Science.gov

Sample records for advanced spatial analysis

  1. Advances in diagnosis and spatial analysis of cysticercosis and taeniasis.

    PubMed

    Raoul, Francis; Li, Tiaoying; Sako, Yasuhito; Chen, Xingwang; Long, Changping; Yanagida, Tetsuya; Wu, Yunfei; Nakao, Minoru; Okamoto, Munehiro; Craig, Philip S; Giraudoux, Patrick; Ito, Akira

    2013-11-01

    Human cysticercosis, caused by accidental ingestion of eggs of Taenia solium, is one of the most pathogenic helminthiases and is listed among the 17 WHO Neglected Tropical Diseases. Controlling the life-cycle of T. solium between humans and pigs is essential for eradication of cysticercosis. One difficulty for the accurate detection and identification of T. solium species is the possible co-existence of two other human Taenia tapeworms (T. saginata and T. asiatica, which do not cause cysticercosis in humans). Several key issues for taeniasis/cysticercosis (T/C) evidence-based epidemiology and control are reviewed: (1) advances in immunological and molecular tools for screening of human and animals hosts and identification of Taenia species, with a focus on real-time detection of taeniasis carriers and infected animals in field community screenings, and (2) spatial ecological approaches that have been used to detect geospatial patterns of case distributions and to monitor pig activity and behaviour. Most recent eco-epidemiological studies undertaken in Sichuan province, China, are introduced and reviewed. PMID:23985371

  2. Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

    NASA Technical Reports Server (NTRS)

    Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

    2013-01-01

    The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

  3. Geologic spatial analysis

    SciTech Connect

    Thiessen, R.L.; Eliason, J.R.

    1989-01-01

    This report describes the development of geologic spatial analysis research which focuses on conducting comprehensive three-dimensional analysis of regions using geologic data sets that can be referenced by latitude, longitude, and elevation/depth. (CBS)

  4. Spatial Data Analysis.

    PubMed

    Banerjee, Sudipto

    2016-01-01

    With increasing accessibility to geographic information systems (GIS) software, statisticians and data analysts routinely encounter scientific data sets with geocoded locations. This has generated considerable interest in statistical modeling for location-referenced spatial data. In public health, spatial data routinely arise as aggregates over regions, such as counts or rates over counties, census tracts, or some other administrative delineation. Such data are often referred to as areal data. This review article provides a brief overview of statistical models that account for spatial dependence in areal data. It does so in the context of two applications: disease mapping and spatial survival analysis. Disease maps are used to highlight geographic areas with high and low prevalence, incidence, or mortality rates of a specific disease and the variability of such rates over a spatial domain. They can also be used to detect hot spots or spatial clusters that may arise owing to common environmental, demographic, or cultural effects shared by neighboring regions. Spatial survival analysis refers to the modeling and analysis for geographically referenced time-to-event data, where a subject is followed up to an event (e.g., death or onset of a disease) or is censored, whichever comes first. Spatial survival analysis is used to analyze clustered survival data when the clustering arises from geographical regions or strata. Illustrations are provided in these application domains. PMID:26789381

  5. Spatial Data Analysis.

    PubMed

    Banerjee, Sudipto

    2016-01-01

    With increasing accessibility to geographic information systems (GIS) software, statisticians and data analysts routinely encounter scientific data sets with geocoded locations. This has generated considerable interest in statistical modeling for location-referenced spatial data. In public health, spatial data routinely arise as aggregates over regions, such as counts or rates over counties, census tracts, or some other administrative delineation. Such data are often referred to as areal data. This review article provides a brief overview of statistical models that account for spatial dependence in areal data. It does so in the context of two applications: disease mapping and spatial survival analysis. Disease maps are used to highlight geographic areas with high and low prevalence, incidence, or mortality rates of a specific disease and the variability of such rates over a spatial domain. They can also be used to detect hot spots or spatial clusters that may arise owing to common environmental, demographic, or cultural effects shared by neighboring regions. Spatial survival analysis refers to the modeling and analysis for geographically referenced time-to-event data, where a subject is followed up to an event (e.g., death or onset of a disease) or is censored, whichever comes first. Spatial survival analysis is used to analyze clustered survival data when the clustering arises from geographical regions or strata. Illustrations are provided in these application domains.

  6. Pennsylvania Spatial Data Access and Online Advanced Spatial Information Systems

    NASA Astrophysics Data System (ADS)

    Lin, H.; Petersen, G.; Kelly, M.; Day, R.

    2002-05-01

    The Pennsylvania Spatial Data Access system (PASDA) is Pennsylvania's official geospatial information clearinghouse and the Commonwealth's node on the National Spatial Data Infrastructure. The PASDA clearinghouse provides for the widespread sharing of geospatial data, eliminates the creation of redundant data sets, and serves as a resource for locating data throughout the Commonwealth through its comprehensive standardized data storage, online free download, interactive mapping tools, and metadata/documentation efforts. PASDA also serves as a primary member of the Geography Network, a node of the National Biological Information Infrastructure for fisheries and aquatic resources, and provides several WebGIS applications such as Pennsylvania Explorer and Pennsylvania Interactive Watershed Atlas. With PASDA data delivery and access mechanisms in place, we are further building Online Advanced Spatial Information Systems (OASIS) for 1) geospatial data mining and knowledge discovery and 2) intelligent spatial decision support. The OASIS intends to integrate artificial intelligence, spatial modeling, data mining tools, and expert systems into PASDA so that a mechanism for transforming geospatial data into information, synthesizing geospatial knowledge, and supporting spatial decision-making may be developed.

  7. A New Methodology of Spatial Cross-Correlation Analysis

    PubMed Central

    Chen, Yanguang

    2015-01-01

    Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

  8. Advanced PFBC transient analysis

    SciTech Connect

    White, J.S.; Bonk, D.L.

    1997-05-01

    Transient modeling and analysis of advanced Pressurized Fluidized Bed Combustion (PFBC) systems is a research area that is currently under investigation by the US Department of Energy`s Federal Energy Technology Center (FETC). The object of the effort is to identify key operating parameters that affect plant performance and then quantify the basic response of major sub-systems to changes in operating conditions. PC-TRAX{trademark}, a commercially available dynamic software program, was chosen and applied in this modeling and analysis effort. This paper describes the development of a series of TRAX-based transient models of advanced PFBC power plants. These power plants burn coal or other suitable fuel in a PFBC, and the high temperature flue gas supports low-Btu fuel gas or natural gas combustion in a gas turbine topping combustor. When it is utilized, the low-Btu fuel gas is produced in a bubbling bed carbonizer. High temperature, high pressure combustion products exiting the topping combustor are expanded in a modified gas turbine to generate electrical power. Waste heat from the system is used to raise and superheat steam for a reheat steam turbine bottoming cycle that generates additional electrical power. Basic control/instrumentation models were developed and modeled in PC-TRAX and used to investigate off-design plant performance. System performance for various transient conditions and control philosophies was studied.

  9. Advances in Spectral-Spatial Classification of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  10. Advanced Economic Analysis

    NASA Technical Reports Server (NTRS)

    Greenberg, Marc W.; Laing, William

    2013-01-01

    An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

  11. Resource materials for a GIS spatial analysis course

    USGS Publications Warehouse

    Raines, Gary L.

    2001-01-01

    This report consists of materials prepared for a GIS spatial analysis course offered as part of the Geography curriculum at the University of Nevada, Reno and the University of California at Santa Barbara in the spring of 2000. The report is intended to share information with instructors preparing spatial-modeling training and scientists with advanced GIS expertise. The students taking this class had completed each universities GIS curriculum and had a foundation in statistics as part of a science major. This report is organized into chapters that contain the following: Slides used during lectures, Guidance on the use of Arcview, Introduction to filtering in Arcview, Conventional and spatial correlation in Arcview, Tools for fuzzification in Arcview, Data and instructions for creating using ArcSDM for simple weights-of-evidence, fuzzy logic, and neural network models for Carlin-type gold deposits in central Nevada, Reading list on spatial modeling, and Selected student spatial-modeling posters from the laboratory exercises.

  12. Spatial uncertainty analysis of population models

    SciTech Connect

    Jager, Yetta; King, Anthony Wayne; Schumaker, Nathan; Ashwood, Tom L; Jackson, Barbara L

    2004-01-01

    This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single reference map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species' habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum

  13. Statistics analysis embedded in spatial DBMS

    NASA Astrophysics Data System (ADS)

    Chen, Rongguo; Chen, Siqing

    2006-10-01

    This article sets forth the principle and methodology for implementing spatial database management system (DBMS) by using open source object-relational DBMS - PostgreSQL. The geospatial data model and spatial analysis and processing operations for spatial objects and datasets can be inserted into the DBMS by extended SQL. To implement the statistics analysis embedded in spatial DBMS, an open source statistical program R is introduced to extend the capability of the spatial DBMS. R is a language and environment for statistical computing and graphics. There is a large sum of statistical methods in the form of packages in R. Many classical and modern spatial statistical techniques are implemented in R environment. PL/R is a loadable procedural language containing most of the capabilities in R language which is extensible and enables user to write DBMS functions and triggers in R language. Therefore, the PL/R will extend its capability of spatial statistics and geostatistics when the two kinds of packages are loaded into R language. The PL/R can be extended without limit so that any new method of statistics analysis embedded into the spatial DBMS becomes very convenient.

  14. Spatial analysis to support geographic targeting of genotypes to environments

    PubMed Central

    Hyman, Glenn; Hodson, Dave; Jones, Peter

    2013-01-01

    Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts. PMID:23515351

  15. Spatial and temporal scene analysis

    NASA Astrophysics Data System (ADS)

    Rollins, J. Michael; Chaapel, Charles; Bleiweiss, Max P.

    1994-06-01

    Current efforts to design reliable background scene generation programs require validation using real images for comparison. A crucial step in making objective comparisons is to parameterize the real and generated images into a common set of feature metrics. Such metrics can be derived from statistical and transform-based analyses and yield information about the structures and textures present in various image regions of interest. This paper presents the results of such a metrics-development process for the smart weapons operability enhancement (SWOE) joint test and evaluation (JT&E) program. Statistical and transform based techniques were applied to images obtained from two separate locations, Grayling, Michigan and Yuma, Arizona, at various times of day and under a variety of environmental conditions. Statistical analyses of scene radiance distributions and `clutter' content were performed both spatially and temporally. Fourier and wavelet transform methods were applied as well. Results and their interpretations are given for the image analyses. The metrics that provide the clearest and most reliable distinction between feature classes are recommended.

  16. Geostatistics and spatial analysis in biological anthropology.

    PubMed

    Relethford, John H

    2008-05-01

    A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology.

  17. Analysis of Advanced Rotorcraft Configurations

    NASA Technical Reports Server (NTRS)

    Johnson, Wayne

    2000-01-01

    Advanced rotorcraft configurations are being investigated with the objectives of identifying vehicles that are larger, quieter, and faster than current-generation rotorcraft. A large rotorcraft, carrying perhaps 150 passengers, could do much to alleviate airport capacity limitations, and a quiet rotorcraft is essential for community acceptance of the benefits of VTOL operations. A fast, long-range, long-endurance rotorcraft, notably the tilt-rotor configuration, will improve rotorcraft economics through productivity increases. A major part of the investigation of advanced rotorcraft configurations consists of conducting comprehensive analyses of vehicle behavior for the purpose of assessing vehicle potential and feasibility, as well as to establish the analytical models required to support the vehicle development. The analytical work of FY99 included applications to tilt-rotor aircraft. Tilt Rotor Aeroacoustic Model (TRAM) wind tunnel measurements are being compared with calculations performed by using the comprehensive analysis tool (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD 11)). The objective is to establish the wing and wake aerodynamic models that are required for tilt-rotor analysis and design. The TRAM test in the German-Dutch Wind Tunnel (DNW) produced extensive measurements. This is the first test to encompass air loads, performance, and structural load measurements on tilt rotors, as well as acoustic and flow visualization data. The correlation of measurements and calculations includes helicopter-mode operation (performance, air loads, and blade structural loads), hover (performance and air loads), and airplane-mode operation (performance).

  18. Sex differences in spatial cognition: advancing the conversation.

    PubMed

    Levine, Susan C; Foley, Alana; Lourenco, Stella; Ehrlich, Stacy; Ratliff, Kristin

    2016-01-01

    The existence of a sex difference in spatial thinking, notably on tasks involving mental rotation, has been a topic of considerable research and debate. We review this literature, with a particular focus on the development of this sex difference, and consider four key questions: (1) When does the sex difference emerge developmentally and does the magnitude of this difference change across development? (2) What are the biological and environmental factors that contribute to sex differences in spatial skill and how might they interact? (3) How malleable are spatial skills, and is the sex difference reduced as a result of training? and (4) Does 'spatializing' the curriculum raise the level of spatial thinking in all students and hold promise for increasing and diversifying the STEM pipeline? Throughout the review, we consider promising avenues for future research. PMID:26825049

  19. Providing Spatial Data for Secondary Analysis

    PubMed Central

    Gutmann, Myron; Witkowski, Kristine; Colyer, Corey; O’Rourke, JoAnne McFarland; McNally, James

    2008-01-01

    Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis -- the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents. PMID:19122860

  20. Joint spatial analysis of gastrointestinal infectious diseases.

    PubMed

    Held, Leonhard; Graziano, Giusi; Frank, Christina; Rue, Håvard

    2006-10-01

    A major obstacle in the spatial analysis of infectious disease surveillance data is the problem of under-reporting. This article investigates the possibility of inferring reporting rates through joint statistical modelling of several infectious diseases with different aetiologies. Once variation in under-reporting can be estimated, geographic risk patterns for infections associated with specific food vehicles may be discerned. We adopt the shared component model, proposed by Knorr-Held and Best for two chronic diseases and further extended by (Held L, Natario I, Fenton S, Rue H, Becker N. Towards joint disease mapping. Statistical Methods in Medical Research 2005b; 14: 61-82) for more than two chronic diseases to the infectious disease setting. Our goal is to estimate a shared component, common to all diseases, which may be interpreted as representing the spatial variation in reporting rates. Additional components are introduced to describe the real spatial variation of the different diseases. Of course, this interpretation is only allowed under specific assumptions, in particular, the geographical variation in under-reporting should be similar for the diseases considered. In addition, it is vital that the data do not contain large local outbreaks, so adjustment based on a time series method recently proposed by (Held L, Höhle M, Hofmann M. A statistical framework for the analysis of multivariate infectious disease surveillance data. Statistical Modelling 2005a; 5: 187-99) is made at a preliminary stage. We will illustrate our approach through the analysis of gastrointestinal diseases notification data obtained from the German infectious disease surveillance system, administered by the Robert Koch Institute in Berlin.

  1. Incorporating spatial dependence in regional frequency analysis

    PubMed Central

    Wang, Zhuo; Yan, Jun; Zhang, Xuebin

    2014-01-01

    The efficiency of regional frequency analysis (RFA) is undermined by intersite dependence, which is usually ignored in parameter estimation. We propose a spatial index flood model where marginal generalized extreme value distributions are joined by an extreme-value copula characterized by a max-stable process for the spatial dependence. The parameters are estimated with a pairwise likelihood constructed from bivariate marginal generalized extreme value distributions. The estimators of model parameters and return levels can be more efficient than those from the traditional index flood model when the max-stable process fits the intersite dependence well. Through simulation, we compared the pairwise likelihood method with an L-moment method and an independence likelihood method under various spatial dependence models and dependence levels. The pairwise likelihood method was found to be the most efficient in mean squared error if the dependence model was correctly specified. When the dependence model was misspecified within the max-stable models, the pairwise likelihood method was still competitive relative to the other two methods. When the dependence model was not a max-stable model, the pairwise likelihood method led to serious bias in estimating the shape parameter and return levels, especially when the dependence was strong. In an illustration with annual maximum precipitation data from Switzerland, the pairwise likelihood method yielded remarkable reduction in the standard errors of return level estimates in comparison to the L-moment method. PMID:25745273

  2. Spatial data analysis and environmental justice

    SciTech Connect

    Bahadur, R.; Samuels, W.B.; Williams, J.W.; Zeitoun, A.H.

    1997-08-01

    Evaluations of environmental justice for government actions concerned with the transportation of hazardous materials over cross country routes presents a significant challenge in spatial data analysis. The sheer volume of data required for accurate identification of minority and low-income populations along the routes and at the endpoints can be formidable. Managing and integrating large volumes of information with state-of-the-art tools is essential in the analysis of environmental justice and equity concerns surrounding transportation of hazardous materials. This paper discusses the role and limitations of geographical information systems in the analysis and visualization of populations potentially affected by the transportation of hazardous materials over transcontinental ground and water routes. Case studies are used to demonstrate the types of data and analyses needed for evaluations of environmental justice for cross country routes and end points. Inherent capabilities and limitations in spatial resolution are evaluated for environmental assessments in which potentially affected areas are quantified based on the physical characteristics of the hazardous cargo.

  3. [Statistical models for spatial analysis in parasitology].

    PubMed

    Biggeri, A; Catelan, D; Dreassi, E; Lagazio, C; Cringoli, G

    2004-06-01

    The simplest way to study the spatial pattern of a disease is the geographical representation of its cases (or some indicators of them) over a map. Maps based on raw data are generally "wrong" since they do not take into consideration for sampling errors. Indeed, the observed differences between areas (or points in the map) are not directly interpretable, as they derive from the composition of true, structural differences and of the noise deriving from the sampling process. This problem is well known in human epidemiology, and several solutions have been proposed to filter the signal from the noise. These statistical methods are usually referred to as Disease Mapping. In geographical analysis a first goal is to evaluate the statistical significance of the heterogeneity between areas (or points). If the test indicates rejection of the hypothesis of homogeneity the following task is to study the spatial pattern of the disease. The spatial variability of risk is usually decomposed into two terms: a spatially structured (clustering) and a non spatially structured (heterogeneity) one. The heterogeneity term reflects spatial variability due to intrinsic characteristics of the sampling units (e.g. igienic conditions of farms), while the clustering term models the association due to proximity between sampling units, that usually depends on ecological conditions that vary over the study area and that affect in similar way breedings that are close to each other. Hierarchical bayesian models are the main tool to make inference over the clustering and heterogeneity components. The results are based on the marginal posterior distributions of the parameters of the model, that are approximated by Monte Carlo Markov Chain methods. Different models can be defined depending on the terms that are considered, namely a model with only the clustering term, a model with only the heterogeneity term and a model where both are included. Model selection criteria based on a compromise between

  4. Advanced Extraction of Spatial Information from High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Pour, T.; Burian, J.; Miřijovský, J.

    2016-06-01

    In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  5. ADVANCED POWER SYSTEMS ANALYSIS TOOLS

    SciTech Connect

    Robert R. Jensen; Steven A. Benson; Jason D. Laumb

    2001-08-31

    The use of Energy and Environmental Research Center (EERC) modeling tools and improved analytical methods has provided key information in optimizing advanced power system design and operating conditions for efficiency, producing minimal air pollutant emissions and utilizing a wide range of fossil fuel properties. This project was divided into four tasks: the demonstration of the ash transformation model, upgrading spreadsheet tools, enhancements to analytical capabilities using the scanning electron microscopy (SEM), and improvements to the slag viscosity model. The ash transformation model, Atran, was used to predict the size and composition of ash particles, which has a major impact on the fate of the combustion system. To optimize Atran key factors such as mineral fragmentation and coalescence, the heterogeneous and homogeneous interaction of the organically associated elements must be considered as they are applied to the operating conditions. The resulting model's ash composition compares favorably to measured results. Enhancements to existing EERC spreadsheet application included upgrading interactive spreadsheets to calculate the thermodynamic properties for fuels, reactants, products, and steam with Newton Raphson algorithms to perform calculations on mass, energy, and elemental balances, isentropic expansion of steam, and gasifier equilibrium conditions. Derivative calculations can be performed to estimate fuel heating values, adiabatic flame temperatures, emission factors, comparative fuel costs, and per-unit carbon taxes from fuel analyses. Using state-of-the-art computer-controlled scanning electron microscopes and associated microanalysis systems, a method to determine viscosity using the incorporation of grey-scale binning acquired by the SEM image was developed. The image analysis capabilities of a backscattered electron image can be subdivided into various grey-scale ranges that can be analyzed separately. Since the grey scale's intensity is

  6. Advanced materials: Information and analysis needs

    SciTech Connect

    Curlee, T.R.; Das, S.; Lee, R.; Trumble, D.

