuel temperature distribution. An assessment case input file provided by FRAPCON user group was applied to demonstrate the construction of a post-processor with GUI by object-oriented GUI tool, as well as the capability of visualization functions of Scilab

Visualization of fuel rod burnup analysis by Scilab

Energy Technology Data Exchange (ETDEWEB)

Tsai, Chiung-Wen, E-mail: d937121@oz.nthu.edu.tw

2013-12-15

The goal of this technical note is to provide an alternative, the freeware Scilab, by which means we may construct custom GUIs and distribute them without extra constrains and cost. A post-processor has been constructed by Scilab to visualize the fuel rod burnup analysis data calculated by FRAPCON-3.4. This post-processor incorporates a graphical user interface (GUI), providing users a rapid overview of the characteristics of the numerical results with 2-D and 3-D graphs, as well as the animations of fuel temperature distribution. An assessment case input file provided by FRAPCON user group was applied to demonstrate the construction of a post-processor with GUI by object-oriented GUI tool, as well as the capability of visualization functions of Scilab.

Pulmonary nodule characterization: A comparison of conventional with quantitative and visual semi-quantitative analyses using contrast enhancement maps

International Nuclear Information System (INIS)

Petkovska, Iva; Shah, Sumit K.; McNitt-Gray, Michael F.; Goldin, Jonathan G.; Brown, Matthew S.; Kim, Hyun J.; Brown, Kathleen; Aberle, Denise R.

2006-01-01

Purpose: To determine whether conventional nodule densitometry or analysis based on contrast enhancement maps of indeterminate lung nodules imaged with contrast-enhanced CT can distinguish benign from malignant lung nodules. Materials and method: Thin section, contrast-enhanced CT (baseline, and post-contrast series acquired at 45, 90,180, and 360 s) was performed on 29 patients with indeterminate lung nodules (14 benign, 15 malignant). A thoracic radiologist identified the boundary of each nodule using semi-automated contouring to form a 3D region-of-interest (ROI) on each image series. The post-contrast series having the maximum mean enhancement was then volumetrically registered to the baseline series. The two series were subtracted volumetrically and the subtracted voxels were quantized into seven color-coded bins, forming a contrast enhancement map (CEM). Conventional nodule densitometry was performed to obtain the maximum difference in mean enhancement values for each nodule from a circular ROI. Three thoracic radiologists performed visual semi-quantitative analysis of each nodule, scoring each map for: (a) magnitude and (b) heterogeneity of enhancement throughout the entire volume of the nodule on a five-point scale. Receiver operator characteristic (ROC) analysis was conducted on these features to evaluate their diagnostic efficacy. Finally, 14 quantitative texture features were calculated for each map. A statistical analysis was performed to combine the 14 texture features to a single factor. ROC analysis of the derived aggregate factor was done as an indicator of malignancy. All features were analyzed for differences between benign and malignant nodules. Results: Using 15 HU as a threshold, 93% (14/15) of malignant and 79% (11/14) of benign nodules demonstrated enhancement. The ROC curve when higher values of enhancement indicate malignancy was generated and area under the curve (AUC) was 0.76. The visually scored magnitude of enhancement was found to be

A Python-based interface to examine motions in time series of solar images

Science.gov (United States)

Campos-Rozo, J. I.; Vargas Domínguez, S.

2017-10-01

Python is considered to be a mature programming language, besides of being widely accepted as an engaging option for scientific analysis in multiple areas, as will be presented in this work for the particular case of solar physics research. SunPy is an open-source library based on Python that has been recently developed to furnish software tools to solar data analysis and visualization. In this work we present a graphical user interface (GUI) based on Python and Qt to effectively compute proper motions for the analysis of time series of solar data. This user-friendly computing interface, that is intended to be incorporated to the Sunpy library, uses a local correlation tracking technique and some extra tools that allows the selection of different parameters to calculate, vizualize and analyze vector velocity fields of solar data, i.e. time series of solar filtergrams and magnetograms.

A Componential Analysis of Visual Attention in Children With ADHD.

Science.gov (United States)

McAvinue, Laura P; Vangkilde, Signe; Johnson, Katherine A; Habekost, Thomas; Kyllingsbæk, Søren; Bundesen, Claus; Robertson, Ian H

2015-10-01

Inattentive behaviour is a defining characteristic of ADHD. Researchers have wondered about the nature of the attentional deficit underlying these symptoms. The primary purpose of the current study was to examine this attentional deficit using a novel paradigm based upon the Theory of Visual Attention (TVA). The TVA paradigm enabled a componential analysis of visual attention through the use of a mathematical model to estimate parameters relating to attentional selectivity and capacity. Children's ability to sustain attention was also assessed using the Sustained Attention to Response Task. The sample included a comparison between 25 children with ADHD and 25 control children aged 9-13. Children with ADHD had significantly impaired sustained attention and visual processing speed but intact attentional selectivity, perceptual threshold and visual short-term memory capacity. The results of this study lend support to the notion of differential impairment of attentional functions in children with ADHD. © 2012 SAGE Publications.

Visual Task Demands and the Auditory Mismatch Negativity: An Empirical Study and a Meta-Analysis.

Science.gov (United States)

Wiens, Stefan; Szychowska, Malina; Nilsson, Mats E

2016-01-01

Because the auditory system is particularly useful in monitoring the environment, previous research has examined whether task-irrelevant, auditory distracters are processed even if subjects focus their attention on visual stimuli. This research suggests that attentionally demanding visual tasks decrease the auditory mismatch negativity (MMN) to simultaneously presented auditory distractors. Because a recent behavioral study found that high visual perceptual load decreased detection sensitivity of simultaneous tones, we used a similar task (n = 28) to determine if high visual perceptual load would reduce the auditory MMN. Results suggested that perceptual load did not decrease the MMN. At face value, these nonsignificant findings may suggest that effects of perceptual load on the MMN are smaller than those of other demanding visual tasks. If so, effect sizes should differ systematically between the present and previous studies. We conducted a selective meta-analysis of published studies in which the MMN was derived from the EEG, the visual task demands were continuous and varied between high and low within the same task, and the task-irrelevant tones were presented in a typical oddball paradigm simultaneously with the visual stimuli. Because the meta-analysis suggested that the present (null) findings did not differ systematically from previous findings, the available evidence was combined. Results of this meta-analysis confirmed that demanding visual tasks reduce the MMN to auditory distracters. However, because the meta-analysis was based on small studies and because of the risk for publication biases, future studies should be preregistered with large samples (n > 150) to provide confirmatory evidence for the results of the present meta-analysis. These future studies should also use control conditions that reduce confounding effects of neural adaptation, and use load manipulations that are defined independently from their effects on the MMN.

Visual Task Demands and the Auditory Mismatch Negativity: An Empirical Study and a Meta-Analysis

Science.gov (United States)

Wiens, Stefan; Szychowska, Malina; Nilsson, Mats E.

2016-01-01

Because the auditory system is particularly useful in monitoring the environment, previous research has examined whether task-irrelevant, auditory distracters are processed even if subjects focus their attention on visual stimuli. This research suggests that attentionally demanding visual tasks decrease the auditory mismatch negativity (MMN) to simultaneously presented auditory distractors. Because a recent behavioral study found that high visual perceptual load decreased detection sensitivity of simultaneous tones, we used a similar task (n = 28) to determine if high visual perceptual load would reduce the auditory MMN. Results suggested that perceptual load did not decrease the MMN. At face value, these nonsignificant findings may suggest that effects of perceptual load on the MMN are smaller than those of other demanding visual tasks. If so, effect sizes should differ systematically between the present and previous studies. We conducted a selective meta-analysis of published studies in which the MMN was derived from the EEG, the visual task demands were continuous and varied between high and low within the same task, and the task-irrelevant tones were presented in a typical oddball paradigm simultaneously with the visual stimuli. Because the meta-analysis suggested that the present (null) findings did not differ systematically from previous findings, the available evidence was combined. Results of this meta-analysis confirmed that demanding visual tasks reduce the MMN to auditory distracters. However, because the meta-analysis was based on small studies and because of the risk for publication biases, future studies should be preregistered with large samples (n > 150) to provide confirmatory evidence for the results of the present meta-analysis. These future studies should also use control conditions that reduce confounding effects of neural adaptation, and use load manipulations that are defined independently from their effects on the MMN. PMID:26741815

Analysis and implementation of LLC-T series parallel resonant ...

African Journals Online (AJOL)

A prototype 300 W, 100 kHz converter is designed and built to experimentally demonstrate, dynamic and steady state performance for the LLC-T series parallel resonant converter. A comparative study is performed between experimental results and the simulation studies. The analysis shows that the output of converter is ...

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

International Nuclear Information System (INIS)

Munoz-Diosdado, A

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

Energy Technology Data Exchange (ETDEWEB)

Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

Visual Analysis as a design and decision-making tool in the development of a quarry

Science.gov (United States)

Randall Boyd Fitzgerald

1979-01-01

In order to obtain local and state government approvals, an environmental impact analysis of the mining and reclamation of a proposed hard rock quarry was required. High visibility of the proposed mining area from the adjacent community required a visual impact analysis in the planning and design of the project. The Visual Analysis defined design criteria for the...

Visual Data Analysis as an Integral Part of Environmental Management

Energy Technology Data Exchange (ETDEWEB)

Meyer, Joerg; Bethel, E. Wes; Horsman, Jennifer L.; Hubbard, Susan S.; Krishnan, Harinarayan; Romosan,, Alexandru; Keating, Elizabeth H.; Monroe, Laura; Strelitz, Richard; Moore, Phil; Taylor, Glenn; Torkian, Ben; Johnson, Timothy C.; Gorton, Ian

2012-10-01

The U.S. Department of Energy's (DOE) Office of Environmental Management (DOE/EM) currently supports an effort to understand and predict the fate of nuclear contaminants and their transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing nuclear waste sites, to simulate their behavior and to extrapolate it into the future. We use visualization as an integral part in each step of this process. In the first step, visualization is used to verify model setup and to estimate critical parameters. High-performance computing simulations of contaminant transport produces massive amounts of data, which is then analyzed using visualization software specifically designed for parallel processing of large amounts of structured and unstructured data. Finally, simulation results are validated by comparing simulation results to measured current and historical field data. We describe in this article how visual analysis is used as an integral part of the decision-making process in the planning of ongoing and future treatment options for the contaminated nuclear waste sites. Lessons learned from visually analyzing our large-scale simulation runs will also have an impact on deciding on treatment measures for other contaminated sites.

Brain SPECT in mesial temporal lobe epilepsy: comparison between visual analysis and SPM (Statistical Parametric Mapping)

Energy Technology Data Exchange (ETDEWEB)

Amorim, Barbara Juarez; Ramos, Celso Dario; Santos, Allan Oliveira dos; Lima, Mariana da Cunha Lopes de; Camargo, Edwaldo Eduardo; Etchebehere, Elba Cristina Sa de Camargo, E-mail: juarezbarbara@hotmail.co [State University of Campinas (UNICAMP), SP (Brazil). School of Medical Sciences. Dept. of Radiology; Min, Li Li; Cendes, Fernando [State University of Campinas (UNICAMP), SP (Brazil). School of Medical Sciences. Dept. of Neurology

2010-04-15

Objective: to compare the accuracy of SPM and visual analysis of brain SPECT in patients with mesial temporal lobe epilepsy (MTLE). Method: interictal and ictal SPECTs of 22 patients with MTLE were performed. Visual analysis were performed in interictal (VISUAL(inter)) and ictal (VISUAL(ictal/inter)) studies. SPM analysis consisted of comparing interictal (SPM(inter)) and ictal SPECTs (SPM(ictal)) of each patient to control group and by comparing perfusion of temporal lobes in ictal and interictal studies among themselves (SPM(ictal/inter)). Results: for detection of the epileptogenic focus, the sensitivities were as follows: VISUAL(inter)=68%; VISUAL(ictal/inter)=100%; SPM(inter)=45%; SPM(ictal)=64% and SPM(ictal/inter)=77%. SPM was able to detect more areas of hyperperfusion and hypoperfusion. Conclusion: SPM did not improve the sensitivity to detect epileptogenic focus. However, SPM detected different regions of hypoperfusion and hyperperfusion and is therefore a helpful tool for better understand pathophysiology of seizures in MTLE. (author)

Brain SPECT in mesial temporal lobe epilepsy: comparison between visual analysis and SPM (Statistical Parametric Mapping)

International Nuclear Information System (INIS)

Amorim, Barbara Juarez; Ramos, Celso Dario; Santos, Allan Oliveira dos; Lima, Mariana da Cunha Lopes de; Camargo, Edwaldo Eduardo; Etchebehere, Elba Cristina Sa de Camargo; Min, Li Li; Cendes, Fernando

2010-01-01

Objective: to compare the accuracy of SPM and visual analysis of brain SPECT in patients with mesial temporal lobe epilepsy (MTLE). Method: interictal and ictal SPECTs of 22 patients with MTLE were performed. Visual analysis were performed in interictal (VISUAL(inter)) and ictal (VISUAL(ictal/inter)) studies. SPM analysis consisted of comparing interictal (SPM(inter)) and ictal SPECTs (SPM(ictal)) of each patient to control group and by comparing perfusion of temporal lobes in ictal and interictal studies among themselves (SPM(ictal/inter)). Results: for detection of the epileptogenic focus, the sensitivities were as follows: VISUAL(inter)=68%; VISUAL(ictal/inter)=100%; SPM(inter)=45%; SPM(ictal)=64% and SPM(ictal/inter)=77%. SPM was able to detect more areas of hyperperfusion and hypoperfusion. Conclusion: SPM did not improve the sensitivity to detect epileptogenic focus. However, SPM detected different regions of hypoperfusion and hyperperfusion and is therefore a helpful tool for better understand pathophysiology of seizures in MTLE. (author)

Ovis: A framework for visual analysis of ocean forecast ensembles

KAUST Repository

Hollt, Thomas; Magdy, Ahmed; Zhan, Peng; Chen, Guoning; Gopalakrishnan, Ganesh; Hoteit, Ibrahim; Hansen, Charles D.; Hadwiger, Markus

2014-01-01

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis.The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures.Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea. © 1995-2012 IEEE.

Ovis: A framework for visual analysis of ocean forecast ensembles

KAUST Repository

Hollt, Thomas

2014-08-01

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis.The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures.Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea. © 1995-2012 IEEE.

A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis

Directory of Open Access Journals (Sweden)

José Alberto Benítez

2017-01-01

Full Text Available There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data.

Visual and statistical analysis of {sup 18}F-FDG PET in primary progressive aphasia

Energy Technology Data Exchange (ETDEWEB)

Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge [Hospital Clinico San Carlos, Department of Neurology, Madrid (Spain); Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis [San Carlos Health Research Institute (IdISSC) Complutense University of Madrid, Department of Nuclear Medicine, Hospital Clinico San Carlos, Madrid (Spain)

2015-05-01

Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)

Content and user-based music visual analysis

Science.gov (United States)

Guo, Xiaochun; Tang, Lei

2015-12-01

In recent years, people's ability to collect music got enhanced greatly. Many people who prefer listening music offline even stored thousands of music on their local storage or portable device. However, their ability to deal with music information has not been improved accordingly, which results in two problems. One is how to find out the favourite songs from large music dataset and satisfy different individuals. The other one is how to compose a play list quickly. To solve these problems, the authors proposed a content and user-based music visual analysis approach. We first developed a new recommendation algorithm based on the content of music and user's behaviour, which satisfy individual's preference. Then, we make use of visualization and interaction tools to illustrate the relationship between songs and help people compose a suitable play list. At the end of this paper, a survey is mentioned to show that our system is available and effective.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

International Nuclear Information System (INIS)

Jafri, Y.Z.; Kamal, L.

2007-01-01

Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

Science.gov (United States)

Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.

Visual physics analysis-from desktop to physics analysis at your fingertips

International Nuclear Information System (INIS)

Bretz, H-P; Erdmann, M; Fischer, R; Hinzmann, A; Klingebiel, D; Komm, M; Lingemann, J; Rieger, M; Müller, G; Steggemann, J; Winchen, T

2012-01-01

Visual Physics Analysis (VISPA) is an analysis environment with applications in high energy and astroparticle physics. Based on a data-flow-driven paradigm, it allows users to combine graphical steering with self-written C++ and Python modules. This contribution presents new concepts integrated in VISPA: layers, convenient analysis execution, and web-based physics analysis. While the convenient execution offers full flexibility to vary settings for the execution phase of an analysis, layers allow to create different views of the analysis already during its design phase. Thus, one application of layers is to define different stages of an analysis (e.g. event selection and statistical analysis). However, there are other use cases such as to independently optimize settings for different types of input data in order to guide all data through the same analysis flow. The new execution feature makes job submission to local clusters as well as the LHC Computing Grid possible directly from VISPA. Web-based physics analysis is realized in the VISPA-Web project, which represents a whole new way to design and execute analyses via a standard web browser.

Interactive visual analysis of nuclear data with ZVView

International Nuclear Information System (INIS)

Zerkin, Viktor

2002-01-01

This paper describes the cross section graphics software package ZVVIEW that was developed for the evaluators to perform efficient interactive visual analysis of experimental and theoretical nuclear data. ZVVIEW is a very powerful and complete package that simplifies the presentation of nuclear cross section data. A CD-ROM version of this computer package is available from the IAEA-NDS on request. (a.n.)

Language as the visual: Exploring the intersection of linguistic and visual language in manga

Directory of Open Access Journals (Sweden)

Giancarla Unser-Schutz

2011-03-01

Full Text Available In manga studies, a distinction is made between linguistic text (language and visual language. However, because linguistic text is mediated by visual structures, there is a a tendency to assume that it is a secondary element. I would argue, however, that examination of both languages might give a better idea of how manga functions, and start that process here by looking at two manga text types: handwritten lines, thoughts and authorial comments. Visually differentiated from other texts, and more common in series for girls (shōjo-manga, I compare them with Ōtsuka's (1994 highly-visual monologues from 1970s/1980s shōjo-manga, and demonstrate similarities to Takeuchi's (2005 mediator and spectator characters, and argue that these texts offer a sense of closeness to authors while also visually-coding data in terms of relevance. While non-essential secondary text, their visual-encoding offers a space of dynamic interpretation, with readerships able to ignore or read them as per their needs.

Analysis of historical series of industrial demand of energy; Analisi delle serie storiche dei consumi energetici dell`industria

Energy Technology Data Exchange (ETDEWEB)

Moauro, F. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

1995-03-01

This paper reports a short term analysis of the Italian demand for energy fonts and a check of a statistic model supposing the industrial demand for energy fonts as a function of prices and production, according to neoclassic neoclassic micro economic theory. To this pourpose monthly time series of industrial consumption of main energy fonts in 6 sectors, industrial production indexes in the same sectors and indexes of energy prices (coal, natural gas, oil products, electricity) have been used. The statistic methodology refers to modern analysis of time series and specifically to transfer function models. These ones permit rigorous identification and representation of the most important dynamic relations between dependent variables (production and prices), as relation of an input-output system. The results have shown an important positive correlation between energy consumption with prices. Furthermore, it has been shown the reliability of forecasts and their use as monthly energy indicators.

Time Series Analysis of Wheat flour Price Shocks in Pakistan: A Case Analysis

OpenAIRE

Asad Raza Abdi; Ali Hassan Halepoto; Aisha Bashir Shah; Faiz M. Shaikh

2013-01-01

The current research investigates the wheat flour Price Shocks in Pakistan: A case analysis. Data was collected by using secondary sources by using Time series Analysis, and data were analyzed by using SPSS-20 version. It was revealed that the price of wheat flour increases from last four decades, and trend of price shocks shows that due to certain market variation and supply and demand shocks also play a positive relationship in price shocks in the wheat prices. It was further revealed th...

Time series clustering analysis of health-promoting behavior

Science.gov (United States)

Yang, Chi-Ta; Hung, Yu-Shiang; Deng, Guang-Feng

2013-10-01

Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.

Capturing Structure Implicitly from Time-Series having Limited Data

OpenAIRE

Emaasit, Daniel; Johnson, Matthew

2018-01-01

Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have well-calibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeabl...

Fractal time series analysis of postural stability in elderly and control subjects

Directory of Open Access Journals (Sweden)

Doussot Michel

2007-05-01

Full Text Available Abstract Background The study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H, may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA and Stabilogram Diffusion Analysis (SDA for elderly and control subjects, as well as evaluating the effect of recording duration. Methods Centre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC was used as a measure of reliability. Results Both SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA. Conclusion Both methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.

A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series

Directory of Open Access Journals (Sweden)

Charmaine eDemanuele

2015-10-01

Full Text Available Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from fMRI blood oxygenation level dependent (BOLD time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC, but not in the primary visual cortex (V1. Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel

Bayesian near-boundary analysis in basic macroeconomic time series models

NARCIS (Netherlands)

M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)

2008-01-01

textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic

A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data

Directory of Open Access Journals (Sweden)

Johannes Jordan

2016-01-01

Full Text Available Multispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality to a wider array of applications like medical diagnosis, agriculture, and cultural heritage. This necessitates new tools that allow general analysis of the image data and are intuitive to users who are new to hyperspectral imaging. We introduce a novel framework that bundles new interactive visualization techniques with powerful algorithms and is accessible through an efficient and intuitive graphical user interface. We visualize the spectral distribution of an image via parallel coordinates with a strong link to traditional visualization techniques, enabling new paradigms in hyperspectral image analysis that focus on interactive raw data exploration. We combine novel methods for supervised segmentation, global clustering, and nonlinear false-color coding to assist in the visual inspection. Our framework coined Gerbil is open source and highly modular, building on established methods and being easily extensible for application-specific needs. It satisfies the need for a general, consistent software framework that tightly integrates analysis algorithms with an intuitive, modern interface to the raw image data and algorithmic results. Gerbil finds its worldwide use in academia and industry alike with several thousand downloads originating from 45 countries.

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

Directory of Open Access Journals (Sweden)

Carolyn D Langen

Full Text Available Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1 middle-aged versus elderly subjects; and (2 patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only

Arab drama series content analysis from a transnational Arab identity perspective

Directory of Open Access Journals (Sweden)

Joelle Chamieh

2016-04-01

Full Text Available The scientific contribution in deciphering drama series falls under the discipline of understanding the narratology of distinctive cultures and traditions within specific contexts of certain societies. This article spells out the interferences deployed by the provocations that are induced through the functions of values in modeling societies which are projected through the transmission of media. The proposed operational model consists of providing an à priori design of common Arab values assimilated into an innovative grid analysis code book that has enabled the execution of a systematic and reliable approach to the quantitative content analysis performance. Additionally, a more thorough qualitative content analysis has been implemented in terms of narratolgy where actions have been evaluated based on the grid analysis code book for a clearer perception of Arab values depicted in terms of their context within the Arab drama milieu. This approach has been deployed on four Arab drama series covering the transnational/national and non-divisive/divisive media aspects in the intention of extracting the transmitted values from a common identity perspective for cause of divulging Arab people’s expectancies.

Visual intelligence Microsoft tools and techniques for visualizing data

CERN Document Server

Stacey, Mark; Jorgensen, Adam

2013-01-01

Go beyond design concepts and learn to build state-of-the-art visualizations The visualization experts at Microsoft's Pragmatic Works have created a full-color, step-by-step guide to building specific types of visualizations. The book thoroughly covers the Microsoft toolset for data analysis and visualization, including Excel, and explores best practices for choosing a data visualization design, selecting tools from the Microsoft stack, and building a dynamic data visualization from start to finish. You'll examine different types of visualizations, their strengths and weaknesses, a

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

Science.gov (United States)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin

Science.gov (United States)

zhangli, Sun; xiufang, Zhu; yaozhong, Pan

2016-04-01

Accurate estimation of flood frequency is key to effective, nationwide flood damage abatement programs. The partial duration series (PDS) method is widely used in hydrologic studies because it considers all events above a certain threshold level as compared to the annual maximum series (AMS) method, which considers only the annual maximum value. However, the PDS has a drawback in that it is difficult to define the thresholds and maintain an independent and identical distribution of the partial duration time series; this drawback is discussed in this paper. The Ganjiang River is the seventh largest tributary of the Yangtze River, the longest river in China. The Ganjiang River covers a drainage area of 81,258 km2 at the Wanzhou hydrologic station as the basin outlet. In this work, 56 years of daily flow data (1954-2009) from the Wanzhou station were used to analyze flood frequency, and the Pearson-III model was employed as the hydrologic probability distribution. Generally, three tasks were accomplished: (1) the threshold of PDS by percentile rank of daily runoff was obtained; (2) trend analysis of the flow series was conducted using PDS; and (3) flood frequency analysis was conducted for partial duration flow series. The results showed a slight upward trend of the annual runoff in the Ganjiang River basin. The maximum flow with a 0.01 exceedance probability (corresponding to a 100-year flood peak under stationary conditions) was 20,000 m3/s, while that with a 0.1 exceedance probability was 15,000 m3/s. These results will serve as a guide to hydrological engineering planning, design, and management for policymakers and decision makers associated with hydrology.

Special Issue of Selected Papers from Visualization and Data Analysis 2011

Science.gov (United States)

Kao, David L.; Wong, Pak Chung

2012-01-01

This special issue features the best papers that were selected from the 18th SPIE Conference on Visualization and Data Analysis (VDA 2011). This annual conference is a major international forum for researchers and practitioners interested in data visualization and analytics research, development, and applications. VDA 2011 received 42 high-quality submissions from around the world. Twenty-four papers were selected for full conference papers. The top five papers have been expanded and reviewed for this special issue.

Efficient visual object and word recognition relies on high spatial frequency coding in the left posterior fusiform gyrus: evidence from a case-series of patients with ventral occipito-temporal cortex damage.