    1990-09-01

    This report presents the findings of a study to identify the types of information and analysis that are needed for advanced materials. The project was sponsored by the US Bureau of Mines (BOM). It includes a conceptual description of information needs for advanced materials and the development and implementation of a questionnaire on the same subject. This report identifies twelve fundamental differences between advanced and traditional materials and discusses the implications of these differences for data and analysis needs. Advanced and traditional materials differ significantly in terms of physical and chemical properties. Advanced material properties can be customized more easily. The production of advanced materials may differ from traditional materials in terms of inputs, the importance of by-products, the importance of different processing steps (especially fabrication), and scale economies. The potential for change in advanced materials characteristics and markets is greater and is derived from the marriage of radically different materials and processes. In addition to the conceptual study, a questionnaire was developed and implemented to assess the opinions of people who are likely users of BOM information on advanced materials. The results of the questionnaire, which was sent to about 1000 people, generally confirm the propositions set forth in the conceptual part of the study. The results also provide data on the categories of advanced materials and the types of information that are of greatest interest to potential users. 32 refs., 1 fig., 12 tabs.

  7. ANALYSIS OF COVARIANCE WITH SPATIALLY CORRELATED SECONDARY VARIABLES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Data sets which contain measurements on a spatially referenced response and covariate are analyzed using either co-kriging or spatial analysis of covariance. While co-kriging accounts for the correlation structure of the covariate, it is purely a predictive tool. Alternatively, spatial analysis of c...

  8. Robust geostatistical analysis of spatial data

    NASA Astrophysics Data System (ADS)

    Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.

    2012-04-01

    Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled

  9. Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

    SciTech Connect

    Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono

    2004-06-01

    Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.

  10. Spatial analysis of notified dengue fever infections.

    PubMed

    Hu, W; Clements, A; Williams, G; Tong, S

    2011-03-01

    This study aimed to investigate the spatial clustering and dynamic dispersion of dengue incidence in Queensland, Australia. We used Moran's I statistic to assess the spatial autocorrelation of reported dengue cases. Spatial empirical Bayes smoothing estimates were used to display the spatial distribution of dengue in postal areas throughout Queensland. Local indicators of spatial association (LISA) maps and logistic regression models were used to identify spatial clusters and examine the spatio-temporal patterns of the spread of dengue. The results indicate that the spatial distribution of dengue was clustered during each of the three periods of 1993-1996, 1997-2000 and 2001-2004. The high-incidence clusters of dengue were primarily concentrated in the north of Queensland and low-incidence clusters occurred in the south-east of Queensland. The study concludes that the geographical range of notified dengue cases has significantly expanded in Queensland over recent years.

  11. Advanced analysis methods in particle physics

    SciTech Connect

    Bhat, Pushpalatha C.; /Fermilab

    2010-10-01

    Each generation of high energy physics experiments is grander in scale than the previous - more powerful, more complex and more demanding in terms of data handling and analysis. The spectacular performance of the Tevatron and the beginning of operations of the Large Hadron Collider, have placed us at the threshold of a new era in particle physics. The discovery of the Higgs boson or another agent of electroweak symmetry breaking and evidence of new physics may be just around the corner. The greatest challenge in these pursuits is to extract the extremely rare signals, if any, from huge backgrounds arising from known physics processes. The use of advanced analysis techniques is crucial in achieving this goal. In this review, I discuss the concepts of optimal analysis, some important advanced analysis methods and a few examples. The judicious use of these advanced methods should enable new discoveries and produce results with better precision, robustness and clarity.

  12. Spatial Uncertainty Analysis of Ecological Models

    SciTech Connect

    Jager, H.I.; Ashwood, T.L.; Jackson, B.L.; King, A.W.

    2000-09-02

    The authors evaluated the sensitivity of a habitat model and a source-sink population model to spatial uncertainty in landscapes with different statistical properties and for hypothetical species with different habitat requirements. Sequential indicator simulation generated alternative landscapes from a source map. Their results showed that spatial uncertainty was highest for landscapes in which suitable habitat was rare and spatially uncorrelated. Although, they were able to exert some control over the degree of spatial uncertainty by varying the sampling density drawn from the source map, intrinsic spatial properties (i.e., average frequency and degree of spatial autocorrelation) played a dominant role in determining variation among realized maps. To evaluate the ecological significance of landscape variation, they compared the variation in predictions from a simple habitat model to variation among landscapes for three species types. Spatial uncertainty in predictions of the amount of source habitat depended on both the spatial life history characteristics of the species and the statistical attributes of the synthetic landscapes. Species differences were greatest when the landscape contained a high proportion of suitable habitat. The predicted amount of source habitat was greater for edge-dependent (interior) species in landscapes with spatially uncorrelated(correlated) suitable habitat. A source-sink model demonstrated that, although variation among landscapes resulted in relatively little variation in overall population growth rate, this spatial uncertainty was sufficient in some situations, to produce qualitatively different predictions about population viability (i.e., population decline vs. increase).

  13. Advanced nuclear energy analysis technology.

    SciTech Connect

    Gauntt, Randall O.; Murata, Kenneth K.; Romero, Vicente JosÔe; Young, Michael Francis; Rochau, Gary Eugene

    2004-05-01

    A two-year effort focused on applying ASCI technology developed for the analysis of weapons systems to the state-of-the-art accident analysis of a nuclear reactor system was proposed. The Sandia SIERRA parallel computing platform for ASCI codes includes high-fidelity thermal, fluids, and structural codes whose coupling through SIERRA can be specifically tailored to the particular problem at hand to analyze complex multiphysics problems. Presently, however, the suite lacks several physics modules unique to the analysis of nuclear reactors. The NRC MELCOR code, not presently part of SIERRA, was developed to analyze severe accidents in present-technology reactor systems. We attempted to: (1) evaluate the SIERRA code suite for its current applicability to the analysis of next generation nuclear reactors, and the feasibility of implementing MELCOR models into the SIERRA suite, (2) examine the possibility of augmenting ASCI codes or alternatives by coupling to the MELCOR code, or portions thereof, to address physics particular to nuclear reactor issues, especially those facing next generation reactor designs, and (3) apply the coupled code set to a demonstration problem involving a nuclear reactor system. We were successful in completing the first two in sufficient detail to determine that an extensive demonstration problem was not feasible at this time. In the future, completion of this research would demonstrate the feasibility of performing high fidelity and rapid analyses of safety and design issues needed to support the development of next generation power reactor systems.

  14. Advances in clinical analysis 2012.

    PubMed

    Couchman, Lewis; Mills, Graham A

    2013-01-01

    A report on the meeting organized by The Chromatographic Society and the Separation Science Group, Analytical Division of the Royal Society of Chemistry. Over 60 delegates and commercial exhibitors attended this event, held to celebrate the careers of Robert Flanagan and David Perrett, and acknowledge their extensive contributions in the field of clinical analysis. PMID:23330556

  15. Spatial Pattern Analysis of Heavy Metals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics

    PubMed Central

    Huo, Xiao-Ni; Zhang, Wei-Wei; Sun, Dan-Feng; Li, Hong; Zhou, Lian-Di; Li, Bao-Guo

    2011-01-01

    This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different spatial weight matrixes, and they had significant and positive global spatial correlations based on distance weight. The spatial dependence of the four metals was scale-dependent on distance, but these scale effects existed within a threshold distance of 13 km, 32 km, 50 km, and 29 km, respectively for Cr, Ni, Zn, and Hg. The maximal spatial positive correlation range was 57 km, 70 km, 57 km, and 55 km for Cr, Ni, Zn, and Hg, respectively and these were not affected by sampling density. Local spatial autocorrelation analysis detected the locations of spatial clusters and spatial outliers and revealed that the pollution of these four metals occurred in significant High-high spatial clusters, Low-high, or even High-low spatial outliers. Thus, three major areas were identified and should be receiving more attention: the first was the northeast region of Beijing, where Cr, Zn, Ni, and Hg had significant increases. The second was the southeast region of Beijing where wastewater irrigation had strongly changed the content of metals, particularly of Cr and Zn, in soils. The third area was the urban fringe around city, where Hg showed a significant increase. PMID:21776217

  16. Robust geostatistical analysis of spatial data

    NASA Astrophysics Data System (ADS)

    Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

    2013-04-01

    Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R

  17. Spatial and temporal epidemiological analysis in the Big Data era.

    PubMed

    Pfeiffer, Dirk U; Stevens, Kim B

    2015-11-01

    Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle

  18. Spatial and temporal epidemiological analysis in the Big Data era.

    PubMed

    Pfeiffer, Dirk U; Stevens, Kim B

    2015-11-01

    Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle

  19. Advanced Placement: Model Policy Components. Policy Analysis

    ERIC Educational Resources Information Center

    Zinth, Jennifer

    2016-01-01

    Advanced Placement (AP), launched in 1955 by the College Board as a program to offer gifted high school students the opportunity to complete entry-level college coursework, has since expanded to encourage a broader array of students to tackle challenging content. This Education Commission of the State's Policy Analysis identifies key components of…

  20. High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

    PubMed

    Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

    2015-01-01

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

  1. Spatial Distribution Analysis of Scrub Typhus in Korea

    PubMed Central

    Jin, Hong Sung; Chu, Chaeshin; Han, Dong Yeob

    2013-01-01

    Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does not directly affect the incidence rate. Conclusion: GIS analysis shows the spatial characteristics of scrub typhus. This research can be used to construct a spatial-temporal model to understand the epidemic tsutsugamushi. PMID:24159523

  2. Advanced Interval Management: A Benefit Analysis

    NASA Technical Reports Server (NTRS)

    Timer, Sebastian; Peters, Mark

    2016-01-01

    This document is the final report for the NASA Langley Research Center (LaRC)- sponsored task order 'Possible Benefits for Advanced Interval Management Operations.' Under this research project, Architecture Technology Corporation performed an analysis to determine the maximum potential benefit to be gained if specific Advanced Interval Management (AIM) operations were implemented in the National Airspace System (NAS). The motivation for this research is to guide NASA decision-making on which Interval Management (IM) applications offer the most potential benefit and warrant further research.

  3. Statistical Software for spatial analysis of stratigraphic data sets

    2003-04-08

    Stratistics s a tool for statistical analysis of spatially explicit data sets and model output for description and for model-data comparisons. lt is intended for the analysis of data sets commonly used in geology, such as gamma ray logs and lithologic sequences, as well as 2-D data such as maps. Stratistics incorporates a far wider range of spatial analysis methods drawn from multiple disciplines, than are currently available in other packages. These include incorporation ofmore » techniques from spatial and landscape ecology, fractal analysis, and mathematical geology. Its use should substantially reduce the risk associated with the use of predictive models« less

  4. Analysis of a spatially deconvolved solar pore

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Shimizu, T.; Ruiz Cobo, B.; Suematsu, Y.; Katsukawa, Y.; Ichimoto, K.

    2016-08-01

    Solar pores are active regions with large magnetic field strengths and apparent simple magnetic configurations. Their properties resemble the ones found for the sunspot umbra although pores do not show penumbra. Therefore, solar pores present themselves as an intriguing phenomenon that is not completely understood. We examine in this work a solar pore observed with Hinode/SP using two state of the art techniques. The first one is the spatial deconvolution of the spectropolarimetric data that allows removing the stray light contamination induced by the spatial point spread function of the telescope. The second one is the inversion of the Stokes profiles assuming local thermodynamic equilibrium that let us to infer the atmospheric physical parameters. After applying these techniques, we found that the spatial deconvolution method does not introduce artefacts, even at the edges of the magnetic structure, where large horizontal gradients are detected on the atmospheric parameters. Moreover, we also describe the physical properties of the magnetic structure at different heights finding that, in the inner part of the solar pore, the temperature is lower than outside, the magnetic field strength is larger than 2 kG and unipolar, and the line-of-sight velocity is almost null. At neighbouring pixels, we found low magnetic field strengths of same polarity and strong downward motions that only occur at the low photosphere, below the continuum optical depth log τ = -1. Finally, we studied the spatial relation between different atmospheric parameters at different heights corroborating the physical properties described before.

  5. Experimental Analysis of Spatial Learning in Goldfish

    ERIC Educational Resources Information Center

    Saito, Kotaro; Watanabe, Shigeru

    2005-01-01

    The present study examined spatial learning in goldfish using a new apparatus that was an open-field circular pool with latticed holes. The subjects were motivated to reach the baited hole. We examined gustatory cues, intramaze cues, the possibility that the subject could see the food, etc. In Experiment 1, the position of the baited hole was…

  6. Application of adaptive optics in complicated and integrated spatial multisensor system and its measurement analysis

    NASA Astrophysics Data System (ADS)

    Ding, Quanxin; Guo, Chunjie; Cai, Meng; Liu, Hua

    2007-12-01

    Adaptive Optics Expand System is a kind of new concept spatial equipment, which concerns system, cybernetics and informatics deeply, and is key way to improve advanced sensors ability. Traditional Zernike Phase Contrast Method is developed, and Accelerated High-level Phase Contrast Theory is established. Integration theory and mathematical simulation is achieved. Such Equipment, which is based on some crucial components, such as, core optical system, multi mode wavefront sensor and so on, is established for AOES advantageous configuration and global design. Studies on Complicated Spatial Multisensor System Integratation and measurement Analysis including error analysis are carried out.

  7. Analysis of DOA estimation spatial resolution using MUSIC algorithm

    NASA Astrophysics Data System (ADS)

    Guo, Yue; Wang, Hongyuan; Luo, Bin

    2005-11-01

    This paper presents a performance analysis of the spatial resolution of the direction of arrival (DOA) estimates attained by the multiple signal classification (MUSIC) algorithm for uncorrelated sources. The confidence interval of estimation angle which is much more intuitionistic will be considered as the new evaluation standard for the spatial resolution. Then, based on the statistic method, the qualitative analysis reveals the factors influencing the performance of the MUSIC algorithm. At last, quantitative simulations prove the theoretical analysis result exactly.

  8. Spatial frequency analysis of multispectral data.

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.

    1972-01-01

    This paper presents the definitions of texture dependent features which can be obtained in terms of the spatial frequencies of small sections of remotely sensed multispectral data. The features are made independent of the direction of view by defining them as symmetric functions of the spatial frequencies sensed with various viewing directions. Several textural features are defined and experimental results indicating existence of signatures in these features are presented. Preliminary experiments have been performed on the classification of 60 samples, 10 from each of the following 6 categories - grass, trees, water, staked tomatoes, treated ground tomatoes, and untreated ground tomatoes. Classifications of the training samples using only one feature at a time indicate that several of the features yield classification efficiencies higher than 65%. The efficiency increases considerably when combinations of these features are used.

  9. Discrete analysis of spatial-sensitivity models

    NASA Technical Reports Server (NTRS)

    Nielsen, Kenneth R. K.; Wandell, Brian A.

    1988-01-01

    Procedures for reducing the computational burden of current models of spatial vision are described, the simplifications being consistent with the prediction of the complete model. A method for using pattern-sensitivity measurements to estimate the initial linear transformation is also proposed which is based on the assumption that detection performance is monotonic with the vector length of the sensor responses. It is shown how contrast-threshold data can be used to estimate the linear transformation needed to characterize threshold performance.

  10. Advanced Analysis Methods in High Energy Physics

    SciTech Connect

    Pushpalatha C. Bhat

    2001-10-03

    During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

  11. Advanced Fuel Cycle Economic Sensitivity Analysis

    SciTech Connect

    David Shropshire; Kent Williams; J.D. Smith; Brent Boore

    2006-12-01

    A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.

  12. APPLICATION OF SPATIAL INFORMATION TECHNOLOGY TO PETROLEUM RESOURCE ASSESSMENT ANALYSIS.

    USGS Publications Warehouse

    Miller, Betty M.; Domaratz, Michael A.

    1984-01-01

    Petroleum resource assessment procedures require the analysis of a large volume of spatial data. The US Geological Survey (USGS) has developed and applied spatial information handling procedures and digital cartographic techniques to a recent study involving the assessment of oil and gas resource potential for 74 million acres of designated and proposed wilderness lands in the western United States. The part of the study which dealt with the application of spatial information technology to petroleum resource assessment procedures is reviewed. A method was designed to expedite the gathering, integrating, managing, manipulating and plotting of spatial data from multiple data sources that are essential in modern resource assessment procedures.

  13. Eigenvector spatial filtering for image analysis: An efficient algorithm

    NASA Astrophysics Data System (ADS)

    Rura, Melissa J.

    Eigenvector Spatial Filtering (ESF) is an established method in social science literature for incorporating spatial information in model specifications. ESF computes spatial eigenvectors, which are defined by the spatial structure associated with a variable. One important limitation of this technique is that it becomes computationally intensive in image analysis because of the massive number of image pixels. This research develops an algorithm, which makes ESF more efficient, by using the analytical solution for the eigenvalues and spatial eigenvectors, which are essentially a series of orthogonal, uncorrelated map patterns that describe positively spatial autocorrelated patterns through negatively spatially autocorrelated patterns, and global, regional, and local patterns of spatial dependencies in a surface. A reformulation of the analytical solution reduces the required computations and allows the eigenvectors to be computed sequentially. Finally, a series of sampling methods are explored. This algorithm is applied to three example multispectral images of different sizes: small (i.e., ˜200,000 pixels), medium (i.e., ˜1,000,000 pixels) and large (i.e., ˜110,000,000 pixels) and is evaluated in terms of output for each sampling technique and the complete spectral information. The output spatial filters of these sampling techniques compare to the filter generated with the complete spectral information. In terms of efficiency evaluation, the time is required to construct filters through sampling versus through analysis of the complete image surface is evaluated and the complexity of set-up and execution of the sampled and distributed algorithms are assessed.

  14. Spatially Weighted Principal Component Analysis for Imaging Classification

    PubMed Central

    Guo, Ruixin; Ahn, Mihye; Zhu, Hongtu

    2014-01-01

    The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex spatial structure of imaging data. In SWPCA, we introduce two sets of novel weights including global and local spatial weights, which enable a selective treatment of individual features and incorporation of the spatial structure of imaging data and class label information. We develop an e cient two-stage iterative SWPCA algorithm and its penalized version along with the associated weight determination. We use both simulation studies and real data analysis to evaluate the finite-sample performance of our SWPCA. The results show that SWPCA outperforms several competing principal component analysis (PCA) methods, such as supervised PCA (SPCA), and other competing methods, such as sparse discriminant analysis (SDA). PMID:26089629

  15. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  16. Advanced Power Plant Development and Analysis Methodologies

    SciTech Connect

    A.D. Rao; G.S. Samuelsen; F.L. Robson; B. Washom; S.G. Berenyi

    2006-06-30

    Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into advanced power plant systems with goals of achieving high efficiency and minimized environmental impact while using fossil fuels. These power plant concepts include 'Zero Emission' power plants and the 'FutureGen' H2 co-production facilities. The study is broken down into three phases. Phase 1 of this study consisted of utilizing advanced technologies that are expected to be available in the 'Vision 21' time frame such as mega scale fuel cell based hybrids. Phase 2 includes current state-of-the-art technologies and those expected to be deployed in the nearer term such as advanced gas turbines and high temperature membranes for separating gas species and advanced gasifier concepts. Phase 3 includes identification of gas turbine based cycles and engine configurations suitable to coal-based gasification applications and the conceptualization of the balance of plant technology, heat integration, and the bottoming cycle for analysis in a future study. Also included in Phase 3 is the task of acquiring/providing turbo-machinery in order to gather turbo-charger performance data that may be used to verify simulation models as well as establishing system design constraints. The results of these various investigations will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

  17. Imaging spectroscopic analysis at the Advanced Light Source

    SciTech Connect

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-05-12

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications.

  18. Advanced Remote-Sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

    NASA Technical Reports Server (NTRS)

    Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred

    2006-01-01

    The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS Aqua Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and MODIS in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for MODIS.

  19. Local spatial frequency analysis for computer vision

    NASA Technical Reports Server (NTRS)

    Krumm, John; Shafer, Steven A.

    1990-01-01

    A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

  20. Analysis of spatially deconvolved polar faculae

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Suematsu, Y.; Ruiz Cobo, B.; Shimizu, T.; Asensio Ramos, A.