Science.gov (United States)

Roberts, Daniel J; Woollams, Anna M; Kim, Esther; Beeson, Pelagie M; Rapcsak, Steven Z; Lambon Ralph, Matthew A

2013-11-01

Recent visual neuroscience investigations suggest that ventral occipito-temporal cortex is retinotopically organized, with high acuity foveal input projecting primarily to the posterior fusiform gyrus (pFG), making this region crucial for coding high spatial frequency information. Because high spatial frequencies are critical for fine-grained visual discrimination, we hypothesized that damage to the left pFG should have an adverse effect not only on efficient reading, as observed in pure alexia, but also on the processing of complex non-orthographic visual stimuli. Consistent with this hypothesis, we obtained evidence that a large case series (n = 20) of patients with lesions centered on left pFG: 1) Exhibited reduced sensitivity to high spatial frequencies; 2) demonstrated prolonged response latencies both in reading (pure alexia) and object naming; and 3) were especially sensitive to visual complexity and similarity when discriminating between novel visual patterns. These results suggest that the patients' dual reading and non-orthographic recognition impairments have a common underlying mechanism and reflect the loss of high spatial frequency visual information normally coded in the left pFG.

Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

Time Series in Education: The Analysis of Daily Attendance in Two High Schools

Science.gov (United States)

Koopmans, Matthijs

2011-01-01

This presentation discusses the use of a time series approach to the analysis of daily attendance in two urban high schools over the course of one school year (2009-10). After establishing that the series for both schools were stationary, they were examined for moving average processes, autoregression, seasonal dependencies (weekly cycles),…

Attention and visual memory in visualization and computer graphics.

Science.gov (United States)

Healey, Christopher G; Enns, James T

2012-07-01

A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we "see" details in an image can directly impact a viewer's efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics.

Intersensory Function in Newborns: Effect of Sound on Visual Preferences.

Science.gov (United States)

Lawson, Katharine Rieke; Turkewitz, Gerald

1980-01-01

Newborn infants' fixation of a graduated series of visual stimuli significantly differed in the absence and presence of white-noise bursts. Relative to the no-sound condition, sound resulted in the infants' tendency to look more at the low-intensity visual stimulus and less at the high- intensity visual stimulus. (Author/DB)

Information theoretic analysis of canny edge detection in visual communication

Science.gov (United States)

Jiang, Bo; Rahman, Zia-ur

2011-06-01

In general edge detection evaluation, the edge detectors are examined, analyzed, and compared either visually or with a metric for specific an application. This analysis is usually independent of the characteristics of the image-gathering, transmission and display processes that do impact the quality of the acquired image and thus, the resulting edge image. We propose a new information theoretic analysis of edge detection that unites the different components of the visual communication channel and assesses edge detection algorithms in an integrated manner based on Shannon's information theory. The edge detection algorithm here is considered to achieve high performance only if the information rate from the scene to the edge approaches the maximum possible. Thus, by setting initial conditions of the visual communication system as constant, different edge detection algorithms could be evaluated. This analysis is normally limited to linear shift-invariant filters so in order to examine the Canny edge operator in our proposed system, we need to estimate its "power spectral density" (PSD). Since the Canny operator is non-linear and shift variant, we perform the estimation for a set of different system environment conditions using simulations. In our paper we will first introduce the PSD of the Canny operator for a range of system parameters. Then, using the estimated PSD, we will assess the Canny operator using information theoretic analysis. The information-theoretic metric is also used to compare the performance of the Canny operator with other edge-detection operators. This also provides a simple tool for selecting appropriate edgedetection algorithms based on system parameters, and for adjusting their parameters to maximize information throughput.

A Reception Analysis on the Youth Audiences of TV Series in Marivan

Directory of Open Access Journals (Sweden)

Omid Karimi

2014-03-01

Full Text Available The aim of this article is to describe the role of foreign media as the agitators of popular culture. For that with reception analysis it’s pay to describe decoding of youth audiences about this series. Globalization theory and Reception in Communication theory are formed the theoretical system of current article. The methodology in this research is qualitative one, and two techniques as in-depth interview and observation are used for data collection. The results show different people based on individual features, social and cultural backgrounds have inclination toward special characters and identify with them. This inclination so far the audience fallow the series because of his/her favorite character. Also there is a great compatibility between audience backgrounds and their receptions. A number of audience have criticized the series and point out the negative consequences on its society. However, seeing the series continue; really they prefer watching series enjoying to risks of it.

Modern Methods of Multidimensional Data Visualization: Analysis, Classification, Implementation, and Applications in Technical Systems

Directory of Open Access Journals (Sweden)

I. K. Romanova

2016-01-01

Full Text Available The article deals with theoretical and practical aspects of solving the problem of visualization of multidimensional data as an effective means of multivariate analysis of systems. Several classifications are proposed for visualization techniques, according to data types, visualization objects, the method of transformation of coordinates and data. To represent classification are used charts with links to the relevant work. The article also proposes two classifications of modern trends in display technology, including integration of visualization techniques as one of the modern trends of development, along with the introduction of interactive technologies and the dynamics of development processes. It describes some approaches to the visualization problem, which are concerned with fulfilling the needs. The needs are generated by the relevant tasks such as information retrieval in global networks, development of bioinformatics, study and control of business processes, development of regions, etc. The article highlights modern visualization tools, which are capable of improving the efficiency of the multivariate analysis and searching for solutions in multi-objective optimization of technical systems, but are not very actively used for such studies. These are horizontal graphs, graphics "quantile-quantile", etc. The paper proposes to use Choropleth cards traditionally used in cartography for simultaneous presentation of the distribution parameters of several criteria in the space. It notes that visualizations of graphs in network applications can be more actively used to describe the control system. The article suggests using the heat maps to provide graphical representation of the sensitivity of the system quality criteria under variations of options (multivariate analysis of technical systems. It also mentions that it is useful to extend the supervising heat maps to the task of estimating quality of identify in constructing system models. A

Visual analysis of transcriptome data in the context of anatomical structures and biological networks

Directory of Open Access Journals (Sweden)

Astrid eJunker

2012-11-01

Full Text Available The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly increasing due to extensive technological developments. Here we present methods for advanced visualization and intuitive exploration of transcriptomics data as necessary prerequisites in order to facilitate the gain of biological knowledge. Color-coding of structural images based on the expression level enables a fast visual data analysis in the background of the examined biological system. The network-based exploration of these visualizations allows for comparative analysis of genes with specific transcript patterns and supports the extraction of functional relationships even from large datasets. In order to illustrate the presented methods, the tool HIVE was applied for visualization and exploration of database-retrieved expression data for master regulators of Arabidopsis thaliana flower and seed development in the context of corresponding tissue-specific regulatory networks.

Time series analysis of monthly pulpwood use in the Northeast

Science.gov (United States)

James T. Bones

1980-01-01

Time series analysis was used to develop a model that depicts pulpwood use in the Northeast. The model is useful in forecasting future pulpwood requirements (short term) or monitoring pulpwood-use activity in relation to past use patterns. The model predicted a downturn in use during 1980.

Time Series Analysis Based on Running Mann Whitney Z Statistics

Science.gov (United States)

A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...

Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

NARCIS (Netherlands)

Velsink, H.

2016-01-01

Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to formulate constraints on

Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

NARCIS (Netherlands)

Hiddo Velsink

2016-01-01

From the article: Abstract Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

Science.gov (United States)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

EmailTime: visual analytics and statistics for temporal email

Science.gov (United States)

Erfani Joorabchi, Minoo; Yim, Ji-Dong; Shaw, Christopher D.

2011-01-01

Although the discovery and analysis of communication patterns in large and complex email datasets are difficult tasks, they can be a valuable source of information. We present EmailTime, a visual analysis tool of email correspondence patterns over the course of time that interactively portrays personal and interpersonal networks using the correspondence in the email dataset. Our approach is to put time as a primary variable of interest, and plot emails along a time line. EmailTime helps email dataset explorers interpret archived messages by providing zooming, panning, filtering and highlighting etc. To support analysis, it also measures and visualizes histograms, graph centrality and frequency on the communication graph that can be induced from the email collection. This paper describes EmailTime's capabilities, along with a large case study with Enron email dataset to explore the behaviors of email users within different organizational positions from January 2000 to December 2001. We defined email behavior as the email activity level of people regarding a series of measured metrics e.g. sent and received emails, numbers of email addresses, etc. These metrics were calculated through EmailTime. Results showed specific patterns in the use email within different organizational positions. We suggest that integrating both statistics and visualizations in order to display information about the email datasets may simplify its evaluation.

GRIZ: Visualization of finite element analysis results on unstructured grids

International Nuclear Information System (INIS)

Dovey, D.; Loomis, M.D.

1994-01-01

GRIZ is a general-purpose post-processing application that supports interactive visualization of finite element analysis results on three-dimensional unstructured grids. GRIZ includes direct-to-videodisc animation capabilities and is being used as a production tool for creating engineering animations

Time series analysis of temporal networks

Science.gov (United States)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

Repeatability of visual acuity measurement.

Science.gov (United States)

Raasch, T W; Bailey, I L; Bullimore, M A

1998-05-01

This study investigates features of visual acuity chart design and acuity testing scoring methods which affect the validity and repeatability of visual acuity measurements. Visual acuity was measured using the Sloan and British Standard letter series, and Landolt rings. Identifiability of the different letters as a function of size was estimated, and expressed in the form of frequency-of-seeing curves. These functions were then used to simulate acuity measurements with a variety of chart designs and scoring criteria. Systematic relationships exist between chart design parameters and acuity score, and acuity score repeatability. In particular, an important feature of a chart, that largely determines the repeatability of visual acuity measurement, is the amount of size change attributed to each letter. The methods used to score visual acuity performance also affect repeatability. It is possible to evaluate acuity score validity and repeatability using the statistical principles discussed here.

The transnational appeal of Danish TV series

DEFF Research Database (Denmark)

Jensen, Pia Majbritt

because it challenges existing theories on global media geography, import/export of audio-visual content, transnational media reception and the importance of transnational TV viewing. According to these theories, non-Anglophone audio-visual content rarely exports outside its geo-linguistic region...... – in Denmark’s case the Nordic region – because audiences in other regions would be too far removed culturally and linguistically, and hence feel alienated Similarly, theories on the consumption of audio-visual content have neglected transnational, ‘non-resident’, viewing – i.e. when audiences engage...... with audio-visual content removed from their own (cultural) context as would be the case with international audiences engaging with Danish series – and instead emphasized the importance of geo-linguistic, national or ‘resident’ viewing. Even in cases when transnational viewing has been theorized...

TargetVue: Visual Analysis of Anomalous User Behaviors in Online Communication Systems.

Science.gov (United States)

Cao, Nan; Shi, Conglei; Lin, Sabrina; Lu, Jie; Lin, Yu-Ru; Lin, Ching-Yung

2016-01-01

Users with anomalous behaviors in online communication systems (e.g. email and social medial platforms) are potential threats to society. Automated anomaly detection based on advanced machine learning techniques has been developed to combat this issue; challenges remain, though, due to the difficulty of obtaining proper ground truth for model training and evaluation. Therefore, substantial human judgment on the automated analysis results is often required to better adjust the performance of anomaly detection. Unfortunately, techniques that allow users to understand the analysis results more efficiently, to make a confident judgment about anomalies, and to explore data in their context, are still lacking. In this paper, we propose a novel visual analysis system, TargetVue, which detects anomalous users via an unsupervised learning model and visualizes the behaviors of suspicious users in behavior-rich context through novel visualization designs and multiple coordinated contextual views. Particularly, TargetVue incorporates three new ego-centric glyphs to visually summarize a user's behaviors which effectively present the user's communication activities, features, and social interactions. An efficient layout method is proposed to place these glyphs on a triangle grid, which captures similarities among users and facilitates comparisons of behaviors of different users. We demonstrate the power of TargetVue through its application in a social bot detection challenge using Twitter data, a case study based on email records, and an interview with expert users. Our evaluation shows that TargetVue is beneficial to the detection of users with anomalous communication behaviors.

Assessing homogeneity and climate variability of temperature and precipitation series in the capitals of northeastern Brazil

Science.gov (United States)

Hänsel, Stephanie; Medeiros, Deusdedit; Matschullat, Jörg; Silva, Isamara; Petta, Reinaldo

2016-03-01

A 51-year dataset (1961 to 2011) from nine meteorological stations in the capitals of northeastern Brazil (NEB), with daily data of precipitation totals and of mean, minimum and maximum temperatures, was statistically analyzed for data homogeneity and for signals of climate variability. The hypothesis was explored that a connection exists between inhomogeneities of the time series and the meteorological systems influencing the region. Results of the homogeneity analysis depend on the selected test variable, the test algorithm and the chosen significance level; all more or less subjective choices. Most of the temperature series was classified as "suspect", while most of the precipitation series was categorized as "useful". Displaying and visually checking the time series demonstrates the power of expertise and may allow for a deeper data analysis. Consistent changes in the seasonality of temperature and precipitation emerge over NEB despite manifold breaks in the temperature series. Both series appear to be coupled. The intra-annual temperature and precipitation ranges have increased, along with an intensified seasonal cycle. Temperature mainly increased during DJF, MAM and SON, with decreases in JJA being related to wetter conditions and more frequent heavy precipitation events. Drought conditions mostly increased in SON and DJF, depending on the timing of the local dry season.

Network Traffic Analysis With Query Driven VisualizationSC 2005HPC Analytics Results

Energy Technology Data Exchange (ETDEWEB)

Stockinger, Kurt; Wu, Kesheng; Campbell, Scott; Lau, Stephen; Fisk, Mike; Gavrilov, Eugene; Kent, Alex; Davis, Christopher E.; Olinger,Rick; Young, Rob; Prewett, Jim; Weber, Paul; Caudell, Thomas P.; Bethel,E. Wes; Smith, Steve

2005-09-01

Our analytics challenge is to identify, characterize, and visualize anomalous subsets of large collections of network connection data. We use a combination of HPC resources, advanced algorithms, and visualization techniques. To effectively and efficiently identify the salient portions of the data, we rely on a multi-stage workflow that includes data acquisition, summarization (feature extraction), novelty detection, and classification. Once these subsets of interest have been identified and automatically characterized, we use a state-of-the-art-high-dimensional query system to extract data subsets for interactive visualization. Our approach is equally useful for other large-data analysis problems where it is more practical to identify interesting subsets of the data for visualization than to render all data elements. By reducing the size of the rendering workload, we enable highly interactive and useful visualizations. As a result of this work we were able to analyze six months worth of data interactively with response times two orders of magnitude shorter than with conventional methods.

[The Performance Analysis for Lighting Sources in Highway Tunnel Based on Visual Function].

Science.gov (United States)

Yang, Yong; Han, Wen-yuan; Yan, Ming; Jiang, Hai-feng; Zhu, Li-wei

2015-10-01

Under the condition of mesopic vision, the spectral luminous efficiency function is shown as a series of curves. Its peak wavelength and intensity are affected by light spectrum, background brightness and other aspects. The impact of light source to lighting visibility could not be carried out via a single optical parametric characterization. The reaction time of visual cognition is regard as evaluating indexes in this experiment. Under the condition of different speed and luminous environment, testing visual cognition based on vision function method. The light sources include high pressure sodium, electrodeless fluorescent lamp and white LED with three kinds of color temperature (the range of color temperature is from 1 958 to 5 537 K). The background brightness value is used for basic section of highway tunnel illumination and general outdoor illumination, its range is between 1 and 5 cd x m(-)2. All values are in the scope of mesopic vision. Test results show that: under the same condition of speed and luminance, the reaction time of visual cognition that corresponding to high color temperature of light source is shorter than it corresponding to low color temperature; the reaction time corresponding to visual target in high speed is shorter than it in low speed. At the end moment, however, the visual angle of target in observer's visual field that corresponding to low speed was larger than it corresponding to high speed. Based on MOVE model, calculating the equivalent luminance of human mesopic vision, which is on condition of different emission spectrum and background brightness that formed by test lighting sources. Compared with photopic vision result, the standard deviation (CV) of time-reaction curve corresponding to equivalent brightness of mesopic vision is smaller. Under the condition of mesopic vision, the discrepancy between equivalent brightness of different lighting source and photopic vision, that is one of the main reasons for causing the

Numerical Analysis on Color Preference and Visual Comfort from Eye Tracking Technique

Directory of Open Access Journals (Sweden)

Ming-Chung Ho

2015-01-01

Full Text Available Color preferences in engineering are very important, and there exists relationship between color preference and visual comfort. In this study, there are thirty university students who participated in the experiment, supplemented by pre- and posttest questionnaires, which lasted about an hour. The main purpose of this study is to explore the visual effects of different color assignment with subjective color preferences via eye tracking technology. Eye-movement data through a nonlinear analysis detect slight differences in color preferences and visual comfort, suggesting effective physiological indicators as extensive future research discussed. Results found that the average pupil size of eye-movement indicators can effectively reflect the differences of color preferences and visual comfort. This study more confirmed that the subjective feeling will make people have misjudgment.

UTOOLS: microcomputer software for spatial analysis and landscape visualization.

Science.gov (United States)

Alan A. Ager; Robert J. McGaughey

1997-01-01

UTOOLS is a collection of programs designed to integrate various spatial data in a way that allows versatile spatial analysis and visualization. The programs were designed for watershed-scale assessments in which a wide array of resource data must be integrated, analyzed, and interpreted. UTOOLS software combines raster, attribute, and vector data into "spatial...

Visual search of cyclic spatio-temporal events

Science.gov (United States)

Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

2018-05-01

The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

Science.gov (United States)

Suhaila, Jamaludin; Yusop, Zulkifli

2017-06-01

Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.

Contingency Analysis Post-Processing With Advanced Computing and Visualization

Energy Technology Data Exchange (ETDEWEB)

Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

2017-07-01

Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability and accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.

Visualization rhetoric: framing effects in narrative visualization.

Science.gov (United States)

Hullman, Jessica; Diakopoulos, Nicholas

2011-12-01

Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that "tell a story" can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels-the data, visual representation, textual annotations, and interactivity-and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation. © 2011 IEEE

The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis

Science.gov (United States)

Veatch, W.; Friedman, D.; Baker, B.; Mueller, C.

2017-12-01

The vast majority of data analyzed by climate researchers are repeated observations of physical process or time series data. This data lends itself of a common set of statistical techniques and models designed to determine trends and variability (e.g., seasonality) of these repeated observations. Often, these same techniques and models can be applied to a wide variety of different time series data. The Timeseries Toolbox is a web application designed to standardize and streamline these common approaches to time series analysis and modeling with particular attention to hydrologic time series used in climate preparedness and resilience planning and design by the U. S. Army Corps of Engineers. The application performs much of the pre-processing of time series data necessary for more complex techniques (e.g. interpolation, aggregation). With this tool, users can upload any dataset that conforms to a standard template and immediately begin applying these techniques to analyze their time series data.

Fractal Analysis of Radiologists Visual Scanning Pattern in Screening Mammography

Energy Technology Data Exchange (ETDEWEB)

Alamudun, Folami T [ORNL; Yoon, Hong-Jun [ORNL; Hudson, Kathy [University of Tennessee, Knoxville (UTK); Morin-Ducote, Garnetta [University of Tennessee, Knoxville (UTK); Tourassi, Georgia [ORNL

2015-01-01

Several investigators have investigated radiologists visual scanning patterns with respect to features such as total time examining a case, time to initially hit true lesions, number of hits, etc. The purpose of this study was to examine the complexity of the radiologists visual scanning pattern when viewing 4-view mammographic cases, as they typically do in clinical practice. Gaze data were collected from 10 readers (3 breast imaging experts and 7 radiology residents) while reviewing 100 screening mammograms (24 normal, 26 benign, 50 malignant). The radiologists scanpaths across the 4 mammographic views were mapped to a single 2-D image plane. Then, fractal analysis was applied on the derived scanpaths using the box counting method. For each case, the complexity of each radiologist s scanpath was estimated using fractal dimension. The association between gaze complexity, case pathology, case density, and radiologist experience was evaluated using 3 factor fixed effects ANOVA. ANOVA showed that case pathology, breast density, and experience level are all independent predictors of the visual scanning pattern complexity. Visual scanning patterns are significantly different for benign and malignant cases than for normal cases as well as when breast parenchyma density changes.

Visual scan-path analysis with feature space transient fixation moments

Science.gov (United States)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

On statistical inference in time series analysis of the evolution of road safety.

Science.gov (United States)

Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

2013-11-01

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

Science.gov (United States)

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

Time series analysis of wind speed using VAR and the generalized impulse response technique

Energy Technology Data Exchange (ETDEWEB)

Ewing, Bradley T. [Area of Information Systems and Quantitative Sciences, Rawls College of Business and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX 79409-2101 (United States); Kruse, Jamie Brown [Center for Natural Hazard Research, East Carolina University, Greenville, NC (United States); Schroeder, John L. [Department of Geosciences and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States); Smith, Douglas A. [Department of Civil Engineering and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States)

2007-03-15

This research examines the interdependence in time series wind speed data measured in the same location at four different heights. A multiple-equation system known as a vector autoregression is proposed for characterizing the time series dynamics of wind. Additionally, the recently developed method of generalized impulse response analysis provides insight into the cross-effects of the wind series and their responses to shocks. Findings are based on analysis of contemporaneous wind speed time histories taken at 13, 33, 70 and 160 ft above ground level with a sampling rate of 10 Hz. The results indicate that wind speeds measured at 70 ft was the most variable. Further, the turbulence persisted longer at the 70-ft measurement than at the other heights. The greatest interdependence is observed at 13 ft. Gusts at 160 ft led to the greatest persistence to an 'own' shock and led to greatest persistence in the responses of the other wind series. (author)

A visual analysis of gender bias in contemporary anatomy textbooks.

Science.gov (United States)

Parker, Rhiannon; Larkin, Theresa; Cockburn, Jon

2017-05-01

Empirical research has linked gender bias in medical education with negative attitudes and behaviors in healthcare providers. Yet it has been more than 20 years since research has considered the degree to which women and men are equally represented in anatomy textbooks. Furthermore, previous research has not explored beyond quantity of representation to also examine visual gender stereotypes and, in light of theoretical advancements in the area of intersectional research, the relationship between representations of gender and representations of ethnicity, body type, health, and age. This study aimed to determine the existence and representation of gender bias in the major anatomy textbooks used at Australian Medical Schools. A systematic visual content analysis was conducted on 6044 images in which sex/gender could be identified, sourced from 17 major anatomy textbooks published from 2008 to 2013. Further content analysis was performed on the 521 narrative images, which represent an unfolding story, found within the same textbooks. Results indicate that the representation of gender in images from anatomy textbooks remain predominantly male except within sex-specific sections. Further, other forms of bias were found to exist in: the visualization of stereotypical gendered emotions, roles and settings; the lack of ethnic, age, and body type diversity; and in the almost complete adherence to a sex/gender binary. Despite increased attention to gender issues in medicine, the visual representation of gender in medical curricula continues to be biased. The biased construction of gender in anatomy textbooks designed for medical education provides future healthcare providers with inadequate and unrealistic information about patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of cyclical behavior in time series of stock market returns

Science.gov (United States)

Stratimirović, Djordje; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana

2018-01-01

In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time-dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.

Visual computing scientific visualization and imaging systems

CERN Document Server

2014-01-01

This volume aims to stimulate discussions on research involving the use of data and digital images as an understanding approach for analysis and visualization of phenomena and experiments. The emphasis is put not only on graphically representing data as a way of increasing its visual analysis, but also on the imaging systems which contribute greatly to the comprehension of real cases. Scientific Visualization and Imaging Systems encompass multidisciplinary areas, with applications in many knowledge fields such as Engineering, Medicine, Material Science, Physics, Geology, Geographic Information Systems, among others. This book is a selection of 13 revised and extended research papers presented in the International Conference on Advanced Computational Engineering and Experimenting -ACE-X conferences 2010 (Paris), 2011 (Algarve), 2012 (Istanbul) and 2013 (Madrid). The examples were particularly chosen from materials research, medical applications, general concepts applied in simulations and image analysis and ot...

VAMPS: a website for visualization and analysis of microbial population structures.

Science.gov (United States)

Huse, Susan M; Mark Welch, David B; Voorhis, Andy; Shipunova, Anna; Morrison, Hilary G; Eren, A Murat; Sogin, Mitchell L

2014-02-05

The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10⁵-10⁸ reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators' private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next

Knowledge-assisted cross-media analysis of audio-visual content in the news domain

NARCIS (Netherlands)

Mezaris, Vasileios; Gidaros, Spyros; Papadopoulos, Georgios Th.; Kasper, Walter; Ordelman, Roeland J.F.; de Jong, Franciska M.G.; Kompatsiaris, Ioannis

In this paper, a complete architecture for knowledge-assisted cross-media analysis of News-related multimedia content is presented, along with its constituent components. The proposed analysis architecture employs state-of-the-art methods for the analysis of each individual modality (visual, audio,

FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis.

Science.gov (United States)

Wan, Yong; Otsuna, Hideo; Holman, Holly A; Bagley, Brig; Ito, Masayoshi; Lewis, A Kelsey; Colasanto, Mary; Kardon, Gabrielle; Ito, Kei; Hansen, Charles

2017-05-26

Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.

Dissociation of the Neural Correlates of Visual and Auditory Contextual Encoding

Science.gov (United States)

Gottlieb, Lauren J.; Uncapher, Melina R.; Rugg, Michael D.