    2016-07-01

    Polar faculae are bright features that can be detected in solar limb observations and they are related to magnetic field concentrations. Although there are a large number of works studying them, some questions about their nature as their magnetic properties at different heights are still open. Thus, we aim to improve the understanding of solar polar faculae. In that sense, we infer the vertical stratification of the temperature, gas pressure, line-of-sight velocity and magnetic field vector of polar faculae regions. We performed inversions of the Stokes profiles observed with Hinode/Spectropolarimeter after removing the stray light contamination produced by the spatial point spread function of the telescope. Moreover, after solving the azimuth ambiguity, we transform the magnetic field vector to local solar coordinates. The obtained results reveal that the polar faculae are constituted by hot plasma with low line-of-sight velocities and single polarity magnetic fields in the kilogauss range that are nearly perpendicular to the solar surface. We also found that the spatial location of these magnetic fields is slightly shifted respect to the continuum observations towards the disc centre. We believe that this is due to the hot wall effect that allows detecting photons that come from deeper layers located closer to the solar limb.

  1. Forest fire spatial pattern analysis in Galicia (NW Spain).

    PubMed

    Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

    2013-10-15

    Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years.

  2. Using R to implement spatial analysis in open source environment

    NASA Astrophysics Data System (ADS)

    Shao, Yixi; Chen, Dong; Zhao, Bo

    2007-06-01

    R is an open source (GPL) language and environment for spatial analysis, statistical computing and graphics which provides a wide variety of statistical and graphical techniques, and is highly extensible. In the Open Source environment it plays an important role in doing spatial analysis. So, to implement spatial analysis in the Open Source environment which we called the Open Source geocomputation is using the R data analysis language integrated with GRASS GIS and MySQL or PostgreSQL. This paper explains the architecture of the Open Source GIS environment and emphasizes the role R plays in the aspect of spatial analysis. Furthermore, one apt illustration of the functions of R is given in this paper through the project of constructing CZPGIS (Cheng Zhou Population GIS) supported by Changzhou Government, China. In this project we use R to implement the geostatistics in the Open Source GIS environment to evaluate the spatial correlation of land price and estimate it by Kriging Interpolation. We also use R integrated with MapServer and php to show how R and other Open Source software cooperate with each other in WebGIS environment, which represents the advantages of using R to implement spatial analysis in Open Source GIS environment. And in the end, we points out that the packages for spatial analysis in R is still scattered and the limited memory is still a bottleneck when large sum of clients connect at the same time. Therefore further work is to group the extensive packages in order or design normative packages and make R cooperate better with other commercial software such as ArcIMS. Also we look forward to developing packages for land price evaluation.

  3. Spatially explicit spectral analysis of point clouds and geospatial data

    NASA Astrophysics Data System (ADS)

    Buscombe, Daniel

    2016-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described

  4. Spatially explicit spectral analysis of point clouds and geospatial data

    USGS Publications Warehouse

    Buscombe, Daniel D.

    2015-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is

  5. Integrated safety analysis based on spatial kinetics

    SciTech Connect

    Finnemann, H.; Drescher, G.

    1994-12-31

    The continuing progress in computer technology, characterized by the ever-increasing calculational speed of various computer architectures, enables the direct coupling of up to recently separate code systems. As a consequence different areas of analysis like reactor physics, core thermal hydraulics, and plant dynamics can be integrated to increase the accuracy of simulation over that obtained from imposing conservative boundary conditions at the interfaces. The coupling of thermal-hydraulic subchannel analysis with nodal space-time kinetics calculations is an important step toward an even more extensive integration of complex code systems. In this paper we present some results of a transient departure from nucleate boiling ratio (DNBR) calculation integrated in the nodal kinetics code PANBOX.

  6. Second-order spatial analysis of epidermal nerve fibers.

    PubMed

    Waller, Lance A; Särkkä, Aila; Olsbo, Viktor; Myllymäki, Mari; Panoutsopoulou, Ioanna G; Kennedy, William R; Wendelschafer-Crabb, Gwen

    2011-10-15

    Breakthroughs in imaging of skin tissue reveal new details on the distribution of nerve fibers in the epidermis. Preliminary neurologic studies indicate qualitative differences in the spatial patterns of nerve fibers based on pathophysiologic conditions in the subjects. Of particular interest is the evolution of spatial patterns observed in the progression of diabetic neuropathy. It appears that the spatial distribution of nerve fibers becomes more 'clustered' as neuropathy advances, suggesting the possibility of diagnostic prediction based on patterns observed in skin biopsies. We consider two approaches to establish statistical inference relating to this observation. First, we view the set of locations where the nerves enter the epidermis from the dermis as a realization of a spatial point process. Secondly, we treat the set of fibers as a realization of a planar fiber process. In both cases, we use estimated second-order properties of the observed data patterns to describe the degree and scale of clustering observed in the microscope images of blister biopsies. We illustrate the methods using confocal microscopy blister images taken from the thigh of one normal (disease-free) individual and two images each taken from the thighs of subjects with mild, moderate, and severe diabetes and report measurable differences in the spatial patterns of nerve entry points/fibers associated with disease status.

  7. Advancing Behavior Analysis in Zoos and Aquariums.

    PubMed

    Maple, Terry L; Segura, Valerie D

    2015-05-01

    Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers.

  8. Advancing Behavior Analysis in Zoos and Aquariums.

    PubMed

    Maple, Terry L; Segura, Valerie D

    2015-05-01

    Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers. PMID:27540508

  9. Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

    USGS Publications Warehouse

    Phillips, D.L.; Marks, D.G.

    1996-01-01

    In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated

  10. Spatial data analysis for exploration of regional scale geothermal resources

    NASA Astrophysics Data System (ADS)

    Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

    2013-10-01

    Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

  11. Spatial statistical analysis of tree deaths using airborne digital imagery

    NASA Astrophysics Data System (ADS)

    Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

    2013-04-01

    High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

  12. Advanced Technology Lifecycle Analysis System (ATLAS)

    NASA Technical Reports Server (NTRS)

    O'Neil, Daniel A.; Mankins, John C.

    2004-01-01

    Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is

  13. Fiber-Based, Spatially and Temporally Shaped Picosecond UV Laser for Advanced RF Gun Applications

    SciTech Connect

    Shverdin, M Y; Anderson, S G; Betts, S M; Gibson, D J; Hartemann, F V; Hernandez, J E; Johnson, M; Jovanovic, I; Messerly, M; Pruet, J; Tremaine, A M; McNabb, D P; Siders, C W; Barty, C J

    2007-06-08

    The fiber-based, spatially and temporally shaped, picosecond UV laser system described here has been specifically designed for advanced rf gun applications, with a special emphasis on the production of high-brightness electron beams for free-electron lasers and Compton scattering light sources. The laser pulse can be shaped to a flat-top in both space and time with a duration of 10 ps at full width of half-maximum (FWHM) and rise and fall times under 1 ps. The expected pulse energy is 50 {micro}J at 261.75 nm and the spot size diameter of the beam at the photocathode is 2 mm. A fiber oscillator and amplifier system generates a chirped pump pulse at 1047 nm; stretching is achieved in a chirped fiber Bragg grating. A single multi-layer dielectric grating based compressor recompresses the input pulse to 250 fs FWHM and a two stage harmonic converter frequency quadruples the beam. Temporal shaping is achieved with a Michelson-based ultrafast pulse stacking device with nearly 100% throughput. Spatial shaping is achieved by truncating the beam at the 20% energy level with an iris and relay-imaging the resulting beam profile onto the photocathode. The integration of the system, as well as preliminary laser measurements will be presented.

  14. Advanced techniques in current signature analysis

    SciTech Connect

    Smith, S.F.; Castleberry, K.N.

    1992-03-01

    In general, both ac and dc motors can be characterized as weakly nonlinear systems, in which both linear and nonlinear effects occur simultaneously. Fortunately, the nonlinearities are generally well behaved and understood and an be handled via several standard mathematical techniques already well developed in the systems modeling area; examples are piecewise linear approximations and Volterra series representations. Field measurements of numerous motors and motor-driven systems confirm the rather complex nature of motor current spectra and illustrate both linear and nonlinear effects (including line harmonics and modulation components). Although previous current signature analysis (CSA) work at Oak Ridge and other sites has principally focused on the modulation mechanisms and detection methods (AM, PM, and FM), more recent studies have been conducted on linear spectral components (those appearing in the electric current at their actual frequencies and not as modulation sidebands). For example, large axial-flow compressors ({approximately}3300 hp) in the US gaseous diffusion uranium enrichment plants exhibit running-speed ({approximately}20 Hz) and high-frequency vibrational information (>1 kHz) in their motor current spectra. Several signal-processing techniques developed to facilitate analysis of these components, including specialized filtering schemes, are presented. Finally, concepts for the designs of advanced digitally based CSA units are offered, which should serve to foster the development of much more computationally capable ``smart`` CSA instrumentation in the next several years. 3 refs.

  15. Variability of Soil Temperature: A Spatial and Temporal Analysis.

    ERIC Educational Resources Information Center

    Walsh, Stephen J.; And Others

    1991-01-01

    Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

  16. Visuo-Spatial Performance in Autism: A Meta-Analysis

    ERIC Educational Resources Information Center

    Muth, Anne; Hönekopp, Johannes; Falter, Christine M.

    2014-01-01

    Visuo-spatial skills are believed to be enhanced in autism spectrum disorders (ASDs). This meta-analysis tests the current state of evidence for Figure Disembedding, Block Design, Mental Rotation and Navon tasks in ASD and neurotypicals. Block Design (d = 0.32) and Figure Disembedding (d = 0.26) showed superior performance for ASD with large…

  17. Spatial regression analysis of traffic crashes in Seoul.

    PubMed

    Rhee, Kyoung-Ah; Kim, Joon-Ki; Lee, Young-ihn; Ulfarsson, Gudmundur F

    2016-06-01

    Traffic crashes can be spatially correlated events and the analysis of the distribution of traffic crash frequency requires evaluation of parameters that reflect spatial properties and correlation. Typically this spatial aspect of crash data is not used in everyday practice by planning agencies and this contributes to a gap between research and practice. A database of traffic crashes in Seoul, Korea, in 2010 was developed at the traffic analysis zone (TAZ) level with a number of GIS developed spatial variables. Practical spatial models using available software were estimated. The spatial error model was determined to be better than the spatial lag model and an ordinary least squares baseline regression. A geographically weighted regression model provided useful insights about localization of effects. The results found that an increased length of roads with speed limit below 30 km/h and a higher ratio of residents below age of 15 were correlated with lower traffic crash frequency, while a higher ratio of residents who moved to the TAZ, more vehicle-kilometers traveled, and a greater number of access points with speed limit difference between side roads and mainline above 30 km/h all increased the number of traffic crashes. This suggests, for example, that better control or design for merging lower speed roads with higher speed roads is important. A key result is that the length of bus-only center lanes had the largest effect on increasing traffic crashes. This is important as bus-only center lanes with bus stop islands have been increasingly used to improve transit times. Hence the potential negative safety impacts of such systems need to be studied further and mitigated through improved design of pedestrian access to center bus stop islands. PMID:26994374

  18. Geostatistical analysis of spatial and temporal variations of groundwater level.

    PubMed

    Ahmadi, Seyed Hamid; Sedghamiz, Abbas

    2007-06-01

    Groundwater and water resources management plays a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying management tools which can reveal the critical and hot conditions seems necessary due to some limitations such as labor and funding. In this study, spatial and temporal analysis of monthly groundwater level fluctuations of 39 piezometric wells monitored during 12 years was carried out. Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial and temporal structure of groundwater level fluctuation. Results showed that a strong spatial and temporal structure existed for groundwater level fluctuations due to very low nugget effects. Spatial analysis showed a strong structure of groundwater level drop across the study area and temporal analysis showed that groundwater level fluctuations have temporal structure. On average, the range of variograms for spatial and temporal analysis was about 9.7 km and 7.2 months, respectively. Ordinary and universal kriging methods with cross-validation were applied to assess the accuracy of the chosen variograms in estimation of the groundwater level drop and groundwater level fluctuations for spatial and temporal scales, respectively. Results of ordinary and universal krigings revealed that groundwater level drop and groundwater level fluctuations were underestimated by 3% and 6% for spatial and temporal analysis, respectively, which are very low and acceptable errors and support the unbiasedness hypothesis of kriging. Although, our results demonstrated that spatial structure was a little bit stronger than temporal structure, however, estimation of groundwater level drop and groundwater level fluctuations could be performed with low uncertainty in both space and time scales. Moreover, the results showed that kriging is a beneficial and capable tool for detecting those critical regions where need more attentions for

  19. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

    PubMed

    Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

  20. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

    NASA Astrophysics Data System (ADS)

    Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

  1. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

    PubMed

    Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. PMID:25863895

  2. Advanced Coal Wind Hybrid: Economic Analysis

    SciTech Connect

    Phadke, Amol; Goldman, Charles; Larson, Doug; Carr, Tom; Rath, Larry; Balash, Peter; Yih-Huei, Wan

    2008-11-28

    Growing concern over climate change is prompting new thinking about the technologies used to generate electricity. In the future, it is possible that new government policies on greenhouse gas emissions may favor electric generation technology options that release zero or low levels of carbon emissions. The Western U.S. has abundant wind and coal resources. In a world with carbon constraints, the future of coal for new electrical generation is likely to depend on the development and successful application of new clean coal technologies with near zero carbon emissions. This scoping study explores the economic and technical feasibility of combining wind farms with advanced coal generation facilities and operating them as a single generation complex in the Western US. The key questions examined are whether an advanced coal-wind hybrid (ACWH) facility provides sufficient advantages through improvements to the utilization of transmission lines and the capability to firm up variable wind generation for delivery to load centers to compete effectively with other supply-side alternatives in terms of project economics and emissions footprint. The study was conducted by an Analysis Team that consists of staff from the Lawrence Berkeley National Laboratory (LBNL), National Energy Technology Laboratory (NETL), National Renewable Energy Laboratory (NREL), and Western Interstate Energy Board (WIEB). We conducted a screening level analysis of the economic competitiveness and technical feasibility of ACWH generation options located in Wyoming that would supply electricity to load centers in California, Arizona or Nevada. Figure ES-1 is a simple stylized representation of the configuration of the ACWH options. The ACWH consists of a 3,000 MW coal gasification combined cycle power plant equipped with carbon capture and sequestration (G+CC+CCS plant), a fuel production or syngas storage facility, and a 1,500 MW wind plant. The ACWH project is connected to load centers by a 3,000 MW

  3. Multispectral laser imaging for advanced food analysis

    NASA Astrophysics Data System (ADS)

    Senni, L.; Burrascano, P.; Ricci, M.

    2016-07-01

    A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

  4. Hierarchical Spatial Analysis of Extreme Precipitation in Urban Areas

    NASA Astrophysics Data System (ADS)

    Rajulapati, C. R.; Mujumdar, P.

    2015-12-01

    Quantification of extreme precipitation is important for hydrologic designs. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult and extrapolating the distributions to locations where observations are not available is challenging. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 10 km. Therefore it is crucial to study the uncertainties in the spatial variation of precipitation in urban areas. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical spatial analysis and the spatial variation of return levels is studied. The analysis is carried out with both the Peak over Threshold (PoT) and the Block Maxima approaches for defining the extreme precipitation. The study area is Bangalore city, India. Daily data for seventeen stations in and around Bangalore city are considered in the study. The threshold exceedences are modeled using a Generalized Pareto (GP) distribution and the block maxima are modeled using Generalized Extreme Value (GEV) distribution. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the data (either block maxima or the threshold exceedences) at each station. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained. The results show that there is significant variation in

  5. Incorporating spatial context into the analysis of salmonid habitat relations

    USGS Publications Warehouse

    Torgersen, Christian E.; Baxter, Colden V.; Ebersole, J.L.; Gresswell, Bob; Church, Michael; Biron, Pascale M.; Roy, Andre G.

    2012-01-01

    In this response to the chapter by Lapointe (this volume), we discuss the question of why it is so difficult to predict salmonid-habitat relations in gravel-bed rivers and streams. We acknowledge that this cannot be an exhaustive treatment of the subject and, thus, identify what we believe are several key issues that demonstrate the necessity of incorporating spatial context into the analysis of fish-habitat data. Our emphasis is on spatial context (i.e., scale and location), but it is important to note that the same principles may be applied with some modification to temporal context, which is beyond the scope of this chapter.

  6. Cost analysis of gas distribution industry with spatial variables

    SciTech Connect

    Kim, Tai-Yoo; Lee, Jeong-Dong

    1995-12-31

    Cost assessment is important in the regulatory process, but it is not easy to effect, especially for distribution sector, because the spatial conditions as well as the output quantity play a major role in determining the cost. The hedonic cost function is introduced to incorporate the spatial characteristics (or network configurations) in the analysis of cost behavior of the Korean gas industry. The findings in this paper are that (1) almost all of the firms are exhausting their scale economies, (2) the average cost trend can be expressed as a surface of output quantity and spatial characteristics, and (3) the imaginary firm`s cost trend is derived by the regression approach. Industries that are related to electricity (water, railroad, and telecommunications, etc.) have the same cost property as the gas distribution industry, and the basic result and methodology in this paper would be applicable to these industries.

  7. Near ground level sensing for spatial analysis of vegetation

    NASA Technical Reports Server (NTRS)

    Sauer, Tom; Rasure, John; Gage, Charlie

    1991-01-01

    Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

  8. Spatial analysis of the Chania prefecture: Crete triangulation network quality

    NASA Astrophysics Data System (ADS)

    Achilleos, Georgios

    2016-08-01

    The network of trigonometric points of a region is the basis upon which any form of cartographic work is attached to the national geodetic coordinate system (data collection, processing, output presentations) and not only. The products of the cartographic work (cartographic representations), provide the background which is used in cases of spatial planning and development strategy. This trigonometric network, except that, provides to a single cartographic work, the ability to exist within a unified official state geodetic reference system, simultaneously determines the quality of the result, since the trigonometric network data that are used, have their own quality. In this paper, we present the research of spatial quality of the trigonometric network of Chania Prefecture in Crete. This analysis examines the triangulation network points, both with respect to their spatial position (distribution in space), and in their accuracy (horizontally and vertically).

  9. Analysis of the Spatial Organization of Molecules with Robust Statistics

    PubMed Central

    Lagache, Thibault; Lang, Gabriel; Sauvonnet, Nathalie; Olivo-Marin, Jean-Christophe

    2013-01-01

    One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules’ interactions and physical interplay with their environment. The standard tool for analyzing molecules’ distribution statistically is the Ripley’s K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles’ computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters’ size from the maxima of the Ripley’s K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of , which suggests distinct physical mechanisms and cellular functions for each pathway. PMID:24349021

  10. Socio-Spatial Intelligence: social media and spatial cognition for territorial behavioral analysis.

    PubMed

    Luini, Lorenzo P; Cardellicchio, Davide; Felletti, Fulvia; Marucci, Francesco S

    2015-09-01

    Investigative analysts gather data from different sources, especially from social media (SM), in order to shed light on cognitive factors that may explain criminal spatial behavior. A former research shows how tweets can be used to estimate private points of interest. Authors' aim was to demonstrate, as they extend the analysis to a wider statistical base, how social maps and Web applications could be used in investigative analysis and spatial cognition research. A total of 100 Twitter accounts with approximately 250 tweets each were submitted to common geographical techniques (measures such as Convex-Hull, Mean-Center, Median-Center, Standard-Deviation-Ellipse) in order to test the hypothesis that user areas of activity are predictable. Predictions were tested through a set of specific information: clear reference to areas of activity and clear reference about user's residence. Simple algorithms and procedures demonstrated that they could be used to predict where SM users live, giving positive results in about 4/5 cases and giving indications about their home location. In fact, all home positions were found in the Convex-Hull and most of them in the Standard-Deviation-Ellipse. Furthermore, in up to 80% of cases, houses were found within a buffer zone of 1.500 m with Median-Center as centrum (70% using Median-Center as centrum) with a minimum effectiveness threshold of 12-13 tweets. SM may help in studying people mobility and their cognition of space and, moreover, where they live, or their traveling behavior. The processing of geographical data in conjunction with the SM analysis may facilitate the construction of models describing specific behavior of people. The use of geographical information system tools and SM analysis represents an effective approach in order to acquire spatial and territorial information, referred to social relationship. The results may be used successfully in the understanding of social dynamics and for the prevention of criminal behavior.

  11. Analysis and System Design Framework for Infrared Spatial Heterodyne Spectrometers

    SciTech Connect

    Cooke, B.J.; Smith, B.W.; Laubscher, B.E.; Villeneuve, P.V.; Briles, S.D.

    1999-04-05

    The authors present a preliminary analysis and design framework developed for the evaluation and optimization of infrared, Imaging Spatial Heterodyne Spectrometer (SHS) electro-optic systems. Commensurate with conventional interferometric spectrometers, SHS modeling requires an integrated analysis environment for rigorous evaluation of system error propagation due to detection process, detection noise, system motion, retrieval algorithm and calibration algorithm. The analysis tools provide for optimization of critical system parameters and components including : (1) optical aperture, f-number, and spectral transmission, (2) SHS interferometer grating and Littrow parameters, and (3) image plane requirements as well as cold shield, optical filtering, and focal-plane dimensions, pixel dimensions and quantum efficiency, (4) SHS spatial and temporal sampling parameters, and (5) retrieval and calibration algorithm issues.

  12. Recent advances in the determination of a high spatial resolution geopotential model using chronometric geodesy

    NASA Astrophysics Data System (ADS)

    Lion, Guillaume; Guerlin, Christine; Bize, Sébastien; Wolf, Peter; Delva, Pacôme; Panet, Isabelle

    2016-04-01

    Current methods to determine the geopotential are mainly based on indirect approaches using gravimetric, gradiometric and topographic data. Satellite missions (GRACE, GOCE) have contributed significantly to improve the knowledge of the Earth's gravity field with a spatial resolution of about 90 km, but it is not enough to access, for example, to the geoid variation in hilly regions. While airborne and ground-based gravimeters provide the high resolution, the problem of these technics is that the accuracy is hampered by the heterogeneous coverage of gravity data (ground and offshore). Recent technological advances in atomic clocks are opening new perspectives in the determination of the geopotential. To date, the best of them reach a stability of 1.6×10-18 (NIST, RIKEN + Univ. Tokyo) in just 7 hours of integration, an accuracy of 2.0×10-18 (JILA). Using the relation of the relativistic gravitational redshift, this corresponds to a determination of geopotential differences at the 0.1 m²/s² level (or 1 cm in geoid height). In this context, the present work aims at evaluating the contribution of optical atomic clocks for the determination of the geopotential at high spatial resolution. To do that, we have studied a test area surrounding the Massif Central in the middle of southern of France. This region, consists in low mountain ranges and plateaus, is interesting because, the gravitational field strength varies greatly from place to place at high resolution due to the relief. Here, we present the synthetic tests methodology: generation of synthetic gravity and potential data, then estimation of the potential from these data using the least-squares collocation and assessment of the clocks contribution. We shall see how the coverage of the data points (realistic or not) can affect the results, and discuss how to quantify the trade-off between the noise level and the number of data points used.

  13. Spatial Analysis of Eco-environmental Risk Factors of Cutaneous Leishmaniasis in Southern Iran

    PubMed Central

    Ali-Akbarpour, Mohsen; Mohammadbeigi, Abolfazl; Tabatabaee, Seyed Hamid Reza; Hatam, Gholamreza

    2012-01-01

    Background: Despite the advances in the diagnosis and treatment of leishmaniasis, it is still considered as a severe public health problem particularly in developing countries and a great economic burden on the health resources. The present study was designed and conducted to determine the eco-environmental characteristics of the leishmaniasis disease by spatial analysis. Materials and Methods: In an ecological study, data were collected on eco-environmental factors of Fars province in Iran and on cutaneous leishmaniasis (CL) cases from 2002 to 2009. geographic weighted regression (GWR) was used to analyse the data and compare them with ordinary least square (OLS) regression model results. Moran's Index was applied for analysis of spatial autocorrelation in residual of OLS. P value less than 0.05 was considered as significant and adjusted R2 was used for model preferences. Results: There was a significant spatial autocorrelation in the residuals of OLS model (Z=2.45, P=0.014). GWR showed that rainy days, minimum temperature, wind velocity, maximum relative humidity and population density were the most important eco-environmental risk factors and explained 0.388 of the associated factors of CL. Conclusion: Spatial analysis can be a good tool for detection and prediction of CL disease. In autocorrelated and non-stationary data, GWR model yields a better fitness than OLS regression model. Also, population density can be used as a surrogate variable of acquired immunity and increase the adjusted R2. PMID:22557853

  14. Fourier mode analysis of source iteration in spatially periodic media

    SciTech Connect

    Zika, M.R.; Larsen, E.W.

    1998-12-31

    The standard Fourier mode analysis is an indispensable tool when designing acceleration techniques for transport iterations; however, it requires the assumption of a homogeneous infinite medium. For problems of practical interest, material heterogeneities may significantly impact iterative performance. Recent work has applied a Fourier analysis to the discretized two-dimensional transport operator with heterogeneous material properties. The results of these analyses may be difficult to interpret because the heterogeneity effects are inherently coupled to the discretization effects. Here, the authors describe a Fourier analysis of source iteration (SI) that allows the calculation of the eigenvalue spectrum for the one-dimensional continuous transport operator with spatially periodic heterogeneous media.

  15. Spatial risk assessment for critical network infrastructure using sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Möderl, Michael; Rauch, Wolfgang

    2011-12-01

    The presented spatial risk assessment method allows for managing critical network infrastructure in urban areas under abnormal and future conditions caused e.g., by terrorist attacks, infrastructure deterioration or climate change. For the spatial risk assessment, vulnerability maps for critical network infrastructure are merged with hazard maps for an interfering process. Vulnerability maps are generated using a spatial sensitivity analysis of network transport models to evaluate performance decrease under investigated thread scenarios. Thereby parameters are varied according to the specific impact of a particular threat scenario. Hazard maps are generated with a geographical information system using raster data of the same threat scenario derived from structured interviews and cluster analysis of events in the past. The application of the spatial risk assessment is exemplified by means of a case study for a water supply system, but the principal concept is applicable likewise to other critical network infrastructure. The aim of the approach is to help decision makers in choosing zones for preventive measures.

  16. Directional spatial frequency analysis of lipid distribution in atherosclerotic plaque

    NASA Astrophysics Data System (ADS)

    Korn, Clyde; Reese, Eric; Shi, Lingyan; Alfano, Robert; Russell, Stewart

    2016-04-01

    Atherosclerosis is characterized by the growth of fibrous plaques due to the retention of cholesterol and lipids within the artery wall, which can lead to vessel occlusion and cardiac events. One way to evaluate arterial disease is to quantify the amount of lipid present in these plaques, since a higher disease burden is characterized by a higher concentration of lipid. Although therapeutic stimulation of reverse cholesterol transport to reduce cholesterol deposits in plaque has not produced significant results, this may be due to current image analysis methods which use averaging techniques to calculate the total amount of lipid in the plaque without regard to spatial distribution, thereby discarding information that may have significance in marking response to therapy. Here we use Directional Fourier Spatial Frequency (DFSF) analysis to generate a characteristic spatial frequency spectrum for atherosclerotic plaques from C57 Black 6 mice both treated and untreated with a cholesterol scavenging nanoparticle. We then use the Cauchy product of these spectra to classify the images with a support vector machine (SVM). Our results indicate that treated plaque can be distinguished from untreated plaque using this method, where no difference is seen using the spatial averaging method. This work has the potential to increase the effectiveness of current in-vivo methods of plaque detection that also use averaging methods, such as laser speckle imaging and Raman spectroscopy.

  17. Advanced Materials and Solids Analysis Research Core (AMSARC)

    EPA Science Inventory

    The Advanced Materials and Solids Analysis Research Core (AMSARC), centered at the U.S. Environmental Protection Agency's (EPA) Andrew W. Breidenbach Environmental Research Center in Cincinnati, Ohio, is the foundation for the Agency's solids and surfaces analysis capabilities. ...

  18. Spatial Fourier analysis of video photobleaching measurements. Principles and optimization.

    PubMed Central

    Tsay, T T; Jacobson, K A

    1991-01-01

    The major use of the fluorescence recovery after photobleaching (FRAP) technique is to measure the translational motion of the molecular components in various condensed media. In a conventional laser spot photobleaching experiment, a photomultiplier is used to measure the total brightness levels of the bleached region in the sample, so no spatial information can be directly obtained. In video-FRAP, a series of images after photobleaching is acquired, allowing the spatial character of the recovery to be determined; this permits direct detection of both anisotropic diffusion and flow. To utilize all of the available image data to determine the transport coefficients, a two-dimensional spatial Fourier transform analysis of the images after photobleaching was employed. The change in the transform between two time points reflects the action of diffusion during the interim. An important advantage of this method, which involves taking the ratio of image transforms at different time points, is that it does not require a specific initial condition to be created by laser photobleaching. The ability of the analysis to extract transport coefficients from computer-simulated diffusional recovery is assessed in the presence of increasing amounts of noise. Experimental data analysis from the diffusion of proteins in viscous solutions and from the diffusion of protein receptors on cell surfaces demonstrate the feasibility of the Fourier analysis to obtain transport coefficients from the video FRAP measurement. Images FIGURE 3 PMID:1912279

  19. Mass Spectrometry Based Imaging Techniques for Spatially Resolved Analysis of Molecules

    PubMed Central

    Matros, Andrea; Mock, Hans-Peter

    2013-01-01

    Higher plants are composed of a multitude of tissues with specific functions, reflected by distinct profiles for transcripts, proteins, and metabolites. Comprehensive analysis of metabolites and proteins has advanced tremendously within recent years, and this progress has been driven by the rapid development of sophisticated mass spectrometric techniques. In most of the current “omics”-studies, analysis is performed on whole organ or whole plant extracts, rendering to the loss of spatial information. Mass spectrometry imaging (MSI) techniques have opened a new avenue to obtain information on the spatial distribution of metabolites and of proteins. Pioneered in the field of medicine, the approaches are now applied to study the spatial profiles of molecules in plant systems. A range of different plant organs and tissues have been successfully analyzed by MSI, and patterns of various classes of metabolites from primary and secondary metabolism could be obtained. It can be envisaged that MSI approaches will substantially contribute to build spatially resolved biochemical networks. PMID:23626593

  20. Multi-resolution analysis of high density spatial and temporal cloud inhomogeneity fields from HOPE campaign

    NASA Astrophysics Data System (ADS)

    Lakshmi Madhavan, Bomidi; Deneke, Hartwig; Macke, Andreas

    2015-04-01

    Clouds are the most complex structures in both spatial and temporal scales of the Earth's atmosphere that effect the downward surface reaching fluxes and thus contribute to large uncertainty in the global radiation budget. Within the framework of High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), a high density network of 99 pyranometer stations was set up around Jülich, Germany (~ 10 × 12 km2 area) during April to July 2013 to capture the small-scale variability in cloud induced radiation fields at the surface. In this study, we perform multi-resolution analysis of the downward solar irradiance variability at the surface from the pyranometer network to investigate the dependence of temporal and spatial averaging scales on the variance and spatial correlation for different cloud regimes. Preliminary results indicate that correlation is strongly scale-dependent where as the variance is dependent on the length of averaging period. Implications of our findings will be useful for quantifying the effect of spatial collocation while validating the satellite inferred solar irradiance estimates, and also to explore the link between cloud structure and radiation. We will present the details of our analysis and results.

  1. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-05-25

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  2. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-11-23

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  3. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    NASA Astrophysics Data System (ADS)

    Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

    2014-02-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

  4. Spatial analysis of ozone in Atlanta: Regulatory and epidemiologic implications

    SciTech Connect

    Butler, A.J.; Mulholland, J.A.; Wilkinson, J.G.; Russell, A.G.; Tolbert, P.E.

    1998-12-31

    Relationships between ambient levels of selected air pollutants and pediatric asthma exacerbation in Atlanta were studied retrospectively. As a part of this study, spatial distributions of ambient ozone concentrations in the twenty-county Atlanta metropolitan area during the summers of 1993, 1994 and 1995 were estimated and assessed. A universal kriging procedure was used for spatial interpolation of aerometric monitoring station data. In this paper, the spatial distributions of ozone are described, and regulatory and epidemiologic implications are discussed. For the study period, the Atlanta ozone nonattainment area based on the one-hour, exceedance-based standard of 0.12 ppm is estimated to expand from 56 percent of the Atlanta MSA by area and 71 percent by population to 88 percent by area and 96 percent by population under the new eight-hour, concentration-based standard of 0.08 ppm. Regarding asthma exacerbation, a 4 percent increase in pediatric asthma emergency room presentation rate per 20 ppb increase in ambient ozone concentration was observed (p-value = 0.001). Ambient ozone level represents a general indicator of air quality due to its correlation with other pollutants. The use of spatially-resolved ozone estimates in the epidemiologic analysis demonstrates the need to control confounding by demographic covariates.

  5. Spatial heterogeneity analysis of brain activation in fMRI

    PubMed Central

    Gupta, Lalit; Besseling, René M.H.; Overvliet, Geke M.; Hofman, Paul A.M.; de Louw, Anton; Vaessen, Maarten J.; Aldenkamp, Albert P.; Ulman, Shrutin; Jansen, Jacobus F.A.; Backes, Walter H.

    2014-01-01

    In many brain diseases it can be qualitatively observed that spatial patterns in blood oxygenation level dependent (BOLD) activation maps appear more (diffusively) distributed than in healthy controls. However, measures that can quantitatively characterize this spatial distributiveness in individual subjects are lacking. In this study, we propose a number of spatial heterogeneity measures to characterize brain activation maps. The proposed methods focus on different aspects of heterogeneity, including the shape (compactness), complexity in the distribution of activated regions (fractal dimension and co-occurrence matrix), and gappiness between activated regions (lacunarity). To this end, functional MRI derived activation maps of a language and a motor task were obtained in language impaired children with (Rolandic) epilepsy and compared to age-matched healthy controls. Group analysis of the activation maps revealed no significant differences between patients and controls for both tasks. However, for the language task the activation maps in patients appeared more heterogeneous than in controls. Lacunarity was the best measure to discriminate activation patterns of patients from controls (sensitivity 74%, specificity 70%) and illustrates the increased irregularity of gaps between activated regions in patients. The combination of heterogeneity measures and a support vector machine approach yielded further increase in sensitivity and specificity to 78% and 80%, respectively. This illustrates that activation distributions in impaired brains can be complex and more heterogeneous than in normal brains and cannot be captured fully by a single quantity. In conclusion, heterogeneity analysis has potential to robustly characterize the increased distributiveness of brain activation in individual patients. PMID:25161893

  6. Event Detection and Spatial Analysis for Characterizing Extreme Precipitation

    NASA Astrophysics Data System (ADS)

    Jeon, S.; Prabhat, M.; Byna, S.; Collins, W.; Wehner, M. F.

    2013-12-01

    Atmospheric Rivers (ARs) are large spatially coherent weather systems with high concentrations of elevated water vapor that often cause severe downpours and flooding over western coastal United States. With the availability of more atmospheric moisture in the future under global warming, we expect ARs to play an important role as a potential cause of extreme precipitation. We have recently developed TECA software for automatically identifying and tracking features in climate datasets. In particular, we are able to identify ARs that make landfall on the western coast of North America. This detection tool examines integrated water vapor field above a certain threshold and performs geometric analysis. Based on the detection procedure, we investigate impacts of ARs by exploring spatial extent of AR precipitation for CMIP5 simulations, and characterize spatial pattern of dependence for future projections under climate change within the framework of extreme value theory. The results show that AR events in RCP8.5 scenario (2076-2100) tend to produce heavier rainfall with higher frequency and longer duration than the events from historical run (1981-2005). Range of spatial dependence between extreme precipitations is concentrated on smaller localized area in California under the highest emission scenario than present day. Preliminary results are illustrated in Figure 1 and 2. Fig 1: Boxplot of annual max precipitation (left two) and max AR precipitation (right two) from GFDL-ESM2M during 25-year time period by station in California, US. Fig 2: Spatial dependence of max AR precipitation calculated from Station 4 (triangle) for historical run (left) and for future projections of RCP8.5 (right) from GFDL-ESM2M. Green and orange colors represent complete dependence and independence between two stations respectively.

  7. Fractal analysis of multiscale spatial autocorrelation among point data

    USGS Publications Warehouse

    De Cola, L.

    1991-01-01

    The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author

  8. An integrated spatial signature analysis and automatic defect classification system

    SciTech Connect

    Gleason, S.S.; Tobin, K.W.; Karnowski, T.P.

    1997-08-01

    An integrated Spatial Signature Analysis (SSA) and automatic defect classification (ADC) system for improved automatic semiconductor wafer manufacturing characterization is presented. Both concepts of SSA and ADC methodologies are reviewed and then the benefits of an integrated system are described, namely, focused ADC and signature-level sampling. Focused ADC involves the use of SSA information on a defect signature to reduce the number of possible classes that an ADC system must consider, thus improving the ADC system performance. Signature-level sampling improved the ADC system throughput and accuracy by intelligently sampling defects within a given spatial signature for subsequent off-line, high-resolution ADC. A complete example of wafermap characterization via an integrated SSA/ADC system is presented where a wafer with 3274 defects is completely characterized by revisiting only 25 defects on an off-line ADC review station. 13 refs., 7 figs.

  9. Spatial Durbin model analysis macroeconomic loss due to natural disasters

    NASA Astrophysics Data System (ADS)

    Kusrini, D. E.; Mukhtasor

    2015-03-01

    Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

  10. An information theory analysis of spatial decisions in cognitive development

    PubMed Central

    Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

  11. An information theory analysis of spatial decisions in cognitive development.

    PubMed

    Scott, Nicole M; Sera, Maria D; Georgopoulos, Apostolos P

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of "cognitive entropy" were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured "chunking" of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework.

  12. Advanced Spatial-Division Multiplexed Measurement Systems Propositions-From Telecommunication to Sensing Applications: A Review.

    PubMed

    Weng, Yi; Ip, Ezra; Pan, Zhongqi; Wang, Ting

    2016-01-01

    The concepts of spatial-division multiplexing (SDM) technology were first proposed in the telecommunications industry as an indispensable solution to reduce the cost-per-bit of optical fiber transmission. Recently, such spatial channels and modes have been applied in optical sensing applications where the returned echo is analyzed for the collection of essential environmental information. The key advantages of implementing SDM techniques in optical measurement systems include the multi-parameter discriminative capability and accuracy improvement. In this paper, to help readers without a telecommunication background better understand how the SDM-based sensing systems can be incorporated, the crucial components of SDM techniques, such as laser beam shaping, mode generation and conversion, multimode or multicore elements using special fibers and multiplexers are introduced, along with the recent developments in SDM amplifiers, opto-electronic sources and detection units of sensing systems. The examples of SDM-based sensing systems not only include Brillouin optical time-domain reflectometry or Brillouin optical time-domain analysis (BOTDR/BOTDA) using few-mode fibers (FMF) and the multicore fiber (MCF) based integrated fiber Bragg grating (FBG) sensors, but also involve the widely used components with their whole information used in the full multimode constructions, such as the whispering gallery modes for fiber profiling and chemical species measurements, the screw/twisted modes for examining water quality, as well as the optical beam shaping to improve cantilever deflection measurements. Besides, the various applications of SDM sensors, the cost efficiency issue, as well as how these complex mode multiplexing techniques might improve the standard fiber-optic sensor approaches using single-mode fibers (SMF) and photonic crystal fibers (PCF) have also been summarized. Finally, we conclude with a prospective outlook for the opportunities and challenges of SDM

  13. Advanced Spatial-Division Multiplexed Measurement Systems Propositions—From Telecommunication to Sensing Applications: A Review

    PubMed Central

    Weng, Yi; Ip, Ezra; Pan, Zhongqi; Wang, Ting

    2016-01-01

    The concepts of spatial-division multiplexing (SDM) technology were first proposed in the telecommunications industry as an indispensable solution to reduce the cost-per-bit of optical fiber transmission. Recently, such spatial channels and modes have been applied in optical sensing applications where the returned echo is analyzed for the collection of essential environmental information. The key advantages of implementing SDM techniques in optical measurement systems include the multi-parameter discriminative capability and accuracy improvement. In this paper, to help readers without a telecommunication background better understand how the SDM-based sensing systems can be incorporated, the crucial components of SDM techniques, such as laser beam shaping, mode generation and conversion, multimode or multicore elements using special fibers and multiplexers are introduced, along with the recent developments in SDM amplifiers, opto-electronic sources and detection units of sensing systems. The examples of SDM-based sensing systems not only include Brillouin optical time-domain reflectometry or Brillouin optical time-domain analysis (BOTDR/BOTDA) using few-mode fibers (FMF) and the multicore fiber (MCF) based integrated fiber Bragg grating (FBG) sensors, but also involve the widely used components with their whole information used in the full multimode constructions, such as the whispering gallery modes for fiber profiling and chemical species measurements, the screw/twisted modes for examining water quality, as well as the optical beam shaping to improve cantilever deflection measurements. Besides, the various applications of SDM sensors, the cost efficiency issue, as well as how these complex mode multiplexing techniques might improve the standard fiber-optic sensor approaches using single-mode fibers (SMF) and photonic crystal fibers (PCF) have also been summarized. Finally, we conclude with a prospective outlook for the opportunities and challenges of SDM

  14. Advanced Spatial-Division Multiplexed Measurement Systems Propositions-From Telecommunication to Sensing Applications: A Review.