2010-01-01

The present study contrasted the neural correlates of encoding item-context associations according to whether the contextual information was visual or auditory. Subjects (N = 20) underwent fMRI scanning while studying a series of visually presented pictures, each of which co-occurred with either a visually or an auditorily presented name. The task…

Design and implementation of network attack analysis and detect system

International Nuclear Information System (INIS)

Lu Zhigang; Wu Huan; Liu Baoxu

2007-01-01

This paper first analyzes the present research state of IDS (intrusion detection system), classifies and compares existing methods. According to the problems existing in IDS, such as false-positives, false-negatives and low information visualization, this paper suggests a system named NAADS which supports multi data sources. Through a series of methods such as clustering analysis, association analysis and visualization, rate of detection and usability of NAADS are increased. (authors)

Scalable data management, analysis and visualization (SDAV) Institute. Final Scientific/Technical Report

Energy Technology Data Exchange (ETDEWEB)

Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States)

2017-03-28

The purpose of the SDAV institute is to provide tools and expertise in scientific data management, analysis, and visualization to DOE’s application scientists. Our goal is to actively work with application teams to assist them in achieving breakthrough science, and to provide technical solutions in the data management, analysis, and visualization regimes that are broadly used by the computational science community. Over the last 5 years members of our institute worked directly with application scientists and DOE leadership-class facilities to assist them by applying the best tools and technologies at our disposal. We also enhanced our tools based on input from scientists on their needs. Many of the applications we have been working with are based on connections with scientists established in previous years. However, we contacted additional scientists though our outreach activities, as well as engaging application teams running on leading DOE computing systems. Our approach is to employ an evolutionary development and deployment process: first considering the application of existing tools, followed by the customization necessary for each particular application, and then the deployment in real frameworks and infrastructures. The institute is organized into three areas, each with area leaders, who keep track of progress, engagement of application scientists, and results. The areas are: (1) Data Management, (2) Data Analysis, and (3) Visualization. Kitware has been involved in the Visualization area. This report covers Kitware’s contributions over the last 5 years (February 2012 – February 2017). For details on the work performed by the SDAV institute as a whole, please see the SDAV final report.

Qualifying program on Non-Destructive Testing, Visual Inspection of the welding (level 2)

International Nuclear Information System (INIS)

Shafee, M. A.

2011-01-01

Nondestructive testing is a wide group of analysis technique used in science and industry to evaluate the properties of a material, component or system without causing damage. Common Non-Destructive Testing methods include ultrasonic, magnetic-particle, liquid penetrate, radiographic, visual inspection and eddy-current testing. AAEA put the new book of the Non-Destructive Testing publication series that focused on Q ualifying program on Non-Destructive Testing, visual inspection of welding-level 2 . This book was done in accordance with the Arab standard certification of Non-Destructive Testing (ARAB-NDT-CERT-002) which is agreeing with the ISO-9712 (2005) and IAEA- TEC-DOC-487. It includes twenty one chapters dealing with engineering materials used in industry, the mechanical behavior of metals, metal forming equipments, welding, metallurgy, testing of welds, introduction to Non-Destructive Testing, defects in metals, welding defects and discontinuities, introduction to visual inspection theory, properties and tools of visual testing, visual testing, quality control regulations, standards, codes and specifications, procedures of welding inspections, responsibility of welding test inspector, qualification of Non-Destructive Testing inspector and health safety during working.

Trident: scalable compute archives: workflows, visualization, and analysis

Science.gov (United States)

Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Kotulla, Ralf; Henschel, Robert; Harbeck, Daniel

2016-08-01

The Astronomy scientific community has embraced Big Data processing challenges, e.g. associated with time-domain astronomy, and come up with a variety of novel and efficient data processing solutions. However, data processing is only a small part of the Big Data challenge. Efficient knowledge discovery and scientific advancement in the Big Data era requires new and equally efficient tools: modern user interfaces for searching, identifying and viewing data online without direct access to the data; tracking of data provenance; searching, plotting and analyzing metadata; interactive visual analysis, especially of (time-dependent) image data; and the ability to execute pipelines on supercomputing and cloud resources with minimal user overhead or expertise even to novice computing users. The Trident project at Indiana University offers a comprehensive web and cloud-based microservice software suite that enables the straight forward deployment of highly customized Scalable Compute Archive (SCA) systems; including extensive visualization and analysis capabilities, with minimal amount of additional coding. Trident seamlessly scales up or down in terms of data volumes and computational needs, and allows feature sets within a web user interface to be quickly adapted to meet individual project requirements. Domain experts only have to provide code or business logic about handling/visualizing their domain's data products and about executing their pipelines and application work flows. Trident's microservices architecture is made up of light-weight services connected by a REST API and/or a message bus; a web interface elements are built using NodeJS, AngularJS, and HighCharts JavaScript libraries among others while backend services are written in NodeJS, PHP/Zend, and Python. The software suite currently consists of (1) a simple work flow execution framework to integrate, deploy, and execute pipelines and applications (2) a progress service to monitor work flows and sub

Formulating qualitative features using interactive visualization for analysis of multivariate spatiotemporal data

Science.gov (United States)

Porter, M.; Hill, M. C.; Pierce, S. A.; Gil, Y.; Pennington, D. D.

2017-12-01

DiscoverWater is a web-based visualization tool developed to enable the visual representation of data, and thus, aid scientific and societal understanding of hydrologic systems. Open data sources are coalesced to, for example, illustrate the impacts on streamflow of irrigation withdrawals. Scientists and stakeholders are informed through synchronized time-series data plots that correlate multiple spatiotemporal datasets and an interactive time-evolving map that provides a spatial analytical context. Together, these components elucidate trends so that the user can try to envision the relations between groundwater-surface water interactions, the impacts of pumping on these interactions, and the interplay of climate. Aligning data in this manner has the capacity for interdisciplinary knowledge discovery and motivates dialogue about system processes that we seek to enhance through qualitative features informed through quantitative models. DiscoverWater and its connection is demonstrated using two field cases. First, it is used to visualize data sets from the High Plains aquifer, where reservoir- and groundwater-supported irrigation has affected the Arkansas River in western Kansas. Second, data and model results from Barton Springs segment of the Edwards aquifer in Texas reveal the effects of regional pumping on this important urbanizing aquifer system. Identifying what is interesting about the data and the modeled system in the two different case studies is a step towards moving typically static visualization capabilities to an adaptive framework. Additionally, the dashboard interface incorporates both quantitative and qualitative information about distinctive case studies in a machine-readable form, such that a catalog of qualitative models can capture subject matter expertise alongside associated datasets. As the catalog is expanded to include other case studies, the collection has potential to establish a standard framework able to inform intelligent system

A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis

Science.gov (United States)

Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

2018-04-01

For the first time, we introduced the probabilistic principal component analysis (pPCA) regarding the spatio-temporal filtering of Global Navigation Satellite System (GNSS) position time series to estimate and remove Common Mode Error (CME) without the interpolation of missing values. We used data from the International GNSS Service (IGS) stations which contributed to the latest International Terrestrial Reference Frame (ITRF2014). The efficiency of the proposed algorithm was tested on the simulated incomplete time series, then CME was estimated for a set of 25 stations located in Central Europe. The newly applied pPCA was compared with previously used algorithms, which showed that this method is capable of resolving the problem of proper spatio-temporal filtering of GNSS time series characterized by different observation time span. We showed, that filtering can be carried out with pPCA method when there exist two time series in the dataset having less than 100 common epoch of observations. The 1st Principal Component (PC) explained more than 36% of the total variance represented by time series residuals' (series with deterministic model removed), what compared to the other PCs variances (less than 8%) means that common signals are significant in GNSS residuals. A clear improvement in the spectral indices of the power-law noise was noticed for the Up component, which is reflected by an average shift towards white noise from - 0.98 to - 0.67 (30%). We observed a significant average reduction in the accuracy of stations' velocity estimated for filtered residuals by 35, 28 and 69% for the North, East, and Up components, respectively. CME series were also subjected to analysis in the context of environmental mass loading influences of the filtering results. Subtraction of the environmental loading models from GNSS residuals provides to reduction of the estimated CME variance by 20 and 65% for horizontal and vertical components, respectively.

Regression analysis for LED color detection of visual-MIMO system

Science.gov (United States)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

Time series analysis for psychological research: examining and forecasting change.

Science.gov (United States)

Jebb, Andrew T; Tay, Louis; Wang, Wei; Huang, Qiming

2015-01-01

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials.

Time series analysis for psychological research: examining and forecasting change

Science.gov (United States)

Jebb, Andrew T.; Tay, Louis; Wang, Wei; Huang, Qiming

2015-01-01

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials. PMID:26106341

Evaluating an animated and static time series map of District Six: A ...

African Journals Online (AJOL)

Visualization of spatial information is an important aspect in the representation of map displays. Maps today are visually adapted to a variety of mediums in displaying spatial information temporally and as time series phenomena. GIS technology has incorporated tools for analysing these spatio-temporal trends. However ...

Investigation and experimental data de-noising of Damavand tokamak by using fourier series expansion and wavelet code

International Nuclear Information System (INIS)

Sadeghi, Y.

2006-01-01

Computer Programs are important tools in physics. Analysis of the experimental data and the control of complex handle physical phenomenon and the solution of numerical problem in physics help scientist to the behavior and simulate the process. In this paper, calculation of several Fourier series gives us a visual and analytic impression of data analyses from Fourier series. One of important aspect in data analyses is to find optimum method for de-noising. Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution corresponding to its scale. They have advantages over usual traditional methods in analyzing physical situations where the signal contains discontinuities and sharp spikes. Transformed data by wavelets in frequency space has time information and can clearly show the exact location in time of the discontinuity. This aspect makes wavelets an excellent tool in the field of data analysis. In this paper, we show how Fourier series and wavelets can analyses data in Damavand tokamak. ?

Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data

International Nuclear Information System (INIS)

Rubel, Oliver; Ahern, Sean; Bethel, E. Wes; Biggin, Mark D.; Childs, Hank; Cormier-Michel, Estelle; DePace, Angela; Eisen, Michael B.; Fowlkes, Charless C.; Geddes, Cameron G.R.; Hagen, Hans; Hamann, Bernd; Huang, Min-Yu; Keranen, Soile V.E.; Knowles, David W.; Hendriks, Chris L. Luengo; Malik, Jitendra; Meredith, Jeremy; Messmer, Peter; Prabhat; Ushizima, Daniela; Weber, Gunther H.; Wu, Kesheng

2010-01-01

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies 'such as efficient data management' supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

Phase correction and error estimation in InSAR time series analysis

Science.gov (United States)

Zhang, Y.; Fattahi, H.; Amelung, F.

2017-12-01

During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same

Experiment archive, analysis, and visualization at the National Ignition Facility

International Nuclear Information System (INIS)

Hutton, Matthew S.; Azevedo, Stephen; Beeler, Richard; Bettenhausen, Rita; Bond, Essex; Casey, Allan; Liebman, Judith; Marsh, Amber; Pannell, Thomas; Warrick, Abbie

2012-01-01

Highlights: ► We show the computing architecture to manage scientific data from NIF experiments. ► NIF laser “shots” generate GBs of data for sub-microsec events separated by hours. ► Results are archived, analyzed and displayed with parallel and scalable code. ► Data quality and pedigree, based on calibration of each part, are tracked. ► Web-based visualization tools present data across shots and diagnostics. - Abstract: The National Ignition Facility (NIF) at the Lawrence Livermore National Laboratory is the world's most energetic laser, providing a scientific research center to study inertial confinement fusion and matter at extreme energy densities and pressures. A target shot involves over 30 specialized diagnostics measuring critical x-ray, optical and nuclear phenomena to quantify ignition results for comparison with computational models. The Shot Analysis and Visualization System (SAVI) acquires and analyzes target diagnostic data for display within a time-budget of 30 min. Laser and target diagnostic data are automatically loaded into the NIF archive database through clustered software data collection agents. The SAVI Analysis Engine distributes signal and image processing tasks to a Linux cluster where computation is performed. Intermediate results are archived at each step of the analysis pipeline. Data is archived with metadata and pedigree. Experiment results are visualized through a web-based user interface in interactive dashboards tailored to single or multiple shot perspectives. The SAVI system integrates open-source software, commercial workflow tools, relational database and messaging technologies into a service-oriented and distributed software architecture that is highly parallel, scalable, and flexible. The architecture and functionality of the SAVI system will be presented along with examples.

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

Science.gov (United States)

Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

Metaviz: interactive statistical and visual analysis of metagenomic data.

Science.gov (United States)

Wagner, Justin; Chelaru, Florin; Kancherla, Jayaram; Paulson, Joseph N; Zhang, Alexander; Felix, Victor; Mahurkar, Anup; Elmqvist, Niklas; Corrada Bravo, Héctor

2018-04-06

Large studies profiling microbial communities and their association with healthy or disease phenotypes are now commonplace. Processed data from many of these studies are publicly available but significant effort is required for users to effectively organize, explore and integrate it, limiting the utility of these rich data resources. Effective integrative and interactive visual and statistical tools to analyze many metagenomic samples can greatly increase the value of these data for researchers. We present Metaviz, a tool for interactive exploratory data analysis of annotated microbiome taxonomic community profiles derived from marker gene or whole metagenome shotgun sequencing. Metaviz is uniquely designed to address the challenge of browsing the hierarchical structure of metagenomic data features while rendering visualizations of data values that are dynamically updated in response to user navigation. We use Metaviz to provide the UMD Metagenome Browser web service, allowing users to browse and explore data for more than 7000 microbiomes from published studies. Users can also deploy Metaviz as a web service, or use it to analyze data through the metavizr package to interoperate with state-of-the-art analysis tools available through Bioconductor. Metaviz is free and open source with the code, documentation and tutorials publicly accessible.