    PubMed

    Weng, Yi; Ip, Ezra; Pan, Zhongqi; Wang, Ting

    2016-01-01

    The concepts of spatial-division multiplexing (SDM) technology were first proposed in the telecommunications industry as an indispensable solution to reduce the cost-per-bit of optical fiber transmission. Recently, such spatial channels and modes have been applied in optical sensing applications where the returned echo is analyzed for the collection of essential environmental information. The key advantages of implementing SDM techniques in optical measurement systems include the multi-parameter discriminative capability and accuracy improvement. In this paper, to help readers without a telecommunication background better understand how the SDM-based sensing systems can be incorporated, the crucial components of SDM techniques, such as laser beam shaping, mode generation and conversion, multimode or multicore elements using special fibers and multiplexers are introduced, along with the recent developments in SDM amplifiers, opto-electronic sources and detection units of sensing systems. The examples of SDM-based sensing systems not only include Brillouin optical time-domain reflectometry or Brillouin optical time-domain analysis (BOTDR/BOTDA) using few-mode fibers (FMF) and the multicore fiber (MCF) based integrated fiber Bragg grating (FBG) sensors, but also involve the widely used components with their whole information used in the full multimode constructions, such as the whispering gallery modes for fiber profiling and chemical species measurements, the screw/twisted modes for examining water quality, as well as the optical beam shaping to improve cantilever deflection measurements. Besides, the various applications of SDM sensors, the cost efficiency issue, as well as how these complex mode multiplexing techniques might improve the standard fiber-optic sensor approaches using single-mode fibers (SMF) and photonic crystal fibers (PCF) have also been summarized. Finally, we conclude with a prospective outlook for the opportunities and challenges of SDM

  15. The Tuition Advance Fund: An Analysis Prepared for Boston University.

    ERIC Educational Resources Information Center

    Botsford, Keith

    Three models for anlayzing the Tuition Advance Fund (TAF) are examined. The three models are: projections by the Institute for Demographic and Economic Studies (IDES), projections by Data Resources, Inc. (DRI), and the Tuition Advance Fund Simulation (TAFSIM) models from Boston University. Analysis of the TAF is based on enrollment, price, and…

  16. Advanced Fingerprint Analysis Project Fingerprint Constituents

    SciTech Connect

    GM Mong; CE Petersen; TRW Clauss

    1999-10-29

    The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.

  17. Spatial frequency analysis of anisotropic drug transport in tumor samples

    PubMed Central

    Russell, Stewart; Samkoe, Kimberley S.; Gunn, Jason R.; Hoopes, P. Jack; Nguyen, Thienan A.; Russell, Milo J.; Alfano, Robert R.; Pogue, Brian W.

    2014-01-01

    Abstract. Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the movement of drugs and nanoparticles into the parenchyma, thereby identifying the characteristic spatial frequencies of regions that inhibit drug transport. The innovative computational methodology and tissue validation techniques presented here provide a tool for future investigation of drug and particle transport in tumor tissues, and could potentially be used a priori to identify barriers to transport, and to analyze real-time monitoring of transport with respect to therapeutic intervention. PMID:24395585

  18. Advanced nuclear rocket engine mission analysis

    SciTech Connect

    Ramsthaler, J.; Farbman, G.; Sulmeisters, T.; Buden, D.; Harris, P.

    1987-12-01

    The use of a derivative of the NERVA engine developed from 1955 to 1973 was evluated for potential application to Air Force orbital transfer and maneuvering missions in the time period 1995 to 2020. The NERVA stge was found to have lower life cycle costs (LCC) than an advanced chemical stage for performing low earth orbit (LEO) to geosynchronous orbit (GEO0 missions at any level of activity greater than three missions per year. It had lower life cycle costs than a high performance nuclear electric engine at any level of LEO to GEO mission activity. An examination of all unmanned orbital transfer and maneuvering missions from the Space Transportation Architecture study (STAS 111-3) indicated a LCC advantage for the NERVA stage over the advanced chemical stage of fifteen million dollars. The cost advanced accured from both the orbital transfer and maneuvering missions. Parametric analyses showed that the specific impulse of the NERVA stage and the cost of delivering material to low earth orbit were the most significant factors in the LCC advantage over the chemical stage. Lower development costs and a higher thrust gave the NERVA engine an LCC advantage over the nuclear electric stage. An examination of technical data from the Rover/NERVA program indicated that development of the NERVA stage has a low technical risk, and the potential for high reliability and safe operation. The data indicated the NERVA engine had a great flexibility which would permit a single stage to perform all Air Force missions.

  19. Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review

    NASA Technical Reports Server (NTRS)

    Antonsson, Erik; Gombosi, Tamas

    2005-01-01

    Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.

  20. Use of artificial neural network for spatial rainfall analysis

    NASA Astrophysics Data System (ADS)

    Paraskevas, Tsangaratos; Dimitrios, Rozos; Andreas, Benardos

    2014-04-01

    In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.

  1. Reducing spatial uncertainty in climatic maps through geostatistical analysis

    NASA Astrophysics Data System (ADS)

    Pesquer, Lluís; Ninyerola, Miquel; Pons, Xavier

    2014-05-01

    Climatic maps from meteorological stations and geographical co-variables can be obtained through correlative models (Ninyerola et al., 2000)*. Nevertheless, the spatial uncertainty of the resulting maps could be reduced. The present work is a new stage over those approaches aiming to study how to obtain better results while characterizing spatial uncertainty. The study area is Catalonia (32000 km2), a region with highly variable relief (0 to 3143 m). We have used 217 stations (321 to 1244 mm) to model the annual precipitation in two steps: 1/ multiple regression using geographical variables (elevation, distance to the coast, latitude, etc) and 2/ refinement of the results by adding the spatial interpolation of the regression residuals with inverse distance weighting (IDW), regularized splines with tension (SPT) or ordinary kriging (OK). Spatial uncertainty analysis is based on an independent subsample (test set), randomly selected in previous works. The main contribution of this work is the analysis of this test set as well as the search for an optimal process of division (split) of the stations in two sets, one used to perform the multiple regression and residuals interpolation (fit set), and another used to compute the quality (test set); optimal division should reduce spatial uncertainty and improve the overall quality. Two methods have been evaluated against classical methods: (random selection RS and leave-one-out cross-validation LOOCV): selection by Euclidian 2D-distance, and selection by anisotropic 2D-distance combined with a 3D-contribution (suitable weighted) from the most representative independent variable. Both methods define a minimum threshold distance, obtained by variogram analysis, between samples. Main preliminary results for LOOCV, RS (average from 10 executions), Euclidian criterion (EU), and for anisotropic criterion (with 1.1 value, UTMY coordinate has a bit more weight than UTMX) combined with 3D criteria (A3D) (1000 factor for elevation

  2. Drought analysis in Switzerland: spatial and temporal features

    NASA Astrophysics Data System (ADS)

    Di Franca, Gaetano; Molnar, Peter; Burlando, Paolo; Bonaccorso, Brunella; Cancelliere, Antonino

    2015-04-01

    Drought as a natural hazard may have negative impacts even in regions characterized by a general abundance of water resources. The Swiss Alpine region has experienced several extreme meteorological events (heat waves, droughts) during the last fifty years that have caused human and economic losses. Though Swiss climate is far from arid or semi-arid, natural climatic variability, exacerbated by climate change, could lead to more severe impacts from naturally occurring meteorological droughts (i.e. lack or significant reduction of precipitation) in the future. In this work, spatial and temporal features of meteorological droughts in Switzerland have been explored by the identification and probabilistic characterization of historic drought events on gridded precipitation data during the period 1961-2012. The run method has been applied to both monthly and annual precipitation time series to probabilistically characterize drought occurrences as well as to analyze their spatial variability. Spatial features have also been investigated by means of Principal Components Analysis (PCA) applied to Standardized Precipitation Index (SPI) series at 3, 6, and 12-month aggregated time scale, in order to detect areas with distinct precipitation patterns, accounting for seasonality throughout year and including both wet and dry conditions. Furthermore, a probabilistic analysis of drought areal extent has been carried out by applying an SPI-based procedure to derive Severity-Area-Frequency (SAF) curves. The application of run method reveals that Ticino and Valais are the most potentially drought-prone Swiss regions, since accumulated deficit precipitation is significantly higher (up to two times) than in the rest of the country. Inspection of SPI series reveals many events in which precipitation has shown significant anomalies from the average in the period 1961-2012 at the investigated time scales. Anomalies in rainfall seem to exhibit high spatial correlation, showing uniform sub

  3. Spatial segregation between populations of ponto-cerebellar neurons: statistical analysis of multivariate spatial interactions.

    PubMed

    Bjaalie, J G; Diggle, P J; Nikundiwe, A; Karagülle, T; Brodal, P

    1991-12-01

    This study applies terms and methods for describing spatial interactions between multivariate spatial point patterns, which are, to our knowledge, new in neurobiology. We consider two categories of points, type 1 and 2, distributed within a certain reference volume (such as a nucleus of the brainstem or a cortical area). The points may, for example, represent different categories of labelled cells or axonal fields of termination. We say that there is spatial neutrality between points of type 1 and 2 if the types are signed by random labelling. If a mechanism drives the two point categories together, we say that the point patterns are positively associated. Conversely, if a mechanism drives type 1 and 2 points apart, we say that they are segregated. By comparing two cumulative distribution functions of distances between points, we can distinguish neutrality, positive association, and segregation. One function, H12(t), is the cumulative distribution function of the distance t between a pair of randomly selected points of type 1 and 2. The other, H00(t), is the corresponding function for a pair of points randomly selected without reference to type. Plots of the estimated difference between these two functions give an indication of positive association, neutrality, or segregation. A statistical test, based on simulations of random (neutral) distributions, can be used to see whether deviations from neutrality are significant. We apply the analysis described above to a major pathway of the brain, namely the ponto-cerebellar projection. Different types of cells in the pontine nuclei are retrogradely labelled with the fluorescent tracers Rhodamine-B-isothiocyanate, Fluoro-Gold, and Fast Blue. The tracers are injected in adjacent or more distant folia of the cerebellar paraflocculus. The location of the somata of labelled cells are recorded and the total distribution reconstructed in three dimensions and displayed on a dynamic graphics workstation. We ask whether different

  4. Advanced tracking systems design and analysis

    NASA Technical Reports Server (NTRS)

    Potash, R.; Floyd, L.; Jacobsen, A.; Cunningham, K.; Kapoor, A.; Kwadrat, C.; Radel, J.; Mccarthy, J.

    1989-01-01

    The results of an assessment of several types of high-accuracy tracking systems proposed to track the spacecraft in the National Aeronautics and Space Administration (NASA) Advanced Tracking and Data Relay Satellite System (ATDRSS) are summarized. Tracking systems based on the use of interferometry and ranging are investigated. For each system, the top-level system design and operations concept are provided. A comparative system assessment is presented in terms of orbit determination performance, ATDRSS impacts, life-cycle cost, and technological risk.

  5. Advanced surface design for logistics analysis

    NASA Astrophysics Data System (ADS)

    Brown, Tim R.; Hansen, Scott D.

    The development of anthropometric arm/hand and tool models and their manipulation in a large system model for maintenance simulation are discussed. The use of Advanced Surface Design and s-fig technology in anthropometrics, and three-dimensional graphics simulation tools, are found to achieve a good balance between model manipulation speed and model accuracy. The present second generation models are shown to be twice as fast to manipulate as the first generation b-surf models, to be easier to manipulate into various configurations, and to more closely approximate human contours.

  6. iGlobe Interactive Visualization and Analysis of Spatial Data

    NASA Technical Reports Server (NTRS)

    Hogan, Patrick

    2012-01-01

    iGlobe is open-source software built on NASA World Wind virtual globe technology. iGlobe provides a growing set of tools for weather science, climate research, and agricultural analysis. Up until now, these types of sophisticated tools have been developed in isolation by national agencies, academic institutions, and research organizations. By providing an open-source solution to analyze and visualize weather, climate, and agricultural data, the scientific and research communities can more readily advance solutions needed to understand better the dynamics of our home planet, Earth

  7. Spatially resolved organic analysis of the allende meteorite.

    PubMed

    Zenobi, R; Philippoz, J M; Zare, R N; Buseck, P R

    1989-11-24

    The distribution of polycyclic aromatic hydrocarbons(PAHs) in the Allende meteorite has been probed with two-step laser desorption/laser multiphoton ionization mass spectrometry. This method allows direct in situ analysis with a spatial resolution of 1 square millimeter or better of selected organic molecules. Spectra from freshly fractured interior surfaces of the meteorite show that PAH concentrations are locally high compared to the average concentrations found by wet chemical analysis of pulverized samples. The data suggest that the PAHs are primarily associated with the fine-grained matrix, where the organic polymer occurs. In addition, highly substituted PAH skeletons were observed. Interiors of individual chondrules were devoid of PAHs at our detection limit(about 0.05 parts per million).

  8. Recovering prehistoric woodworking skills using spatial analysis techniques

    NASA Astrophysics Data System (ADS)

    Kovács, K.; Hanke, K.

    2015-08-01

    Recovering of ancient woodworking skills can be achieved by the simultaneous documentation and analysis of the tangible evidences such as the geometry parameters of prehistoric hand tools or the fine morphological characteristics of well preserved wooden archaeological finds. During this study, altogether 10 different hand tool forms and over 60 hand tool impressions were investigated for the better understanding of the Bronze Age woodworking efficiency. Two archaeological experiments were also designed in this methodology and unknown prehistoric adzes could be reconstructed by the results of these studies and by the spatial analysis of the Bronze Age tool marks. Finally, the trimming efficiency of these objects were also implied and these woodworking skills could be quantified in the case of a Bronze Age wooden construction from Austria. The proposed GIS-based tool mark segmentation and comparison can offer an objective, user-independent technique for the related intangible heritage interpretations in the future.

  9. Spatially resolved organic analysis of the Allende meteorite

    NASA Technical Reports Server (NTRS)

    Zenobi, Renato; Philippoz, Jean-Michel; Zare, Richard N.; Buseck, Peter R.

    1989-01-01

    The distribution of polycyclic aromatic hydrocarbons (PAHs) in the Allende meteorite has been probed with two-step laser desorption/laser multiphoton ionization mass spectrometry. This method allows direct in situ analysis with a spatial resolution of 1 sq mm or better of selected organic molecules. Spectra from freshly fractured interior surfaces of the meteorite show that PAH concentrations are locally high compared to the average concentrations found by wet chemical analysis of pulverized samples. The data suggest that the PAHs are primarily associated with the fine-grained matrix, where the organic polymer occurs. In addition, highly substituted PAH skeletons were observed. Interiors of individual chondrules were devoid of PAHs at the detection limit (about 0.05 ppm).

  10. Characterization of porous surfaces with spatial point pattern analysis

    NASA Astrophysics Data System (ADS)

    Zou, Yibo; Kästner, Markus; Reithmeier, Eduard

    2015-01-01

    Nowadays thermal plasma spray coating is widespread in automobile industry. For example, in the cylinder manufacturing process coatings are applied for friction reduction, wear and corrosion resistance. After the honing process, a coated surface exhibits porous microstructures, which are often characterized in order to understand functional correlations between key parameters of the pores and friction performance. In this paper, spatial point pattern analysis is used to investigate the pores' distribution in a two dimensional space. Methods, such as nearest neighbor analysis and Ripley's K-function, are used to conduct the experiments to analyze the observer's pattern. Different edge correction methods in Ripley's K-function are introduced. Confidence envelopes are simulated using the Monte Carlo method. Experimental results are presented to reveal the patterns of pores, where influences of the selected measurement area on the results are taken into account and further discussed.

  11. Spatially explicit analysis of gastropod biodiversity in ancient Lake Ohrid

    NASA Astrophysics Data System (ADS)

    Hauffe, T.; Albrecht, C.; Schreiber, K.; Birkhofer, K.; Trajanovski, S.; Wilke, T.

    2011-01-01

    The quality of spatial analyses of biodiversity is improved by (i) utilizing study areas with well defined physiogeographical boundaries, (ii) limiting the impact of widespread species, and (iii) using taxa with heterogeneous distributions. These conditions are typically met by ecosystems such as oceanic islands or ancient lakes and their biota. While research on ancient lakes has contributed significantly to our understanding of evolutionary processes, statistically sound studies of spatial variation of extant biodiversity have been hampered by the frequently vast size of ancient lakes, their limited accessibility, and the lack of scientific infrastructure. The European ancient Lake Ohrid provides a rare opportunity for such a reliable spatial study. The comprehensive horizontal and vertical sampling of a species-rich taxon, the Gastropoda, presented here, revealed interesting patterns of biodiversity, which, in part, have not been shown before for other ancient lakes. In a total of 284 samples from 224 different locations throughout the Ohrid Basin, 68 gastropod species, with 50 of them (= 73.5%) being endemic, could be reported. The spatial distribution of these species shows the following characteristics: (i) within Lake Ohrid, the most frequent species are endemic taxa with a wide depth range, (ii) widespread species (i.e. those occurring throughout the Balkans or beyond) are rare and mainly occur in the upper layer of the lake, (iii) while the total number of species decreases with water depth, the proportion of endemics increases, and (iv) the deeper layers of Lake Ohrid appear to have a higher spatial homogeneity of biodiversity. Moreover, gastropod communities of Lake Ohrid and its feeder springs are both distinct from each other and from the surrounding waters. The analysis also shows that community similarity of Lake Ohrid is mainly driven by niche processes (e.g. environmental factors), but also by neutral processes (e.g. dispersal limitation and

  12. Advanced Techniques for Assessment of Postural and Locomotor Ataxia, Spatial Orientation, and Gaze Stability

    NASA Technical Reports Server (NTRS)

    Wall, Conrad., III

    1999-01-01

    In addition to adapting to microgravity, major neurovestibular problems of space flight include postflight difficulties with standing, walking, turning corners, and other activities that require stable upright posture and gaze stability. These difficulties inhibit astronauts' ability to stand or escape from their vehicle during emergencies. The long-ter7n goal of the NSBRI is the development of countermeasures to ameliorate the effects of long duration space flight. These countermeasures must be tested with valid and reliable tools. This project aims to develop quantitative, parametric approaches for assessing gaze stability and spatial orientation during normal gait and when gait is perturbed. Two of this year's most important findings concern head fixation distance and ideal trajectory analysis. During a normal cycle of walking the head moves up and down linearly. A simultaneous angular pitching motion of the head keeps it aligned toward an imaginary point in space at a distance of about one meter in front of a subject and along the line of march. This distance is called the head fixation distance. Head fixation distance provides the fundamental framework necessary for understanding the functional significance of the vestibular reflexes that couple head motion to eye motion. This framework facilitates the intelligent design of counter-measures for the effects of exposure to microgravity upon the vestibular ocular reflexes. Ideal trajectory analysis is a simple candidate countermeasure based upon quantifying body sway during repeated up and down stair stepping. It provides one number that estimates the body sway deviation from an ideal sinusoidal body sway trajectory normalized on the subject's height. This concept has been developed with NSBRI funding in less than one year. These findings are explained in more detail below. Compared to assessments of the vestibuo-ocular reflex, analysis of vestibular effects on locomotor function is relatively less well developed

  13. Recent Advances in Anthocyanin Analysis and Characterization

    PubMed Central

    Welch, Cara R.; Wu, Qingli; Simon, James E.

    2009-01-01

    Anthocyanins are a class of polyphenols responsible for the orange, red, purple and blue colors of many fruits, vegetables, grains, flowers and other plants. Consumption of anthocyanins has been linked as protective agents against many chronic diseases and possesses strong antioxidant properties leading to a variety of health benefits. In this review, we examine the advances in the chemical profiling of natural anthocyanins in plant and biological matrices using various chromatographic separations (HPLC and CE) coupled with different detection systems (UV, MS and NMR). An overview of anthocyanin chemistry, prevalence in plants, biosynthesis and metabolism, bioactivities and health properties, sample preparation and phytochemical investigations are discussed while the major focus examines the comparative advantages and disadvantages of each analytical technique. PMID:19946465

  14. Progress toward accurate high spatial resolution actinide analysis by EPMA

    NASA Astrophysics Data System (ADS)

    Jercinovic, M. J.; Allaz, J. M.; Williams, M. L.

    2010-12-01

    High precision, high spatial resolution EPMA of actinides is a significant issue for geochronology, resource geochemistry, and studies involving the nuclear fuel cycle. Particular interest focuses on understanding of the behavior of Th and U in the growth and breakdown reactions relevant to actinide-bearing phases (monazite, zircon, thorite, allanite, etc.), and geochemical fractionation processes involving Th and U in fluid interactions. Unfortunately, the measurement of minor and trace concentrations of U in the presence of major concentrations of Th and/or REEs is particularly problematic, especially in complexly zoned phases with large compositional variation on the micro or nanoscale - spatial resolutions now accessible with modern instruments. Sub-micron, high precision compositional analysis of minor components is feasible in very high Z phases where scattering is limited at lower kV (15kV or less) and where the beam diameter can be kept below 400nm at high current (e.g. 200-500nA). High collection efficiency spectrometers and high performance electron optics in EPMA now allow the use of lower overvoltage through an exceptional range in beam current, facilitating higher spatial resolution quantitative analysis. The U LIII edge at 17.2 kV precludes L-series analysis at low kV (high spatial resolution), requiring careful measurements of the actinide M series. Also, U-La detection (wavelength = 0.9A) requires the use of LiF (220) or (420), not generally available on most instruments. Strong peak overlaps of Th on U make highly accurate interference correction mandatory, with problems compounded by the ThMIV and ThMV absorption edges affecting peak, background, and interference calibration measurements (especially the interference of the Th M line family on UMb). Complex REE bearing phases such as monazite, zircon, and allanite have particularly complex interference issues due to multiple peak and background overlaps from elements present in the activation

  15. Analysis of an advanced technology subsonic turbofan incorporating revolutionary materials

    NASA Technical Reports Server (NTRS)

    Knip, Gerald, Jr.

    1987-01-01

    Successful implementation of revolutionary composite materials in an advanced turbofan offers the possibility of further improvements in engine performance and thrust-to-weight ratio relative to current metallic materials. The present analysis determines the approximate engine cycle and configuration for an early 21st century subsonic turbofan incorporating all composite materials. The advanced engine is evaluated relative to a current technology baseline engine in terms of its potential fuel savings for an intercontinental quadjet having a design range of 5500 nmi and a payload of 500 passengers. The resultant near optimum, uncooled, two-spool, advanced engine has an overall pressure ratio of 87, a bypass ratio of 18, a geared fan, and a turbine rotor inlet temperature of 3085 R. Improvements result in a 33-percent fuel saving for the specified misssion. Various advanced composite materials are used throughout the engine. For example, advanced polymer composite materials are used for the fan and the low pressure compressor (LPC).

  16. Brazilian Road Traffic Fatalities: A Spatial and Environmental Analysis

    PubMed Central

    de Andrade, Luciano; Vissoci, João Ricardo Nickenig; Rodrigues, Clarissa Garcia; Finato, Karen; Carvalho, Elias; Pietrobon, Ricardo; de Souza, Eniuce Menezes; Nihei, Oscar Kenji; Lynch, Catherine; de Barros Carvalho, Maria Dalva

    2014-01-01

    Background Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. Methods and Findings Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. Conclusions By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies. PMID:24498051

  17. Use of Spatial Analysis to Support Environmental Health Research and Practice

    PubMed Central

    Miranda, Marie Lynn; Edwards, Sharon E.

    2014-01-01

    Recent advances in spatial statistics and geographic information systems provide innovative platforms for diagnosing environmental health problems and for developing interventions. This article discusses when and where spatial techniques can most effectively be deployed to address environmental health issues, especially as they relate to environmental justice concerns. PMID:21721500

  18. Using a spatially explicit analysis model to evaluate spatial variation of corn yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...

  19. Spatial analysis of the distribution of Lyme disease in Wisconsin.

    PubMed

    Kitron, U; Kazmierczak, J J

    1997-03-15

    Surveillance measures for human cases of Lyme disease in Wisconsin were compared and associated with tick distribution and vegetation coverage. During 1991-1994, 1,759 confirmed human cases of Lyme disease reported to the Wisconsin Division of Health were assigned a county of residence, but only 329 (19%) could be assigned with certainty a county of exposure. Distributions of cases by county of exposure and residence were often consistent from year to year. Tick distribution in 46 of 72 Wisconsin counties was mapped based on collections by researchers, statewide surveys of infested deer, and submissions from the public. Satellite data were used to calculate a normalized difference vegetation index (NDVI) for each county. A geographic information system (GIS) was used to map distributions of human Lyme disease cases, ticks, and degree of vegetation cover. Human case distribution by county of exposure was significantly correlated with tick distribution; both were positively correlated with high NDVI values in spring and fall, when wooded vegetation could be distinguished from agricultural crops in the satellite image. Statistical analysis of spatial patterns using a measure of spatial autocorrelation indicated that counties with most human cases and ticks were clustered in parts of western Wisconsin. A map delineating the counties with highest risk for Lyme disease transmission was generated based on numbers of exposed human cases and tick concentrations. PMID:9063347

  20. [Research of Identify Spatial Object Using Spectrum Analysis Technique].

    PubMed

    Song, Wei; Feng, Shi-qi; Shi, Jing; Xu, Rong; Wang, Gong-chang; Li, Bin-yu; Liu, Yu; Li, Shuang; Cao Rui; Cai, Hong-xing; Zhang, Xi-he; Tan, Yong

    2015-06-01

    The high precision scattering spectrum of spatial fragment with the minimum brightness of 4.2 and the resolution of 0.5 nm has been observed using spectrum detection technology on the ground. The obvious differences for different types of objects are obtained by the normalizing and discrete rate analysis of the spectral data. Each of normalized multi-frame scattering spectral line shape for rocket debris is identical. However, that is different for lapsed satellites. The discrete rate of the single frame spectrum of normalized space debris for rocket debris ranges from 0.978% to 3.067%, and the difference of oscillation and average value is small. The discrete rate for lapsed satellites ranges from 3.118 4% to 19.472 7%, and the difference of oscillation and average value relatively large. The reason is that the composition of rocket debris is single, while that of the lapsed satellites is complex. Therefore, the spectrum detection technology on the ground can be used to the classification of the spatial fragment.

  1. Evapotranspiration Controls Imposed by Soil Moisture: A Spatial Analysis across the United States

    NASA Astrophysics Data System (ADS)

    Rigden, A. J.; Tuttle, S. E.; Salvucci, G.

    2014-12-01

    We spatially analyze the control over evapotranspiration (ET) imposed by soil moisture across the United States using daily estimates of satellite-derived soil moisture and data-driven ET over a nine-year period (June 2002-June 2011) at 305 locations. The soil moisture data are developed using 0.25-degree resolution satellite observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), where the 9-year time series for each 0.25-degree pixel was selected from three potential algorithms (VUA-NASA, U. Montana, & NASA) based on the maximum mutual information between soil moisture and precipitation (Tuttle & Salvucci (2014), Remote Sens Environ, 114: 207-222). The ET data are developed independent of soil moisture using an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased ET rates, suggesting that land-atmosphere feedback processes minimize this variance (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from meteorological data measured at 305 common weather stations that are approximately uniformly distributed across the United States. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture. We fit evaporation efficiency curves across the United States at each of the 305 sites during the summertime (May-June-July-August-September). Spatial patterns are visualized by mapping optimal curve fitting coefficients across the Unites States. An analysis of efficiency curves and their spatial patterns will be presented.

  2. Modeling and analysis of advanced binary cycles

    SciTech Connect

    Gawlik, K.

    1997-12-31

    A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.

  3. Spatial Distribution Balance Analysis of Hospitals in Wuhan

    PubMed Central

    Yang, Nai; Chen, Shiyi; Hu, Weilu; Wu, Zhongheng; Chao, Yi

    2016-01-01

    The spatial distribution pattern of hospitals in Wuhan indicates a core in the central urban areas and a sparse distribution in the suburbs, particularly at the center of suburbs. This study aims to improve the gravity and Huff models to analyze healthcare accessibility and resources. Results indicate that healthcare accessibility in central urban areas is better than in the suburbs, where it increasingly worsens for the suburbs. A shortage of healthcare resources is observed in large-scale and high-class hospitals in central urban areas, whereas the resources of some hospitals in the suburbs are redundant. This study proposes the multi-criteria evaluation (MCE) analysis model for the location assessment in constructing new hospitals, which can effectively ameliorate healthcare accessibility in suburban areas. This study presents implications for the planning of urban healthcare facilities. PMID:27706069

  4. Distribution of Modelling Spatial Processes Using Geostatistical Analysis

    NASA Astrophysics Data System (ADS)

    Grynyshyna-Poliuga, Oksana; Stanislawska, Iwona; Swiatek, Anna

    The Geostatistical Analyst uses sample points taken at different locations in a landscape and creates (interpolates) a continuous surface. The Geostatistical Analyst provides two groups of interpolation techniques: deterministic and geostatistical. All methods rely on the similarity of nearby sample points to create the surface. Deterministic techniques use mathematical functions for interpolation. Geostatistics relies on both statistical and mathematical methods, which can be used to create surfaces and assess the uncertainty of the predictions. The first step in geostatistical analysis is variography: computing and modelling a semivariogram. A semivariogram is one of the significant functions to indicate spatial correlation in observations measured at sample locations. It is commonly represented as a graph that shows the variance in measure with distance between all pairs of sampled locations. Such a graph is helpful to build a mathematical model that describes the variability of the measure with location. Modeling of relationship among sample locations to indicate the variability of the measure with distance of separation is called semivariogram modelling. It is applied to applications involving estimating the value of a measure at a new location. Our work presents the analysis of the data following the steps as given below: identification of data set periods, constructing and modelling the empirical semivariogram for single location and using the Kriging mapping function as modelling of TEC maps in mid-latitude during disturbed and quiet days. Based on the semivariogram, weights for the kriging interpolation are estimated. Additional observations do, in general, not provide relevant extra information to the interpolation, because the spatial correlation is well described with the semivariogram. Keywords: Semivariogram, Kriging, modelling, Geostatistics, TEC

  5. Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

    NASA Astrophysics Data System (ADS)

    Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

    2011-11-01

    The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

  6. Spatial analysis and indicator building for metal accumulation in mosses.

    PubMed

    Schröder, Winfried; Pesch, Roland

    2004-11-01

    Mosses are used as passive accumulation monitors for metal accumulation in terrestrial ecosystems. Under leadership of the Federal Agency for Environmental Protection Germany took part in the previous European-wide moss monitoring campaigns 1990, 1995 and 2000. The investigations accomplished thereby cannot be presented completely in this article. The remarks rather concentrate on methodical aspects of the statistical data analysis. In Chapter 2 the design of data collection is summarized. Chapter 3 treats the geostatistical analysis and transformation of point data to areal information. Chapter 4 describes the aggregation of the element-specific metal concentrations in mosses to a spatially and temporally differentiated indicator of metal accumulation by means of descriptive and multivariate statistics. The work presented is only a small part of geostatistics and multivariate statistics which fit for analysis of moss monitoring data. Taking the results presented here as a basis, the following steps would further be of great importance: cluster-analytic evaluation of the results of the Moss Monitoring 1990 and 1995, detailing the cluster results using additional empirical and location describing information (e.g. moss species, ecoregions, site and species specific variability of metal accumulation) as well as optimizing the indicator buildung by testing of multivariate statistical regression models (e.g. Classification and Regression Trees). PMID:15473533

  7. Advancing Usability Evaluation through Human Reliability Analysis

    SciTech Connect

    Ronald L. Boring; David I. Gertman

    2005-07-01

    This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.

  8. Recent advances in statistical energy analysis

    NASA Technical Reports Server (NTRS)

    Heron, K. H.

    1992-01-01

    Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

  9. Progress in Advanced Spectral Analysis of Radioxenon

    SciTech Connect

    Haas, Derek A.; Schrom, Brian T.; Cooper, Matthew W.; Ely, James H.; Flory, Adam E.; Hayes, James C.; Heimbigner, Tom R.; McIntyre, Justin I.; Saunders, Danielle L.; Suckow, Thomas J.

    2010-09-21

    Improvements to a Java based software package developed at Pacific Northwest National Laboratory (PNNL) for display and analysis of radioxenon spectra acquired by the International Monitoring System (IMS) are described here. The current version of the Radioxenon JavaViewer implements the region of interest (ROI) method for analysis of beta-gamma coincidence data. Upgrades to the Radioxenon JavaViewer will include routines to analyze high-purity germanium detector (HPGe) data, Standard Spectrum Method to analyze beta-gamma coincidence data and calibration routines to characterize beta-gamma coincidence detectors. These upgrades are currently under development; the status and initial results will be presented. Implementation of these routines into the JavaViewer and subsequent release is planned for FY 2011-2012.

  10. Advanced CMOS Radiation Effects Testing Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, Jonathan Allen; Marshall, Paul W.; Rodbell, Kenneth P.; Gordon, Michael S.; LaBel, Kenneth A.; Schwank, James R.; Dodds, Nathaniel A.; Castaneda, Carlos M.; Berg, Melanie D.; Kim, Hak S.; Phan, Anthony M.; Seidleck, Christina M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  11. Advanced CMOS Radiation Effects Testing and Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, J. A.; Marshall, P. W.; Rodbell, K. P.; Gordon, M. S.; LaBel, K. A.; Schwank, J. R.; Dodds, N. A.; Castaneda, C. M.; Berg, M. D.; Kim, H. S.; Phan, A. M.; Seidleck, C. M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  12. Advanced Techniques for Root Cause Analysis

    2000-09-19

    Five items make up this package, or can be used individually. The Chronological Safety Management Template utilizes a linear adaptation of the Integrated Safety Management System laid out in the form of a template that greatly enhances the ability of the analyst to perform the first step of any investigation which is to gather all pertinent facts and identify causal factors. The Problem Analysis Tree is a simple three (3) level problem analysis tree whichmore » is easier for organizations outside of WSRC to use. Another part is the Systemic Root Cause Tree. One of the most basic and unique features of Expanded Root Cause Analysis is the Systemic Root Cause portion of the Expanded Root Cause Pyramid. The Systemic Root Causes are even more basic than the Programmatic Root Causes and represent Root Causes that cut across multiple (if not all) programs in an organization. the Systemic Root Cause portion contains 51 causes embedded at the bottom level of a three level Systemic Root Cause Tree that is divided into logical, organizationally based categorie to assist the analyst. The Computer Aided Root Cause Analysis that allows the analyst at each level of the Pyramid to a) obtain a brief description of the cause that is being considered, b) record a decision that the item is applicable, c) proceed to the next level of the Pyramid to see only those items at the next level of the tree that are relevant to the particular cause that has been chosen, and d) at the end of the process automatically print out a summary report of the incident, the causal factors as they relate to the safety management system, the probable causes, apparent causes, Programmatic Root Causes and Systemic Root Causes for each causal factor and the associated corrective action.« less

  13. Advanced automated char image analysis techniques

    SciTech Connect

    Tao Wu; Edward Lester; Michael Cloke

    2006-05-15

    Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300{sup o}C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 {mu}m). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles. 20 refs., 10 figs., 3 tabs.

  14. Spatial resolution measurements of the advanced radiographic capability x-ray imaging system at energies relevant to Compton radiography

    NASA Astrophysics Data System (ADS)

    Hall, G. N.; Izumi, N.; Landen, O. L.; Tommasini, R.; Holder, J. P.; Hargrove, D.; Bradley, D. K.; Lumbard, A.; Cruz, J. G.; Piston, K.; Lee, J. J.; Romano, E.; Bell, P. M.; Carpenter, A. C.; Palmer, N. E.; Felker, B.; Rekow, V.; Allen, F. V.

    2016-11-01

    Compton radiography provides a means to measure the integrity, ρR and symmetry of the DT fuel in an inertial confinement fusion implosion near peak compression. Upcoming experiments at the National Ignition Facility will use the ARC (Advanced Radiography Capability) laser to drive backlighter sources for Compton radiography experiments and will use the newly commissioned AXIS (ARC X-ray Imaging System) instrument as the detector. AXIS uses a dual-MCP (micro-channel plate) to provide gating and high DQE at the 40-200 keV x-ray range required for Compton radiography, but introduces many effects that contribute to the spatial resolution. Experiments were performed at energies relevant to Compton radiography to begin characterization of the spatial resolution of the AXIS diagnostic.

  15. Advanced Orion Optimized Laser System Analysis

    NASA Technical Reports Server (NTRS)

    1996-01-01

    Contractor shall perform a complete analysis of the potential of the solid state laser in the very long pulse mode (100 ns pulse width, 10-30 hz rep-rate) and in the very short pulse mode (100 ps pulse width 10-30 hz rep rate) concentrating on the operation of the device in the 'hot-rod' mode, where no active cooling the laser operation is attempted. Contractor's calculations shall be made of the phase aberrations which develop during the repped-pulse train, and the results shall feed into the adaptive optics analyses. The contractor shall devise solutions to work around ORION track issues. A final report shall be furnished to the MSFC COTR including all calculations and analysis of estimates of bulk phase and intensity aberration distribution in the laser output beam as a function of time during the repped-pulse train for both wave forms (high-energy/long-pulse, as well as low-energy/short-pulse). Recommendations shall be made for mitigating the aberrations by laser re-design and/or changes in operating parameters of optical pump sources and/or designs.

  16. Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

    DOEpatents

    Van Berkel, Gary J.

    2015-10-06

    A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

  17. Advanced Remote-sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

    NASA Technical Reports Server (NTRS)

    Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred G.; Broberg, Steve E.

    2006-01-01

    This paper describes a space based instrument concept that will provide scientists with data needed to support key ongoing and future Earth System Science investigations. The measurement approach builds on the observations made by AIRS and MODIS and exceeds their capability with improved spatial and spectral resolution. This paper describes the expected products and the instrument concept that can meet those requirements.

  18. Technology Advancements in the Next Generation of Domain Agnostic Spatial Data Infrastructures

    NASA Astrophysics Data System (ADS)

    Golodoniuc, Pavel; Rankine, Terry; Box, Paul; Atkinson, Rob; Kostanski, Laura

    2013-04-01

    Spatial Data Infrastructures (SDI) are typically composed of a suite of products focused on improving spatial information discovery and access. Proliferation of SDI initiatives has caused the "Yet Another Portal" (YAP) syndrome to emerge with each initiative providing a new mechanism for cataloguing and enabling users to search for spatial information resources. Often coarse-grained and incomplete metadata information available via these SDIs renders them to being analogous with an antiquated library catalogue. We posit that the successful use of SDI resources requires attention to be focused on various semantic aspects of the information contained within - particularly the information models and vocabularies. Currently it is common for understanding of these models and vocabularies to be built into portals. This does not enhance interoperability between SDIs, nor does this provide a means for referencing or searching for a specific feature (e.g., the City of Sydney) without first knowing the location of the information source for the feature and the form in which it is represented. SDI interfaces, such as OGC WFS, provide data from a spatial representation perspective, but do not provide identifiers that can easily be cited or used across system boundaries. The lack of mechanisms to provide stable identifiers of a feature renders it permanently scoped to a particular dataset. The other three important aspects that are commonly lacking in SDIs are the inadequate handling of feature level metadata that is commonly not sufficient enough for more than the most basic data discovery; features delivered through SDI are not well integrated with information systems that deliver statistical information about those features; and, importantly there are inadequate mechanisms to reconcile and associate multiple identities and representations of the same real world feature. In this paper we present an extended view of an SDI architecture with integrated support for information

  19. Advanced stability analysis for laminar flow control

    NASA Technical Reports Server (NTRS)

    Orszag, S. A.