BasinVis 1.0: A MATLAB®-based program for sedimentary basin subsidence analysis and visualization

Science.gov (United States)

Lee, Eun Young; Novotny, Johannes; Wagreich, Michael

2016-06-01

Stratigraphic and structural mapping is important to understand the internal structure of sedimentary basins. Subsidence analysis provides significant insights for basin evolution. We designed a new software package to process and visualize stratigraphic setting and subsidence evolution of sedimentary basins from well data. BasinVis 1.0 is implemented in MATLAB®, a multi-paradigm numerical computing environment, and employs two numerical methods: interpolation and subsidence analysis. Five different interpolation methods (linear, natural, cubic spline, Kriging, and thin-plate spline) are provided in this program for surface modeling. The subsidence analysis consists of decompaction and backstripping techniques. BasinVis 1.0 incorporates five main processing steps; (1) setup (study area and stratigraphic units), (2) loading well data, (3) stratigraphic setting visualization, (4) subsidence parameter input, and (5) subsidence analysis and visualization. For in-depth analysis, our software provides cross-section and dip-slip fault backstripping tools. The graphical user interface guides users through the workflow and provides tools to analyze and export the results. Interpolation and subsidence results are cached to minimize redundant computations and improve the interactivity of the program. All 2D and 3D visualizations are created by using MATLAB plotting functions, which enables users to fine-tune the results using the full range of available plot options in MATLAB. We demonstrate all functions in a case study of Miocene sediment in the central Vienna Basin.

Network analysis for the visualization and analysis of qualitative data.

Science.gov (United States)

Pokorny, Jennifer J; Norman, Alex; Zanesco, Anthony P; Bauer-Wu, Susan; Sahdra, Baljinder K; Saron, Clifford D

2018-03-01

We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures. Here, as a proof of concept, we applied this method to a set of interview transcripts that had been coded in 2 different ways and the resultant network graphs were examined. The creation of network graphs allows researchers an opportunity to view and share their qualitative data in an innovative way that may provide new insights and enhance transparency of the analytical process by which they reach their conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

Science.gov (United States)

Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

2013-01-01

This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

Visualized attribute analysis approach for characterization and quantification of rice taste flavor using electronic tongue

Energy Technology Data Exchange (ETDEWEB)

Lu, Lin; Hu, Xianqiao [Rice Product Quality Supervision and Inspection Center, Ministry of Agriculture, China National Rice Research Institute, Hangzhou 310006 (China); Tian, Shiyi; Deng, Shaoping [College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310035 (China); Zhu, Zhiwei, E-mail: 615834652@qq.com [Rice Product Quality Supervision and Inspection Center, Ministry of Agriculture, China National Rice Research Institute, Hangzhou 310006 (China)

2016-05-05

This paper deals with a novel visualized attributive analysis approach for characterization and quantification of rice taste flavor attributes (softness, stickiness, sweetness and aroma) employing a multifrequency large-amplitude pulse voltammetric electronic tongue. Data preprocessing methods including Principal Component Analysis (PCA) and Fast Fourier Transform (FFT) were provided. An attribute characterization graph was represented for visualization of the interactive response in which each attribute responded by specific electrodes and frequencies. The model was trained using signal data from electronic tongue and attribute scores from artificial evaluation. The correlation coefficients for all attributes were over 0.9, resulting in good predictive ability of attributive analysis model preprocessed by FFT. This approach extracted more effective information about linear relationship between electronic tongue and taste flavor attribute. Results indicated that this approach can accurately quantify taste flavor attributes, and can be an efficient tool for data processing in a voltammetric electronic tongue system. - Graphical abstract: Schematic process for visualized attributive analysis approach using multifrequency large-amplitude pulse voltammetric electronic tongue for determination of rice taste flavor attribute. (a) sample; (b) sensors in electronic tongue; (c) excitation voltage program and response current signal from MLAPS; (d) similarity data matrix by data preprocessing and similarity extraction; (e) feature data matrix of attribute; (f) attribute characterization graph; (g) attribute scores predicted by the model. - Highlights: • Multifrequency large-amplitude pulse voltammetric electronic tongue was used. • A visualized attributive analysis approach was created as an efficient tool for data processing. • Rice taste flavor attribute was determined and predicted. • The attribute characterization graph was represented for visualization of the

Fractal analysis of visual search activity for mass detection during mammographic screening.

Science.gov (United States)

Alamudun, Folami; Yoon, Hong-Jun; Hudson, Kathleen B; Morin-Ducote, Garnetta; Hammond, Tracy; Tourassi, Georgia D

2017-03-01

The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics. The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) from 10 readers (three board certified radiologists and seven Radiology residents), formed the corpus for this study. The fractal dimension of the readers' visual scanning pattern was computed with the Minkowski-Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined. Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the complexity of visual scanning pattern when screening for breast cancer. No higher order effects were found to be significant. Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics. © 2017 American Association of Physicists in Medicine.

Familiarity Vs Trust: A Comparative Study of Domain Scientists' Trust in Visual Analytics and Conventional Analysis Methods.

Science.gov (United States)

Dasgupta, Aritra; Lee, Joon-Yong; Wilson, Ryan; Lafrance, Robert A; Cramer, Nick; Cook, Kristin; Payne, Samuel

2017-01-01

Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust. We propose a trust-augmented design of the visual analytics system, that explicitly takes into account domain-specific tasks, conventions, and preferences. For evaluating the system, we present the results of a controlled user study with 34 biologists where we compare the variation of the level of trust across conventional and visual analytic mediums and explore the influence of familiarity and task complexity on trust. We find that despite being unfamiliar with a visual analytic medium, scientists seem to have an average level of trust that is comparable with the same in conventional analysis medium. In fact, for complex sense-making tasks, we find that the visual analytic system is able to inspire greater trust than other mediums. We summarize the implications of our findings with directions for future research on trustworthiness of visual analytic systems.

Development of design and analysis software for advanced nuclear system

International Nuclear Information System (INIS)

Wu Yican; Hu Liqin; Long Pengcheng; Luo Yuetong; Li Yazhou; Zeng Qin; Lu Lei; Zhang Junjun; Zou Jun; Xu Dezheng; Bai Yunqing; Zhou Tao; Chen Hongli; Peng Lei; Song Yong; Huang Qunying

2010-01-01

A series of professional codes, which are necessary software tools and data libraries for advanced nuclear system design and analysis, were developed by the FDS Team, including the codes of automatic modeling, physics and engineering calculation, virtual simulation and visualization, system engineering and safety analysis and the related database management etc. The development of these software series was proposed as an exercise of development of nuclear informatics. This paper introduced the main functions and key techniques of the software series, as well as some tests and practical applications. (authors)

TINJAUAN ELEMEN ELEMEN CITRA KOTA SEBAGAI PEMBENTUK SERI VISUAL DI KOTA JAYAPURA

Directory of Open Access Journals (Sweden)

Alfini Baharudin

2016-01-01

Full Text Available A town ought to have clarity at its planning structure so that the town can give strong picture and image to its public. For the purpose required by existence of town planning structure which covers its functions and visual aspect which be each other related to give clarity.  Structural of the town planning among others can be observed visually by through an observation in doing movement of one point to point of others in town.  In this study, observation performed at town planning structure of Jayapura by doing observation to structural elements of town planning which there have. Observation there performed visually alongside main road which connects downtown of Jayapura-Abepura-Waena. From result show that town planning structure of Jayapura has one regulating elements in the form of kurvalinier main road which connects downtown of Jayapura-Abepura-Waena. Some of the structural elements of town planning which there have can give picture of strong image, but some elements between it needs arrangement in hope that can give optimal clarity. Result of this study recommends arrangement concept of serial vision at town planning structure of Jayapura according to its hierarchy.

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

Science.gov (United States)

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

Visual cues for data mining

Science.gov (United States)

Rogowitz, Bernice E.; Rabenhorst, David A.; Gerth, John A.; Kalin, Edward B.

1996-04-01

This paper describes a set of visual techniques, based on principles of human perception and cognition, which can help users analyze and develop intuitions about tabular data. Collections of tabular data are widely available, including, for example, multivariate time series data, customer satisfaction data, stock market performance data, multivariate profiles of companies and individuals, and scientific measurements. In our approach, we show how visual cues can help users perform a number of data mining tasks, including identifying correlations and interaction effects, finding clusters and understanding the semantics of cluster membership, identifying anomalies and outliers, and discovering multivariate relationships among variables. These cues are derived from psychological studies on perceptual organization, visual search, perceptual scaling, and color perception. These visual techniques are presented as a complement to the statistical and algorithmic methods more commonly associated with these tasks, and provide an interactive interface for the human analyst.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

Science.gov (United States)

Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Subsurface data visualization in Virtual Reality

Science.gov (United States)

Krijnen, Robbert; Smelik, Ruben; Appleton, Rick; van Maanen, Peter-Paul

2017-04-01

Due to their increasing complexity and size, visualization of geological data is becoming more and more important. It enables detailed examining and reviewing of large volumes of geological data and it is often used as a communication tool for reporting and education to demonstrate the importance of the geology to policy makers. In the Netherlands two types of nation-wide geological models are available: 1) Layer-based models in which the subsurface is represented by a series of tops and bases of geological or hydrogeological units, and 2) Voxel models in which the subsurface is subdivided in a regular grid of voxels that can contain different properties per voxel. The Geological Survey of the Netherlands (GSN) provides an interactive web portal that delivers maps and vertical cross-sections of such layer-based and voxel models. From this portal you can download a 3D subsurface viewer that can visualize the voxel model data of an area of 20 × 25 km with 100 × 100 × 5 meter voxel resolution on a desktop computer. Virtual Reality (VR) technology enables us to enhance the visualization of this volumetric data in a more natural way as compared to a standard desktop, keyboard mouse setup. The use of VR for data visualization is not new but recent developments has made expensive hardware and complex setups unnecessary. The availability of consumer of-the-shelf VR hardware enabled us to create an new intuitive and low visualization tool. A VR viewer has been implemented using the HTC Vive head set and allows visualization and analysis of the GSN voxel model data with geological or hydrogeological units. The user can navigate freely around the voxel data (20 × 25 km) which is presented in a virtual room at a scale of 2 × 2 or 3 × 3 meters. To enable analysis, e.g. hydraulic conductivity, the user can select filters to remove specific hydrogeological units. The user can also use slicing to cut-off specific sections of the voxel data to get a closer look. This slicing

Visual comparison for information visualization

KAUST Repository

Gleicher, M.; Albers, D.; Walker, R.; Jusufi, I.; Hansen, C. D.; Roberts, J. C.

2011-01-01

Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. Increasingly, information visualization tools support such comparisons explicitly, beyond simply allowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a general understanding of comparative visualization and facilitating the development of more comparative visualization tools. © The Author(s) 2011.

Visual comparison for information visualization

KAUST Repository

Gleicher, M.

2011-09-07

Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. Increasingly, information visualization tools support such comparisons explicitly, beyond simply allowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a general understanding of comparative visualization and facilitating the development of more comparative visualization tools. © The Author(s) 2011.

Direct visualization of β phase causing intergranular forms of corrosion in Al–Mg alloys

Energy Technology Data Exchange (ETDEWEB)

Yang, Young-Ki, E-mail: deltag@naver.com; Allen, Todd

2013-06-15

For a more effective examination of microstructure in Al–Mg alloys, a new etching solution has been developed; dissolved ammonium persulfate in water. It is demonstrated how β phase (Al{sub 3}Mg{sub 2}) in Al–Mg alloys respond to this solution using samples of a binary Al–Mg alloy and a commercial 5083 aluminum alloy. Nanometer sized β phase is clearly visualized for the first time using scanning electron microscopy (SEM) instead of transmission electron microscopy (TEM). It is anticipated that direct and unambiguous visualization of β phase will greatly augment intergranular corrosion research in 5xxx series aluminum alloys. - Highlights: • Nanometer sized β phase in Al-10% Mg is first clearly visualized with SEM. • Nanometer sized β phase in wrought alloy 5083 is first clearly visualized with SEM. • Grain boundary decorating β phase and isolated sponge-like β phase are shown. • This phase is confirmed to be β phase using composition analysis.

A visual interface to computer programs for linkage analysis.

Science.gov (United States)

Chapman, C J

1990-06-01

This paper describes a visual approach to the input of information about human families into computer data bases, making use of the GEM graphic interface on the Atari ST. Similar approaches could be used on the Apple Macintosh or on the IBM PC AT (to which it has been transferred). For occasional users of pedigree analysis programs, this approach has considerable advantages in ease of use and accessibility. An example of such use might be the analysis of risk in families with Huntington disease using linked RFLPs. However, graphic interfaces do make much greater demands on the programmers of these systems.

Identification of human operator performance models utilizing time series analysis

Science.gov (United States)

Holden, F. M.; Shinners, S. M.

1973-01-01

The results of an effort performed by Sperry Systems Management Division for AMRL in applying time series analysis as a tool for modeling the human operator are presented. This technique is utilized for determining the variation of the human transfer function under various levels of stress. The human operator's model is determined based on actual input and output data from a tracking experiment.

Methotrexate therapy for chronic noninfectious uveitis: analysis of a case series of 160 patients.