    1981-01-01

    Five classes of problems are addressed: (1) the extension of the SALLY stability analysis code to the full eighth order compressible stability equations for three dimensional boundary layer; (2) a comparison of methods for prediction of transition using SALLY for incompressible flows; (3) a study of instability and transition in rotating disk flows in which the effects of Coriolis forces and streamline curvature are included; (4) a new linear three dimensional instability mechanism that predicts Reynolds numbers for transition to turbulence in planar shear flows in good agreement with experiment; and (5) a study of the stability of finite amplitude disturbances in axisymmetric pipe flow showing the stability of this flow to all nonlinear axisymmetric disturbances.

  20. Value analysis for advanced technology products

    NASA Astrophysics Data System (ADS)

    Soulliere, Mark

    2011-03-01

    Technology by itself can be wondrous, but buyers of technology factor in the price they have to pay along with performance in their decisions. As a result, the ``best'' technology may not always win in the marketplace when ``good enough'' can be had at a lower price. Technology vendors often set pricing by ``cost plus margin,'' or by competitors' offerings. What if the product is new (or has yet to be invented)? Value pricing is a methodology to price products based on the value generated (e.g. money saved) by using one product vs. the next best technical alternative. Value analysis can often clarify what product attributes generate the most value. It can also assist in identifying market forces outside of the control of the technology vendor that also influence pricing. These principles are illustrated with examples.

  1. Study of academic achievements using spatial analysis tools

    NASA Astrophysics Data System (ADS)

    González, C.; Velilla, C.; Sánchez-Girón, V.

    2012-04-01

    In the 2010/12 academic year the College of Agricultural Engineering of the Technical University of Madrid implemented three new degrees all of them adapted to the European Space for Higher Education. These degrees are namely: Graduate in Agricultural Engineering and Science, Graduate in Food Engineering and Graduate in Agro-Environmental Engineering. A total of 382 new incoming students were finally registered and a survey study was carried out with these students about their academic achievement with the aim of finding the level of dependence among the following variables: the final mark in their secondary studies, the option followed in the secondary studies (Art, Science and Technology, and Humanities and Social Sciences), the mark obtained in the entering examination to the university and in which of the two opportunities per year this examination takes place the latter mark was obtained. Similarly, another group of 77 students were evaluated independently to the former group. These students were those entering the College in the previous academic year (2009/10) and decided to change their curricula to the new ones. Subsequently, using the tools of spatial analysis of geographic information systems, we analyzed the possible relationship between the success or failure at school and the socioeconomic profile of new students in a grade. For this purpose every student was referenced assigning UTM coordinates to their postal addresses. Furthermore, all students' secondary schools were geographically coded considering their typology (public, private, and private subsidized) and fares. Each student was represented by its average geometric point in order to be correlated to their respective record. Following this procedure a map of the performance of each student could be drawn. This map can be used as a reference system, as it includes variables as the distance from the student home to the College, that can be used as a tool to calculate the probability of success or

  2. Spatial Analysis of Stomach Cancer Incidence in Iran.

    PubMed

    Pakzad, Reza; Khani, Yousef; Pakzad, Iraj; Momenimovahed, Zohre; Mohammadian-Hashejani, Abdollah; Salehiniya, Hamid; Towhidi, Farhad; Makhsosi, Behnam Reza

    2016-01-01

    Stomach cancer, the fourth most common cancer and the second leading cause of cancer-related death through the world, is very common in parts of Iran. Geographic variation in the incidence of stomach cancer is due to many different factors. The aim of this study was to assess the geographical and spatial distribution of stomach cancer in Iran using data from the cancer registry program in Iran for the year 2009. The reported incidences of stomach cancer for different provinces were standardized to the world population structure. ArcGIS software was used to analyse the data. Hot spots and high risk areas were determined using spatial analysis (Getis-Ord Gi). Hot and cold spots were determined as more than or less than 2 standard deviations from the national average, respectively. A significance level of 0.10 was used for statistical judgment. In 2009, a total of 6,886 cases of stomach cancers were reported of which 4,891 were in men and 1,995 in women (standardized incidence rates of 19.2 and 10.0, respectively, per 100,000 population). The results showed that stomach cancer was concentrated mainly in northwest of the country in both men and women. In women, northwest provinces such as Ardebil, East Azerbaijan, West Azerbaijan, Gilan, and Qazvin were identified as hot spots (p<0.1). In men, all northwest provinces, Ardabil, East Azerbaijan, Gilan, Qazvin, Zanjan and Kurdistan, the incidences were higher than the national average and these were identified as hot spots (P<0.01). As stomach cancer is clustered in the northwest of the country, further epidemiological studies are needed to identify factors contributing to this concentration.

  3. Spatial control of groundwater contamination, using principal component analysis

    NASA Astrophysics Data System (ADS)

    Rao, N. Subba

    2014-06-01

    A study on the geochemistry of groundwater was carried out in a river basin of Andhra Pradesh to probe into the spatial controlling processes of groundwater contamination, using principal component analysis (PCA). The PCA transforms the chemical variables, pH, EC, Ca2+, Mg2+, Na+, K+, HCO, Cl-, SO, NO and F-, into two orthogonal principal components (PC1 and PC2), accounting for 75% of the total variance of the data matrix. PC1 has high positive loadings of EC, Na+, Cl-, SO, Mg2+ and Ca2+, representing a salinity controlled process of geogenic (mineral dissolution, ion exchange, and evaporation), anthropogenic (agricultural activities and domestic wastewaters), and marine (marine clay) origin. The PC2 loadings are highly positive for HCO , F-, pH and NO, attributing to the alkalinity and pollution controlled processes of geogenic and anthropogenic origins. The PC scores reflect the change of groundwater quality of geogenic origin from upstream to downstream area with an increase in concentration of chemical variables, which is due to anthropogenic and marine origins with varying topography, soil type, depth of water levels, and water usage. Thus, the groundwater quality shows a variation of chemical facies from Na+ > Ca2+ > Mg2+ > K+: HCO > Cl- > SO NO > F-at high topography to Na+ > Mg2+ > Ca2+ > K+: Cl- > HCO > SO NO > F- at low topography. With PCA, an effective tool for the spatial controlling processes of groundwater contamination, a subset of explored wells is indexed for continuous monitoring to optimize the expensive effort.

  4. Temporal and spatial analysis of solar signatures in cloud cover

    NASA Astrophysics Data System (ADS)

    Voiculescu, M.; Usoskin, I.

    2012-12-01

    The persistence of solar signals in cloud cover is analyzed for the time interval, 1984 - 2009, covering two full solar cycles, 22 and 23. A spatial and temporal investigation of the response of low, middle and high cloud data to cosmic ray induced ionization (CRII) and UV irradiance (UVI) is performed in terms of coherence analysis of the two signals for various regions of the globe where correlation is observed between clouds and solar proxies. For some key geographical regions the response of clouds to UVI and CRII is persistent over the entire time interval, which indicates a real link. In other regions the relation is not consistent, being intermittent or out of phase, suggesting that some correlations are not real. However, constant in-phase or anti-phase relationship between clouds and solar proxies for some regions are observed. Low cloud cover correlates to both UVI and CRII, middle clouds seem to be related to UVI while high clouds respond to CRII. Correlation and coherence analysis cannot give definitive answers to questions related to solar effects on clouds but could, nonetheless, pinpoint some possible solar effects on climate and could suggests directions for future research.

  5. Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina.

    PubMed

    Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

    2015-01-01

    OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

  6. Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina

    PubMed Central

    Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

    2015-01-01

    OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

  7. Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina.

    PubMed

    Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

    2015-01-01

    OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.

  8. Bistatic radar configuration for soil moisture retrieval: analysis of the spatial coverage.

    PubMed

    Pierdicca, Nazzareno; De Titta, Ludovico; Pulvirenti, Luca; Della Pietra, Giuliano

    2009-01-01

    Some outcomes of a feasibility analysis of a spaceborne bistatic radar mission for soil moisture retrieval are presented in this paper. The study starts from the orbital design of the configuration suitable for soil moisture estimation identified in a previous study. This configuration is refined according to the results of an analysis of the spatial resolution. The paper focuses on the assessment of the spatial coverage i.e., on the verification that an adequate overlap between the footprints of the antennas is ensured and on the duty cycle, that is the fraction of orbital period during which the bistatic data are acquired. A non-cooperating system is considered, in which the transmitter is the C-band Advanced Synthetic Aperture Radar aboard Envisat. The best performances in terms of duty cycle are achieved if the transmitter operates in Wide Swath Mode. The higher resolution Image Swath Modes that comply with the selected configuration have a duty cycle that is never less than 12% and can exceed 21%. When Envisat operates in Wide Swath Mode, the bistatic system covers a wide latitude range across the equator, while in some of the Image Swath Modes, the bistatic measurements, collected from the same orbit, cover mid-latitude areas. In the latter case, it might be possible to achieve full coverage in an Envisat orbit repeat cycle, while, for a very large latitude range such as that covered in Wide Swath Mode, bistatic acquisitions could be obtained over about 65% of the area.

  9. Advanced analysis techniques for uranium assay

    SciTech Connect

    Geist, W. H.; Ensslin, Norbert; Carrillo, L. A.; Beard, C. A.

    2001-01-01

    Uranium has a negligible passive neutron emission rate making its assay practicable only with an active interrogation method. The active interrogation uses external neutron sources to induce fission events in the uranium in order to determine the mass. This technique requires careful calibration with standards that are representative of the items to be assayed. The samples to be measured are not always well represented by the available standards which often leads to large biases. A technique of active multiplicity counting is being developed to reduce some of these assay difficulties. Active multiplicity counting uses the measured doubles and triples count rates to determine the neutron multiplication (f4) and the product of the source-sample coupling ( C ) and the 235U mass (m). Since the 35U mass always appears in the multiplicity equations as the product of Cm, the coupling needs to be determined before the mass can be known. A relationship has been developed that relates the coupling to the neutron multiplication. The relationship is based on both an analytical derivation and also on empirical observations. To determine a scaling constant present in this relationship, known standards must be used. Evaluation of experimental data revealed an improvement over the traditional calibration curve analysis method of fitting the doubles count rate to the 235Um ass. Active multiplicity assay appears to relax the requirement that the calibration standards and unknown items have the same chemical form and geometry.

  10. Advances in carbonate exploration and reservoir analysis

    USGS Publications Warehouse

    Garland, J.; Neilson, J.; Laubach, S.E.; Whidden, Katherine J.

    2012-01-01

    The development of innovative techniques and concepts, and the emergence of new plays in carbonate rocks are creating a resurgence of oil and gas discoveries worldwide. The maturity of a basin and the application of exploration concepts have a fundamental influence on exploration strategies. Exploration success often occurs in underexplored basins by applying existing established geological concepts. This approach is commonly undertaken when new basins ‘open up’ owing to previous political upheavals. The strategy of using new techniques in a proven mature area is particularly appropriate when dealing with unconventional resources (heavy oil, bitumen, stranded gas), while the application of new play concepts (such as lacustrine carbonates) to new areas (i.e. ultra-deep South Atlantic basins) epitomizes frontier exploration. Many low-matrix-porosity hydrocarbon reservoirs are productive because permeability is controlled by fractures and faults. Understanding basic fracture properties is critical in reducing geological risk and therefore reducing well costs and increasing well recovery. The advent of resource plays in carbonate rocks, and the long-standing recognition of naturally fractured carbonate reservoirs means that new fracture and fault analysis and prediction techniques and concepts are essential.

  11. Spatial-temporal analysis of breast cancer in upper Cape Cod, Massachusetts

    PubMed Central

    Vieira, Verónica M; Webster, Thomas F; Weinberg, Janice M; Aschengrau, Ann

    2008-01-01

    Introduction The reasons for elevated breast cancer rates in the upper Cape Cod area of Massachusetts remain unknown despite several epidemiological studies that investigated possible environmental risk factors. Data from two of these population-based case-control studies provide geocoded residential histories and information on confounders, creating an invaluable dataset for spatial-temporal analysis of participants' residency over five decades. Methods The combination of statistical modeling and mapping is a powerful tool for visualizing disease risk in a spatial-temporal analysis. Advances in geographic information systems (GIS) enable spatial analytic techniques in public health studies previously not feasible. Generalized additive models (GAMs) are an effective approach for modeling spatial and temporal distributions of data, combining a number of desirable features including smoothing of geographical location, residency duration, or calendar years; the ability to estimate odds ratios (ORs) while adjusting for confounders; selection of optimum degree of smoothing (span size); hypothesis testing; and use of standard software. We conducted a spatial-temporal analysis of breast cancer case-control data using GAMs and GIS to determine the association between participants' residential history during 1947–1993 and the risk of breast cancer diagnosis during 1983–1993. We considered geographic location alone in a two-dimensional space-only analysis. Calendar year, represented by the earliest year a participant lived in the study area, and residency duration in the study area were modeled individually in one-dimensional time-only analyses, and together in a two-dimensional time-only analysis. We also analyzed space and time together by applying a two-dimensional GAM for location to datasets of overlapping calendar years. The resulting series of maps created a movie which allowed us to visualize changes in magnitude, geographic size, and location of elevated breast

  12. Spatial analysis of sedimentary controls on submarine groundwater discharge

    NASA Astrophysics Data System (ADS)

    Rapaglia, J.; Vafeidis, A.; Ferrarin, C.; Sarretta, A.; Molinari, M.; Zaggia, L.

    2009-04-01

    , as well as occasional problems with edge effects. Meanwhile, a concurrent study of sediment distribution was performed on more than 100 cores throughout the Venice Lagoon, and sediment was separated into grain size by percentage. This data was further amalgamated into 11 classes based on the USDA grain size diagram and plotted in the Venice Lagoon using ArcGIS. Grain size in-between known points were interpolated using, again, different techniques. Ra activity distribution was then compared with sediment size distribution. Each Ra point sample was compared with sediment samples within a given radius of the sample point. High resolution bathymetry was also utilized to determine grain size and known channels were considered natural borders. Sediment samples within the determined radius, yet in or on the other side of a channel were discounted due to the hydrodynamic barrier created by the channel properties. The relationship between Ra activity and sediment size distribution was analyzed. In general we expected that sandy and sandy-silt size classes would correspond to high Ra activity however, in some cases the correlation was not perfect, specifically near the inlets, where large grain size sediment was found coincident with low Ra concentrations. Still, this is expected as water near the inlet is dominated by re-circulation with low activity Adriatic Sea water. With this new information and taken into account expected patterns near the inlets, we will most likely be able to recalculate the mass balance of Ra with more confidence in our final analysis. With current technology and methods, SGD estimates are often given with 100% error bars and at worst within an order of magnitude. One of the problems is that the spatial analysis of SGD is limited. We suggest combining Ra analysis and sediment distribution in coastal lagoons to increase the confidence with which the scientific community can report SGD measurements.

  13. Advanced computational tools for 3-D seismic analysis

    SciTech Connect

    Barhen, J.; Glover, C.W.; Protopopescu, V.A.

    1996-06-01

    The global objective of this effort is to develop advanced computational tools for 3-D seismic analysis, and test the products using a model dataset developed under the joint aegis of the United States` Society of Exploration Geophysicists (SEG) and the European Association of Exploration Geophysicists (EAEG). The goal is to enhance the value to the oil industry of the SEG/EAEG modeling project, carried out with US Department of Energy (DOE) funding in FY` 93-95. The primary objective of the ORNL Center for Engineering Systems Advanced Research (CESAR) is to spearhead the computational innovations techniques that would enable a revolutionary advance in 3-D seismic analysis. The CESAR effort is carried out in collaboration with world-class domain experts from leading universities, and in close coordination with other national laboratories and oil industry partners.

  14. Strong topographic sheltering effects lead to spatially complex treeline advance and increased forest density in a subtropical mountain region.

    PubMed

    Greenwood, Sarah; Chen, Jan-Chang; Chen, Chaur-Tzuhn; Jump, Alistair S

    2014-12-01

    Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate. PMID:25141823

  15. Strong topographic sheltering effects lead to spatially complex treeline advance and increased forest density in a subtropical mountain region.

    PubMed

    Greenwood, Sarah; Chen, Jan-Chang; Chen, Chaur-Tzuhn; Jump, Alistair S

    2014-12-01

    Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate.

  16. Current practices in the spatial analysis of cancer: flies in the ointment

    PubMed Central

    Jacquez, Geoffrey M

    2004-01-01

    While many lessons have been learned from the spatial analysis of cancer, there are several caveats that apply to many, if not all such analyses. As "flies in the ointment", these can substantially detract from a spatial analysis, and if not accounted for, can lead to weakened and erroneous conclusions. This paper discusses several assumptions and limitations of spatial analysis, identifies problems of scientific inference, and concludes with potential solutions and future directions. PMID:15479473

  17. A book review of Spatial data analysis in ecology and agriculture using R

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial Data Analysis in Ecology and Agriculture Using R is a valuable resource to assist agricultural and ecological researchers with spatial data analyses using the R statistical software(www.r-project.org). Special emphasis is on spatial data sets; how-ever, the text also provides ample guidance ...

  18. NASTRAN documentation for flutter analysis of advanced turbopropellers

    NASA Technical Reports Server (NTRS)

    Elchuri, V.; Gallo, A. M.; Skalski, S. C.

    1982-01-01

    An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs was modified to facilitate investigation of the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) varying sweep.

  19. METHODS ADVANCEMENT FOR MILK ANALYSIS: THE MAMA STUDY

    EPA Science Inventory

    The Methods Advancement for Milk Analysis (MAMA) study was designed by US EPA and CDC investigators to provide data to support the technological and study design needs of the proposed National Children=s Study (NCS). The NCS is a multi-Agency-sponsored study, authorized under the...

  20. Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis

    ERIC Educational Resources Information Center

    Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.

    2006-01-01

    Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…

  1. Polybrominated Diphenyl Ethers in Dryer Lint: An Advanced Analysis Laboratory

    ERIC Educational Resources Information Center

    Thompson, Robert Q.

    2008-01-01

    An advanced analytical chemistry laboratory experiment is described that involves environmental analysis and gas chromatography-mass spectrometry. Students analyze lint from clothes dryers for traces of flame retardant chemicals, polybrominated diphenylethers (PBDEs), compounds receiving much attention recently. In a typical experiment, ng/g…

  2. Spatial Microsimulation for Rural Policy Analysis in Ireland: The Implications of CAP Reforms for the National Spatial Strategy

    ERIC Educational Resources Information Center

    Ballas, D.; Clarke, G. P.; Wiemers, E.

    2006-01-01

    Microsimulation attempts to describe economic and social events by modelling the behaviour of individual agents. These models have proved useful in evaluating the impact of policy changes at the micro level. Spatial microsimulation models contain geographic information and allow for a regional or local approach to policy analysis. This paper…

  3. Spatial Analysis of Volcanoes at Convergent Margins on Earth

    NASA Astrophysics Data System (ADS)

    Roberts, R. V.; de Silva, S. L.; Meyers, M.

    2009-12-01

    One of the most obvious patterns seen on the surface of the terrestrial planets is the distribution of volcanoes. On Earth, most volcanoes are distributed in volcanic “arcs” that signal the primary relationship between subduction and volcanism. The distributions of major composite volcanoes in volcanic arcs are thought to reflect the primary magmatic pathways from source to surface. Understanding these patterns therefore may allow fundamental controls on the organization of magmatic plumbing in arcs to be identified. Using a control dataset from the Central Volcanic Zone of the Andes (de Silva and Francis, 1991; Springer-Verlag) we have examined several popular approaches to spatial analysis of volcano distribution in several volcanic arcs (Aleutian, Alaskan, Central American, Northern and Southern volcanic zones of the Andes). Restricting our analysis to major volcanoes of similar age, we find that while clustering is visually obvious in many volcanic arcs it has been rejected as a primary signal by previous analytical efforts (e.g. Bremont d'Ars et al (1995)). We show that the fractal box or grid counting method used previously does not detect clusters and statistical methods such as the Kernel Density Analysis or Single-link Cluster Analysis are better suited for cluster detection. Utilizing both ARC GIS and Matlab to conduct density analyses in combination with statistical software SPlus for the appropriate hypothesis testing methods such as the pooled variance t-test, the Welch Modified two sample t-test, and the f-test we find evidence of clustering in four volcanic arcs whose crustal thickness is greater than or equal to 40 kilometres (Central America, CVZ, NVZ, SVZ). We suggest that clustering is the surface manifestation of upper crustal diffusion of primary magmatic pathways, which in other places manifests as a single volcano. The inter-cluster distance is a thus reflection of primary magmatic pathways and thus equivalent to inter-volcano distance

  4. Learning Geospatial Analysis Skills with Consumer-Grade GPS Receivers and Low Cost Spatial Analysis Software

    ERIC Educational Resources Information Center

    Linehan, Peter E.