Science.gov (United States)

Samson, C M; Waheed, N; Baltatzis, S; Foster, C S

2001-06-01

To evaluate the outcomes of patients with chronic noninfectious uveitis unresponsive to conventional antiinflammatory therapy who were treated with methotrexate. Retrospective noncomparative interventional case series. All patients with chronic noninfectious uveitis treated with methotrexate at a single institution from 1985 to 1999. Charts of patients seen on the Ocular Immunology & Uveitis Service at the Massachusetts Eye & Ear Infirmary were reviewed. Patients with chronic uveitis of noninfectious origin treated with methotrexate were included in the study. Control of inflammation, steroid-sparing effect, visual acuity, adverse reactions. A total of 160 patients met the inclusion criteria. Control of inflammation was achieved in 76.2% of patients. Steroid-sparing effect was achieved in 56% of patients. Visual acuity was maintained or improved in 90% of patients. Side effects requiring discontinuation of medication occurred in 18% of patients. Potentially serious adverse reactions occurred in only 8.1% of patients. There was neither long-term morbidity nor mortality caused by methotrexate. Methotrexate is effective in the treatment of chronic noninfectious uveitis that fails to respond to conventional steroid treatment. It is an effective steroid-sparing immunomodulator, is a safe medication, and is well tolerated.

Short-term memory digit-span performance under auditory and visual contexts as a function of rate of digit presentation.

Science.gov (United States)

Vitulli, W F; McNeil, M J

1990-12-01

This exploratory investigation concerned the effects of both auditory and visual context variations on the immediate recall of a series of digits presented on a computer screen (CRT). 5 intensities of background noise and 5 background hues were presented randomly to 110 undergraduate volunteers as they studied 25 numerals ranging from 1 to 5 at rates of change of either 1 or 3 sec. per numeral timed from the onset of the previous numeral. A 2 x 2 x 5 mixed split-plot factorial analysis of variance gave a significant difference in mean immediate-recall scores between rates of digit presentation with better recall associated with the 3-sec. rate. There was no significant main effect in recall scores for auditory vs color contexts, yet a post hoc analysis of variance for successive stages followed by Scheffé comparisons showed that across auditory intensities, Stages 3 and 4 and 5 (combined) had significantly higher immediate recall scores than Stages 1 and 2 (combined). This improvement across stages was not found under the visual (color) series. There was a three-way interaction for modality-contexts x rates x levels explained by the partitioning of stages which differed for auditory and for visual contexts. Results are discussed in terms of effects of modality.

Scientific Visualization for Atmospheric Data Analysis in Collaborative Virtual Environments

Science.gov (United States)

Engelke, Wito; Flatken, Markus; Garcia, Arturo S.; Bar, Christian; Gerndt, Andreas

2016-04-01

1 INTRODUCTION The three year European research project CROSS DRIVE (Collaborative Rover Operations and Planetary Science Analysis System based on Distributed Remote and Interactive Virtual Environments) started in January 2014. The research and development within this project is motivated by three use case studies: landing site characterization, atmospheric science and rover target selection [1]. Currently the implementation for the second use case is in its final phase [2]. Here, the requirements were generated based on the domain experts input and lead to development and integration of appropriate methods for visualization and analysis of atmospheric data. The methods range from volume rendering, interactive slicing, iso-surface techniques to interactive probing. All visualization methods are integrated in DLR's Terrain Rendering application. With this, the high resolution surface data visualization can be enriched with additional methods appropriate for atmospheric data sets. This results in an integrated virtual environment where the scientist has the possibility to interactively explore his data sets directly within the correct context. The data sets include volumetric data of the martian atmosphere, precomputed two dimensional maps and vertical profiles. In most cases the surface data as well as the atmospheric data has global coverage and is of time dependent nature. Furthermore, all interaction is synchronized between different connected application instances, allowing for collaborative sessions between distant experts. 2 VISUALIZATION TECHNIQUES Also the application is currently used for visualization of data sets related to Mars the techniques can be used for other data sets as well. Currently the prototype is capable of handling 2 and 2.5D surface data as well as 4D atmospheric data. Specifically, the surface data is presented using an LoD approach which is based on the HEALPix tessellation of a sphere [3, 4, 5] and can handle data sets in the order of

Large Field Visualization with Demand-Driven Calculation

Science.gov (United States)

Moran, Patrick J.; Henze, Chris

1999-01-01

We present a system designed for the interactive definition and visualization of fields derived from large data sets: the Demand-Driven Visualizer (DDV). The system allows the user to write arbitrary expressions to define new fields, and then apply a variety of visualization techniques to the result. Expressions can include differential operators and numerous other built-in functions, ail of which are evaluated at specific field locations completely on demand. The payoff of following a demand-driven design philosophy throughout becomes particularly evident when working with large time-series data, where the costs of eager evaluation alternatives can be prohibitive.

The application of complex network time series analysis in turbulent heated jets

International Nuclear Information System (INIS)

Charakopoulos, A. K.; Karakasidis, T. E.; Liakopoulos, A.; Papanicolaou, P. N.

2014-01-01

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics

Visual complications following irradiation for pituitary adenomas and craniopharyngiomas

International Nuclear Information System (INIS)

Harris, J.R.; Levene, M.B.

1976-01-01

Of 55 patients with pituitary adenomas or craniopharyngiomas treated with irradiation, a retrospective study revealed that 5 sustained a visual loss compatible with radiation damage to the optic nerve. No patient who received less than 250 rads/day fractions showed such visual loss. Within the range of total dosages used in this series, total dose was not an important determinant of this complication. The time to occurrence of visual disturbance ranged from 5 to 34 months following therapy

Interaction for visualization

CERN Document Server

Tominski, Christian

2015-01-01

Visualization has become a valuable means for data exploration and analysis. Interactive visualization combines expressive graphical representations and effective user interaction. Although interaction is an important component of visualization approaches, much of the visualization literature tends to pay more attention to the graphical representation than to interaction.The goal of this work is to strengthen the interaction side of visualization. Based on a brief review of general aspects of interaction, we develop an interaction-oriented view on visualization. This view comprises five key as

Properties of Asymmetric Detrended Fluctuation Analysis in the time series of RR intervals

Science.gov (United States)

Piskorski, J.; Kosmider, M.; Mieszkowski, D.; Krauze, T.; Wykretowicz, A.; Guzik, P.

2018-02-01

Heart rate asymmetry is a phenomenon by which the accelerations and decelerations of heart rate behave differently, and this difference is consistent and unidirectional, i.e. in most of the analyzed recordings the inequalities have the same directions. So far, it has been established for variance and runs based types of descriptors of RR intervals time series. In this paper we apply the newly developed method of Asymmetric Detrended Fluctuation Analysis, which so far has mainly been used with economic time series, to the set of 420 stationary 30 min time series of RR intervals from young, healthy individuals aged between 20 and 40. This asymmetric approach introduces separate scaling exponents for rising and falling trends. We systematically study the presence of asymmetry in both global and local versions of this method. In this study global means "applying to the whole time series" and local means "applying to windows jumping along the recording". It is found that the correlation structure of the fluctuations left over after detrending in physiological time series shows strong asymmetric features in both magnitude, with α+ physiological data after shuffling or with a group of symmetric synthetic time series.

A Comparison of Missing-Data Procedures for Arima Time-Series Analysis

Science.gov (United States)

Velicer, Wayne F.; Colby, Suzanne M.

2005-01-01

Missing data are a common practical problem for longitudinal designs. Time-series analysis is a longitudinal method that involves a large number of observations on a single unit. Four different missing-data methods (deletion, mean substitution, mean of adjacent observations, and maximum likelihood estimation) were evaluated. Computer-generated…

Processamento visual da forma: análise de sistema linear e alguns paradigmas psicofísicos Visual processing of form: linear system analysis and some psychophysical paradigms

Directory of Open Access Journals (Sweden)

Natanael Antonio dos Santos

2002-01-01

Full Text Available O objetivo deste trabalho é discutir alguns aspectos conceituais básicos da análise de Fourier enquanto ferramenta que fundamenta a perspectiva de filtros ou canais múltiplos de freqüências espaciais no estudo do processamento visual da forma. Serão também discutidos alguns dos principais paradigmas psicofísicos utilizados para caracterizar a resposta do sistema visual humano para filtros de freqüências espaciais de banda estreita. A análise de sistema linear e alguns paradigmas psicofísicos têm contribuído para o desenvolvimento teórico da percepção e do processamento visual da forma.The goal of this work is to discuss some basic aspects of Fourier analysis as a tool to be used in the approach of multiple channels of spatial frequencies on the study of visual processing of form. Some of the psychophysical paradigms more frequently used to characterize response of the human visual system to spatial frequency filter of narrow-band. The linear system analysis and some psychophysical paradigms have contributed to theoretical development of perception and of the visual processing of form.

Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

Science.gov (United States)

Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

2015-01-01

Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.

Analysis of relationship among visual evoked potential, oscillatory potential and visual acuity under stimulated weightlessness

Directory of Open Access Journals (Sweden)

Jun Zhao

2013-05-01

Full Text Available AIM: To observe the influence of head-down tilt simulated weightlessness on visual evoked potential(VEP, oscillatory potentials(OPsand visual acuity, and analyse the relationship among them. METHODS: Head-down tilt for -6° was adopted in 14 healthy volunteers. Distant visual acuity, near visual acuity, VEP and OPs were recorded before, two days and five days after trial. The record procedure of OPs followed the ISCEV standard for full-field clinical electroretinography(2008 update. RESULTS: Significant differences were detected in the amplitude of P100 waves and ∑OPs among various time points(P<0.05. But no relationship was observed among VEP, OPs and visual acuity. CONCLUSION: Head-down tilt simulated weightlessness induce the rearrange of blood of the whole body including eyes, which can make the change of visual electrophysiology but not visual acuity.

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG.

Science.gov (United States)

Dalal, Sarang S; Zumer, Johanna M; Guggisberg, Adrian G; Trumpis, Michael; Wong, Daniel D E; Sekihara, Kensuke; Nagarajan, Srikantan S

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.

Visual Linguistic Analysis of Political Discussions : Measuring Deliberative Quality

OpenAIRE

Gold, Valentin; El-Assady, Mennatallah; Hautli-Janisz, Annette; Bögel, Tina; Rohrdantz, Christian; Butt, Miriam; Holzinger, Katharina; Keim, Daniel

2017-01-01

This article reports on a Digital Humanities research project which is concerned with the automated linguistic and visual analysis of political discourses with a particular focus on the concept of deliberative communication. According to the theory of deliberative communication as discussed within political science, political debates should be inclusive and stakeholders participating in these debates are required to justify their positions rationally and respectfully and should eventually def...

How cortical neurons help us see: visual recognition in the human brain

OpenAIRE

Blumberg, Julie; Kreiman, Gabriel

2010-01-01

Through a series of complex transformations, the pixel-like input to the retina is converted into rich visual perceptions that constitute an integral part of visual recognition. Multiple visual problems arise due to damage or developmental abnormalities in the cortex of the brain. Here, we provide an overview of how visual information is processed along the ventral visual cortex in the human brain. We discuss how neurophysiological recordings in macaque monkeys and in humans can help us under...

Adaptive Kalman filtering for real-time mapping of the visual field

Science.gov (United States)

Ward, B. Douglas; Janik, John; Mazaheri, Yousef; Ma, Yan; DeYoe, Edgar A.

2013-01-01

This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume. PMID:22100663

Exploration of High-Dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization

Energy Technology Data Exchange (ETDEWEB)

Dan Maljovec; Bei Wang; Valerio Pascucci; Peer-Timo Bremer; Michael Pernice; Robert Nourgaliev

2013-05-01

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.

The left visual-field advantage in rapid visual presentation is amplified rather than reduced by posterior-parietal rTMS

DEFF Research Database (Denmark)

Verleger, Rolf; Möller, Friderike; Kuniecki, Michal

2010-01-01

) either as effective or as sham stimulation. In two experiments, either one of these two factors, hemisphere and effectiveness of rTMS, was varied within or between participants. Again, T2 was much better identified in the left than in the right visual field. This advantage of the left visual field......In the present task, series of visual stimuli are rapidly presented left and right, containing two target stimuli, T1 and T2. In previous studies, T2 was better identified in the left than in the right visual field. This advantage of the left visual field might reflect dominance exerted...... by the right over the left hemisphere. If so, then repetitive transcranial magnetic stimulation (rTMS) to the right parietal cortex might release the left hemisphere from right-hemispheric control, thereby improving T2 identification in the right visual field. Alternatively or additionally, the asymmetry in T2...

How cortical neurons help us see: visual recognition in the human brain

Science.gov (United States)

Blumberg, Julie; Kreiman, Gabriel

2010-01-01

Through a series of complex transformations, the pixel-like input to the retina is converted into rich visual perceptions that constitute an integral part of visual recognition. Multiple visual problems arise due to damage or developmental abnormalities in the cortex of the brain. Here, we provide an overview of how visual information is processed along the ventral visual cortex in the human brain. We discuss how neurophysiological recordings in macaque monkeys and in humans can help us understand the computations performed by visual cortex. PMID:20811161

Fermeuse wind power project Newfoundland : noise and visual analysis studies

Energy Technology Data Exchange (ETDEWEB)

Henn, P.; Turgeon, J.; Heraud, P.; Belanger, S.; Dakousian, S.; Lamontagne, C.; Soares, D. [Helimax Energy Inc., Montreal, PQ (Canada); Basil, C.; Boulianne, S.; Salacup, S.; Thompson, C. [Skypower, Toronto, ON (Canada)

2008-03-15

This paper discussed the noise and visual analyses used to assess the potential impacts of a wind energy project on the east coast of the Avalon Peninsula near St. John's, Newfoundland. The proposed farm will be located approximately 1 km away from the town of Fermeuse, and will have an installed capacity of 27 MW from 9 turbines. The paper provided details of the consultation process conducted to determine acceptable distance and site locations for the wind turbines from the community. Stakeholders were identified during meetings, events, and discussions with local authorities. Consultations were also held with government agencies and municipal councils. A baseline acoustic environment study was conducted, and details of anticipated environmental impacts during the project's construction, operation, and decommissioning phases were presented. The visual analysis study was divided into the following landscape units: town, shoreline, forest, open land and lacustrine landscapes. The effect of the turbines on the landscapes were assessed from different viewpoints using visual simulation programs. The study showed that the visual effects of the project are not considered as significant because of the low number of turbines. It was concluded that the effect of construction on ambient noise levels is of low concern as all permanent dwellings are located at least 1 km away from the turbines. 2 refs., 4 tabs., 4 figs.

Music in film and animation: experimental semiotics applied to visual, sound and musical structures

Science.gov (United States)

Kendall, Roger A.

2010-02-01

The relationship of music to film has only recently received the attention of experimental psychologists and quantificational musicologists. This paper outlines theory, semiotical analysis, and experimental results using relations among variables of temporally organized visuals and music. 1. A comparison and contrast is developed among the ideas in semiotics and experimental research, including historical and recent developments. 2. Musicological Exploration: The resulting multidimensional structures of associative meanings, iconic meanings, and embodied meanings are applied to the analysis and interpretation of a range of film with music. 3. Experimental Verification: A series of experiments testing the perceptual fit of musical and visual patterns layered together in animations determined goodness of fit between all pattern combinations, results of which confirmed aspects of the theory. However, exceptions were found when the complexity of the stratified stimuli resulted in cognitive overload.

A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)

2012-02-01

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

Visual cognition

Energy Technology Data Exchange (ETDEWEB)

Pinker, S.

1985-01-01

This book consists of essays covering issues in visual cognition presenting experimental techniques from cognitive psychology, methods of modeling cognitive processes on computers from artificial intelligence, and methods of studying brain organization from neuropsychology. Topics considered include: parts of recognition; visual routines; upward direction; mental rotation, and discrimination of left and right turns in maps; individual differences in mental imagery, computational analysis and the neurological basis of mental imagery: componental analysis.

Outcomes of visual acuity in carbon ion radiotherapy: Analysis of dose-volume histograms and prognostic factors

International Nuclear Information System (INIS)

Hasegawa, Azusa; Mizoe, Jun-etsu; Mizota, Atsushi; Tsujii, Hirohiko

2006-01-01

Purpose: To analyze the tolerance dose for retention of visual acuity in patients with head-and-neck tumors treated with carbon ion radiotherapy. Methods and Materials: From June 1994 to March 2000, 163 patients with tumors in the head and neck or skull base region were treated with carbon ion radiotherapy. Analysis was performed on 54 optic nerves (ONs) corresponding to 30 patients whose ONs had been included in the irradiated volume. These patients showed no evidence of visual impairment due to other factors and had a follow-up period of >4 years. All patients had been informed of the possibility of visual impairment before treatment. We evaluated the dose-complication probability and the prognostic factors for the retention of visual acuity in carbon ion radiotherapy, using dose-volume histograms and multivariate analysis. Results: The median age of 30 patients (14 men, 16 women) was 57.2 years. Median prescribed total dose was 56.0 gray equivalents (GyE) at 3.0-4.0 GyE per fraction per day (range, 48-64 GyE; 16-18 fractions; 4-6 weeks). Of 54 ONs that were analyzed, 35 had been irradiated with max ]) resulting in no visual loss. Conversely, 11 of the 19 ONs (58%) irradiated with >57 GyE (D max ) suffered a decrease of visual acuity. In all of these cases, the ONs had been involved in the tumor before carbon ion radiotherapy. In the multivariate analysis, a dose of 20% of the volume of the ON (D 2 ) was significantly associated with visual loss. Conclusions: The occurrence of visual loss seems to be correlated with a delivery of >60 GyE to 20% of the volume of the ON

Visualizing solvent mediated phase transformation behavior of carbamazepine polymorphs by principal component analysis

DEFF Research Database (Denmark)

Tian, Fang; Rades, Thomas; Sandler, Niklas

2008-01-01

The purpose of this research is to gain a greater insight into the hydrate formation processes of different carbamazepine (CBZ) anhydrate forms in aqueous suspension, where principal component analysis (PCA) was applied for data analysis. The capability of PCA to visualize and to reveal simplified...

The neural correlates of visual imagery: A co-ordinate-based meta-analysis.

Science.gov (United States)

Winlove, Crawford I P; Milton, Fraser; Ranson, Jake; Fulford, Jon; MacKisack, Matthew; Macpherson, Fiona; Zeman, Adam

2018-01-02

Visual imagery is a form of sensory imagination, involving subjective experiences typically described as similar to perception, but which occur in the absence of corresponding external stimuli. We used the Activation Likelihood Estimation algorithm (ALE) to identify regions consistently activated by visual imagery across 40 neuroimaging studies, the first such meta-analysis. We also employed a recently developed multi-modal parcellation of the human brain to attribute stereotactic co-ordinates to one of 180 anatomical regions, the first time this approach has been combined with the ALE algorithm. We identified a total 634 foci, based on measurements from 464 participants. Our overall comparison identified activation in the superior parietal lobule, particularly in the left hemisphere, consistent with the proposed 'top-down' role for this brain region in imagery. Inferior premotor areas and the inferior frontal sulcus were reliably activated, a finding consistent with the prominent semantic demands made by many visual imagery tasks. We observed bilateral activation in several areas associated with the integration of eye movements and visual information, including the supplementary and cingulate eye fields (SCEFs) and the frontal eye fields (FEFs), suggesting that enactive processes are important in visual imagery. V1 was typically activated during visual imagery, even when participants have their eyes closed, consistent with influential depictive theories of visual imagery. Temporal lobe activation was restricted to area PH and regions of the fusiform gyrus, adjacent to the fusiform face complex (FFC). These results provide a secure foundation for future work to characterise in greater detail the functional contributions of specific areas to visual imagery. Copyright © 2017. Published by Elsevier Ltd.

Analysis of Land Subsidence Monitoring in Mining Area with Time-Series Insar Technology

Science.gov (United States)

Sun, N.; Wang, Y. J.

2018-04-01

Time-series InSAR technology has become a popular land subsidence monitoring method in recent years, because of its advantages such as high accuracy, wide area, low expenditure, intensive monitoring points and free from accessibility restrictions. In this paper, we applied two kinds of satellite data, ALOS PALSAR and RADARSAT-2, to get the subsidence monitoring results of the study area in two time periods by time-series InSAR technology. By analyzing the deformation range, rate and amount, the time-series analysis of land subsidence in mining area was realized. The results show that InSAR technology could be used to monitor land subsidence in large area and meet the demand of subsidence monitoring in mining area.

VISPA - Visual Physics Analysis on Linux, Mac OS X and Windows

International Nuclear Information System (INIS)

Brodski, M.; Erdmann, M.; Fischer, R.; Hinzmann, A.; Klimkovich, T.; Mueller, G.; Muenzer, T.; Steggemann, J.; Winchen, T.

2009-01-01

Modern physics analysis is an iterative task consisting of prototyping, executing and verifying the analysis procedure. For supporting scientists in each step of this process, we developed VISPA: a toolkit based on graphical and textual elements for visual physics analysis. Unlike many other analysis frameworks VISPA runs on Linux, Windows and Mac OS X. VISPA can be used in any experiment with serial data flow. In particular, VISPA can be connected to any high energy physics experiment. Furthermore, datatypes for the usage in astroparticle physics have recently been successfully included. An analysis on the data is performed in several steps, each represented by an individual module. While modules e.g. for file input and output are already provided, additional modules can be written by the user with C++ or the Python language. From individual modules, the analysis is designed by graphical connections representing the data flow. This modular concept assists the user in fast prototyping of the analysis and improves the reusability of written source code. The execution of the analysis can be performed directly from the GUI, or on any supported computer in batch mode. Therefore the analysis can be transported from the laptop to other machines. The recently improved GUI of VISPA is based on a plug-in mechanism. Besides components for the development and execution of physics analysis, additional plug-ins are available for the visualization of e.g. the structure of high energy physics events or the properties of cosmic rays in an astroparticle physics analysis. Furthermore plug-ins have been developed to display and edit configuration files of individual experiments from within the VISPA GUI. (author)

Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy.

Science.gov (United States)

Biglands, John D; Ibraheem, Montasir; Magee, Derek R; Radjenovic, Aleksandra; Plein, Sven; Greenwood, John P

2018-05-01

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial

The dynamics of visual experience, an EEG study of subjective pattern formation.

Directory of Open Access Journals (Sweden)

Mark A Elliott

Full Text Available BACKGROUND: Since the origin of psychological science a number of studies have reported visual pattern formation in the absence of either physiological stimulation or direct visual-spatial references. Subjective patterns range from simple phosphenes to complex patterns but are highly specific and reported reliably across studies. METHODOLOGY/PRINCIPAL FINDINGS: Using independent-component analysis (ICA we report a reduction in amplitude variance consistent with subjective-pattern formation in ventral posterior areas of the electroencephalogram (EEG. The EEG exhibits significantly increased power at delta/theta and gamma-frequencies (point and circle patterns or a series of high-frequency harmonics of a delta oscillation (spiral patterns. CONCLUSIONS/SIGNIFICANCE: Subjective-pattern formation may be described in a way entirely consistent with identical pattern formation in fluids or granular flows. In this manner, we propose subjective-pattern structure to be represented within a spatio-temporal lattice of harmonic oscillations which bind topographically organized visual-neuronal assemblies by virtue of low frequency modulation.

SATORI: a system for ontology-guided visual exploration of biomedical data repositories.

Science.gov (United States)

Lekschas, Fritz; Gehlenborg, Nils

2018-04-01

The ever-increasing number of biomedical datasets provides tremendous opportunities for re-use but current data repositories provide limited means of exploration apart from text-based search. Ontological metadata annotations provide context by semantically relating datasets. Visualizing this rich network of relationships can improve the explorability of large data repositories and help researchers find datasets of interest. We developed SATORI-an integrative search and visual exploration interface for the exploration of biomedical data repositories. The design is informed by a requirements analysis through a series of semi-structured interviews. We evaluated the implementation of SATORI in a field study on a real-world data collection. SATORI enables researchers to seamlessly search, browse and semantically query data repositories via two visualizations that are highly interconnected with a powerful search interface. SATORI is an open-source web application, which is freely available at http://satori.refinery-platform.org and integrated into the Refinery Platform. nils@hms.harvard.edu. Supplementary data are available at Bioinformatics online.

Visualization-based analysis of multiple response survey data

Science.gov (United States)

Timofeeva, Anastasiia

2017-11-01

During the survey, the respondents are often allowed to tick more than one answer option for a question. Analysis and visualization of such data have difficulties because of the need for processing multiple response variables. With standard representation such as pie and bar charts, information about the association between different answer options is lost. The author proposes a visualization approach for multiple response variables based on Venn diagrams. For a more informative representation with a large number of overlapping groups it is suggested to use similarity and association matrices. Some aggregate indicators of dissimilarity (similarity) are proposed based on the determinant of the similarity matrix and the maximum eigenvalue of association matrix. The application of the proposed approaches is well illustrated by the example of the analysis of advertising sources. Intersection of sets indicates that the same consumer audience is covered by several advertising sources. This information is very important for the allocation of the advertising budget. The differences between target groups in advertising sources are of interest. To identify such differences the hypothesis of homogeneity and independence are tested. Recent approach to the problem are briefly reviewed and compared. An alternative procedure is suggested. It is based on partition of a consumer audience into pairwise disjoint subsets and includes hypothesis testing of the difference between the population proportions. It turned out to be more suitable for the real problem being solved.

Utilization and Organization of Visually Presented Information. Final Report.

Science.gov (United States)

Dick, A. O.

The experiments discussed in this report do not have a direct relationship to each other but represent work on a series of sub-issues within the general framework of visual processing of information. Because of this discreteness, the report is organized into a series of papers. The first is a general review of tachistoscopic work on iconic memory…

Definition of distance for nonlinear time series analysis of marked point process data

Energy Technology Data Exchange (ETDEWEB)

Iwayama, Koji, E-mail: koji@sat.t.u-tokyo.ac.jp [Research Institute for Food and Agriculture, Ryukoku Univeristy, 1-5 Yokotani, Seta Oe-cho, Otsu-Shi, Shiga 520-2194 (Japan); Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)