    2006-01-01

    Spatial analysis technologies are increasingly important tools for all aspects of forest resource management. Field work previously accomplished with map, compass, and engineers' scale is now being augmented, or superseded, by the use of GPS and GIS. Professional-grade GPS receivers and commercial GIS software are preferred for their accuracy and…

  5. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, T. H. H.

    1985-01-01

    Advanced stress analysis methods applicable to turbine engine structures are investigated. Constructions of special elements which containing traction-free circular boundaries are investigated. New versions of mixed variational principle and version of hybrid stress elements are formulated. A method is established for suppression of kinematic deformation modes. semiLoof plate and shell elements are constructed by assumed stress hybrid method. An elastic-plastic analysis is conducted by viscoplasticity theory using the mechanical subelement model.

  6. Recent Advances in Multidisciplinary Analysis and Optimization, part 1

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  7. Recent Advances in Multidisciplinary Analysis and Optimization, part 3

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  8. Recent Advances in Multidisciplinary Analysis and Optimization, part 2

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  9. Spatial analysis of suicide mortality in Québec: spatial clustering and area factor correlates.

    PubMed

    Ngamini Ngui, André; Apparicio, Philippe; Moltchanova, Elena; Vasiliadis, Helen-Maria

    2014-12-15

    Understanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention actions. No previous study has assessed spatial clustering of the different methods of suicide in Quebec. The aim of this study was to assess spatial clustering of suicide in Quebec between 2004 and 2007 and neighborhood level predictors of the clusters. Scan statistics was applied to detect clusters of suicides by method and by sex. Smoothed standardized mortality ratios (SMRs) for suicide for each neighborhood were also estimated and their association with neighborhood characteristics was investigated using the Bayesian hierarchical spatial model. The pattern of suicide rate was different among men and women; men showed higher standardized mortality rates. The most likely clusters of suicide were found in remote rural areas. However, some neighborhoods in urban areas also had noticeable suicide clusters. Firearms suicide was most likely found in remote rural areas while poisoning and hanging suicide methods clustered in urban areas. These findings suggest that it is important to take geographical variations into account in national policy and health services planning.

  10. A spatial, kinematical, and dynamical analysis of Abell 400

    NASA Technical Reports Server (NTRS)

    Beers, Timothy C.; Gebhardt, Karl; Huchra, John P.; Forman, William; Jones, Christine; Bothun, Gregory D.

    1992-01-01

    The paper presents a detailed spatial, kinematical, and dynamical analysis for the cluster A400, based on a nearly complete redshift survey of bright galaxies within 1 Mpc of the cluster center. A dispersed component with a high fraction of spiral galaxies at a velocity of 8200 km/s, and a background group with a mean velocity of 13,400 km/s are identified. It is proposed that the main body of A400 is composed of at least two individual subclusters. If subclustering is ignored, the derived dispersion of the 88 galaxies with measured velocities within 4000 km/s of the bright dumbbell galaxy near the cluster center is 702 km/s. When kinematic information is used to split A400 into likely subclusters, the velocity dispersions of the individual units which make up this cluster are on the order of 200-300 km/s. If A400 is considered a single entity, the inferred blue mass-to-light ratio is 1210 solar masses/solar luminosities. It is argued that A400 is an example of a presently occurring merger, and that the individual components of the dumbbell galaxy were once individual D galaxies within the premerger subclusters.

  11. A Principal Components Analysis of Dynamic Spatial Memory Biases

    ERIC Educational Resources Information Center

    Motes, Michael A.; Hubbard, Timothy L.; Courtney, Jon R.; Rypma, Bart

    2008-01-01

    Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed…

  12. Elemental Analysis of Glass Optical Fibres with High Spatial Resolution.

    NASA Astrophysics Data System (ADS)

    Pugh, Andrew

    Available from UMI in association with The British Library. The properties of glass optical fibres are very strongly dependent on the elemental concentration profiles of the fibre cores. Core dopants such as germanium define the core refractive index, which in turn defines the manner in which the light is transmitted through the fibre. Erbium in fibre cores can facilitate the operation of fibre lasers and aluminium in turn can control the erbium distribution. The aim of the project described in this thesis was to measure the elemental concentration profiles in a variety of fibre cores using X-ray microanalysis in an electron microscope. Conventional X-ray microanalysis of bulk samples has an analytical resolution in the order of a micron. With monomode optical fibre cores having cores typically three microns in diameter the resolution of the conventional technique is plainly inadequate. An experimental technique has been developed for the preparation of thin cross-sectional samples of glass optical fibres. Application of this technique has facilitated the preparation and analysis of thin film specimens with an average thickness of 400 microns. This approach has allowed analysis to be performed with an effective spatial resolution of 100-300 nm. The technique has been applied to the determination of germanium concentration in Raman fibres, to the investigation of erbium confinement in erbium doped fibres and to the investigation of inter-ionic diffusion in semiconductor doped fibres. It has been shown that the germanium, and hence refractive index, profile of germanium doped fibres is not changed by the process of fibre drawing. Evidence has been gathered supporting the theory of erbium confinement by aluminium and an important degree of elemental diffusion has been shown to take place during the drawing of semiconductor doped fibres. In addition an experimental technique has been developed for the preparation of thin cross-sectional samples of glass optical fibres.

  13. Situated student learning and spatial informational analysis for environmental problems

    NASA Astrophysics Data System (ADS)

    Olsen, Timothy Paul

    Ninth and tenth grade high school Biology student research teams used spatial information analysis tools to site a prairie restoration plot on a 55 acre campus during a four-week environment unit. Students made use of innovative technological practices by applying geographic information systems (GIS) approaches to solving environmental and land use problems. Student learning was facilitated by starting with the students' initial conceptions of computing, local landscape and biological environment, and then by guiding them through a problem-based science project process. The project curriculum was framed by the perspective of legitimate peripheral participation (Lave & Wenger, 1991) where students were provided with learning opportunities designed to allow them to act like GIS practitioners. Sociocultural lenses for learning were employed to create accounts of human mental processes that recognize the essential relationship between these processes and their cultural, historical, and institutional settings (Jacob, 1997; Wertsch, 1991). This research investigated how student groups' meaning-making actions were mediated by GIS tools on the periphery of a scientific community of practice. Research observations focused on supporting interpretations of learners' socially constructed actions and the iterative building of assertions from multiple sources. These included the artifacts students produced, the tools they used, the cultural contexts that constrained their activity, and how people begin to adopt ways of speaking (speech genres) of the referent community to negotiate meanings and roles. Students gathered field observations and interpreted attributes of landscape entities from the GIS data to advocate for an environmental decision. However, even while gaining proficiencies with GIS tools, most students did not begin to appropriate roles from the GIS community of practice. Students continued to negotiate their project actions simply as school exercises motivated by

  14. Isolation and analysis of ginseng: advances and challenges

    PubMed Central

    Wang, Chong-Zhi

    2011-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products in the world. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support ginseng’s use worldwide. In the past decade, rapid development of technology has advanced many aspects of ginseng research. The aim of this review is to illustrate the recent advances in the isolation and analysis of ginseng, and to highlight their new applications and challenges. Emphasis is placed on recent trends and emerging techniques. The current article reviews the literature between January 2000 and September 2010. PMID:21258738

  15. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-08-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  16. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-01-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  17. Advanced Post-Irradiation Examination Capabilities Alternatives Analysis Report

    SciTech Connect

    Jeff Bryan; Bill Landman; Porter Hill

    2012-12-01

    An alternatives analysis was performed for the Advanced Post-Irradiation Capabilities (APIEC) project in accordance with the U.S. Department of Energy (DOE) Order DOE O 413.3B, “Program and Project Management for the Acquisition of Capital Assets”. The Alternatives Analysis considered six major alternatives: ? No Action ? Modify Existing DOE Facilities – capabilities distributed among multiple locations ? Modify Existing DOE Facilities – capabilities consolidated at a few locations ? Construct New Facility ? Commercial Partnership ? International Partnerships Based on the alternatives analysis documented herein, it is recommended to DOE that the advanced post-irradiation examination capabilities be provided by a new facility constructed at the Materials and Fuels Complex at the Idaho National Laboratory.

  18. [Fractal theory and its application in the analysis of soil spatial variability: a review].

    PubMed

    Zhang, Fa-Sheng; Liu, Zuo-Xin

    2011-05-01

    Soil has spatial variability in its attributes. The analysis of soil spatial variability is of significance for soil management. This paper summarized the fractal theory and its application in spatial analysis of soil variability, with the focus on the utilization of moment method in calculating the fractal dimension of soil attributes, the multi-fractal analysis of soil spatial variability, and the scaling up of soil attributes based on multi-fractal parameters. The studies on the application of fractal theory and multi-fractal method in the analysis of soil spatial variability were also reviewed. Fractal theory could be an important tool in quantifying the spatial variability and scaling up of soil attributes.

  19. "ATLAS" Advanced Technology Life-cycle Analysis System

    NASA Technical Reports Server (NTRS)

    Lollar, Louis F.; Mankins, John C.; ONeil, Daniel A.

    2004-01-01

    Making good decisions concerning research and development portfolios-and concerning the best systems concepts to pursue - as early as possible in the life cycle of advanced technologies is a key goal of R&D management This goal depends upon the effective integration of information from a wide variety of sources as well as focused, high-level analyses intended to inform such decisions Life-cycle Analysis System (ATLAS) methodology and tool kit. ATLAS encompasses a wide range of methods and tools. A key foundation for ATLAS is the NASA-created Technology Readiness. The toolkit is largely spreadsheet based (as of August 2003). This product is being funded by the Human and Robotics The presentation provides a summary of the Advanced Technology Level (TRL) systems Technology Program Office, Office of Exploration Systems, NASA Headquarters, Washington D.C. and is being integrated by Dan O Neil of the Advanced Projects Office, NASA/MSFC, Huntsville, AL

  20. Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

    NASA Technical Reports Server (NTRS)

    Jong, Jen-Yi

    1997-01-01

    During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

  1. An advanced image processing method to improve the spatial resolution of ion radiographies

    NASA Astrophysics Data System (ADS)

    Krah, N.; Testa, M.; Brons, S.; Jäkel, O.; Parodi, K.; Voss, B.; Rinaldi, I.

    2015-11-01

    We present an optimization method to improve the spatial resolution and the water equivalent thickness (WET) accuracy of ion radiographies. The method is designed for imaging systems measuring for each actively scanned beam spot the lateral position of the pencil beam and at the same time the Bragg curve (behind the target) in discrete steps without relying on tracker detectors to determine the ion trajectory before and after the irradiated volume. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) interleaved with absorber plates of polymethyl methacrylate (PMMA) working as a range telescope. The method uses not only the Bragg peak position, but approximates the entire measured Bragg curve as a superposition of differently shifted Bragg curves. Their relative weights allow to reconstruct the distribution of thickness around each scan spot of a heterogeneous phantom. The approach also allows merging the ion radiography with the geometric information of a co-registered x-ray radiography in order to increase its spatial resolution. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. For the step phantom, the effective spatial resolution was found to be 6 and 4 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed radiography (DRR) obtained from an x-ray CT and properly converted into WET. For a distance-to-agreement (DTA) of 2.5 mm and a relative WET difference (RWET) of 2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. When the optimized proton radiography was merged with the co-registered DRR, the passing ratio was 100% at DTA  =  1.3 mm and RWET

  2. Structural Analysis of Dusty Plasma Formations Based on Spatial Spectra

    SciTech Connect

    Khakhaev, A. D.; Luizova, L. A.; Piskunov, A. A.; Podryadchikov, S. F.; Soloviev, A. V.

    2008-09-07

    Some advantages of studying the structure of dusty plasma formations using spatial spectra are illustrated by simulated experiments and by processing actual images of dusty structures in dc glow discharge in inert and molecular gases.

  3. Inverse spatial principal component analysis for geophysical survey data interpolation

    NASA Astrophysics Data System (ADS)

    Li, Qingmou; Dehler, Sonya A.

    2015-04-01

    The starting point for data processing, visualization, and overlay with other data sources in geological applications often involves building a regular grid by interpolation of geophysical measurements. Typically, the sampling interval along survey lines is much higher than the spacing between survey lines because the geophysical recording system is able to operate with a high sampling rate, while the costs and slower speeds associated with operational platforms limit line spacing. However, currently available interpolating methods often smooth data observed with higher sampling rate along a survey line to accommodate the lower spacing across lines, and much of the higher resolution information is not captured in the interpolation process. In this approach, a method termed as the inverse spatial principal component analysis (isPCA) is developed to address this problem. In the isPCA method, a whole profile observation as well as its line position is handled as an entity and a survey collection of line entities is analyzed for interpolation. To test its performance, the developed isPCA method is used to process a simulated airborne magnetic survey from an existing magnetic grid offshore the Atlantic coast of Canada. The interpolation results using the isPCA method and other methods are compared with the original survey grid. It is demonstrated that the isPCA method outperforms the Inverse Distance Weighting (IDW), Kriging (Geostatistical), and MINimum Curvature (MINC) interpolation methods in retaining detailed anomaly structures and restoring original values. In a second test, a high resolution magnetic survey offshore Cape Breton, Nova Scotia, Canada, was processed and the results are compared with other geological information. This example demonstrates the effective performance of the isPCA method in basin structure identification.

  4. Numerical analysis of the V-Y shaped advancement flap.

    PubMed

    Remache, D; Chambert, J; Pauchot, J; Jacquet, E

    2015-10-01

    The V-Y advancement flap is a usual technique for the closure of skin defects. A triangular flap is incised adjacent to a skin defect of rectangular shape. As the flap is advanced to close the initial defect, two smaller defects in the shape of a parallelogram are formed with respect to a reflection symmetry. The height of the defects depends on the apex angle of the flap and the closure efforts are related to the defects height. Andrades et al. 2005 have performed a geometrical analysis of the V-Y flap technique in order to reach a compromise between the flap size and the defects width. However, the geometrical approach does not consider the mechanical properties of the skin. The present analysis based on the finite element method is proposed as a complement to the geometrical one. This analysis aims to highlight the major role of the skin elasticity for a full analysis of the V-Y advancement flap. Furthermore, the study of this technique shows that closing at the flap apex seems mechanically the most interesting step. Thus different strategies of defect closure at the flap apex stemming from surgeon's know-how have been tested by numerical simulations. PMID:26342442

  5. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

    ERIC Educational Resources Information Center

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

  6. 77 FR 69509 - Combining Modal Responses and Spatial Components in Seismic Response Analysis

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-19

    ... COMMISSION Combining Modal Responses and Spatial Components in Seismic Response Analysis AGENCY: Nuclear... Components in Seismic Response Analysis'' as an administratively changed guide in which there are minor... the NRC staff considers acceptable for combining modal responses and spatial components in...

  7. Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

    NASA Astrophysics Data System (ADS)

    Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

    2014-01-01

    We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

  8. Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

    SciTech Connect

    Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark; Knowles, David W.; Weber, Gunther H.; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

    2011-03-30

    Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

  9. Geologic spatial analysis. 1988 performance report, August 30, 1987--January 30, 1989

    SciTech Connect

    Thiessen, R.L.; Eliason, J.R.

    1989-12-31

    This report describes the development of geologic spatial analysis research which focuses on conducting comprehensive three-dimensional analysis of regions using geologic data sets that can be referenced by latitude, longitude, and elevation/depth. (CBS)

  10. Advances in Mid-Infrared Spectroscopy for Chemical Analysis

    NASA Astrophysics Data System (ADS)

    Haas, Julian; Mizaikoff, Boris

    2016-06-01

    Infrared spectroscopy in the 3–20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

  11. Advances in Mid-Infrared Spectroscopy for Chemical Analysis.

    PubMed

    Haas, Julian; Mizaikoff, Boris

    2016-06-12

    Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

  12. Advances in Mid-Infrared Spectroscopy for Chemical Analysis

    NASA Astrophysics Data System (ADS)

    Haas, Julian; Mizaikoff, Boris

    2016-06-01

    Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

  13. Advances in urinary proteome analysis and biomarker discovery.

    PubMed

    Fliser, Danilo; Novak, Jan; Thongboonkerd, Visith; Argilés, Angel; Jankowski, Vera; Girolami, Mark A; Jankowski, Joachim; Mischak, Harald

    2007-04-01

    Noninvasive diagnosis of kidney diseases and assessment of the prognosis are still challenges in clinical nephrology. Definition of biomarkers on the basis of proteome analysis, especially of the urine, has advanced recently and may provide new tools to solve those challenges. This article highlights the most promising technological approaches toward deciphering the human proteome and applications of the knowledge in clinical nephrology, with emphasis on the urinary proteome. The data in the current literature indicate that although a thorough investigation of the entire urinary proteome is still a distant goal, clinical applications are already available. Progress in the analysis of human proteome in health and disease will depend more on the standardization of data and availability of suitable bioinformatics and software solutions than on new technological advances. It is predicted that proteomics will play an important role in clinical nephrology in the very near future and that this progress will require interactive dialogue and collaboration between clinicians and analytical specialists.

  14. Advanced gamma ray balloon experiment ground checkout and data analysis

    NASA Technical Reports Server (NTRS)

    Blackstone, M.

    1976-01-01

    A software programming package to be used in the ground checkout and handling of data from the advanced gamma ray balloon experiment is described. The Operator's Manual permits someone unfamiliar with the inner workings of the software system (called LEO) to operate on the experimental data as it comes from the Pulse Code Modulation interface, converting it to a form for later analysis, and monitoring the program of an experiment. A Programmer's Manual is included.

  15. Advanced image analysis for the preservation of cultural heritage

    NASA Astrophysics Data System (ADS)

    France, Fenella G.; Christens-Barry, William; Toth, Michael B.; Boydston, Kenneth

    2010-02-01

    The Library of Congress' Preservation Research and Testing Division has established an advanced preservation studies scientific program for research and analysis of the diverse range of cultural heritage objects in its collection. Using this system, the Library is currently developing specialized integrated research methodologies for extending preservation analytical capacities through non-destructive hyperspectral imaging of cultural objects. The research program has revealed key information to support preservation specialists, scholars and other institutions. The approach requires close and ongoing collaboration between a range of scientific and cultural heritage personnel - imaging and preservation scientists, art historians, curators, conservators and technology analysts. A research project of the Pierre L'Enfant Plan of Washington DC, 1791 had been undertaken to implement and advance the image analysis capabilities of the imaging system. Innovative imaging options and analysis techniques allow greater processing and analysis capacities to establish the imaging technique as the first initial non-invasive analysis and documentation step in all cultural heritage analyses. Mapping spectral responses, organic and inorganic data, topography semi-microscopic imaging, and creating full spectrum images have greatly extended this capacity from a simple image capture technique. Linking hyperspectral data with other non-destructive analyses has further enhanced the research potential of this image analysis technique.

  16. Advanced superposition methods for high speed turbopump vibration analysis

    NASA Technical Reports Server (NTRS)

    Nielson, C. E.; Campany, A. D.

    1981-01-01

    The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.

  17. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    PubMed

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan.

  18. Spatial analysis of fatal and injury crashes in Pennsylvania.

    PubMed

    Aguero-Valverde, Jonathan; Jovanis, Paul P

    2006-05-01

    Using injury and fatal crash data for Pennsylvania for 1996-2000, full Bayes (FB) hierarchical models (with spatial and temporal effects and space-time interactions) are compared to traditional negative binomial (NB) estimates of annual county-level crash frequency. Covariates include socio-demographics, weather conditions, transportation infrastructure and amount of travel. FB hierarchical models are generally consistent with the NB estimates. Counties with a higher percentage of the population under poverty level, higher percentage of their population in age groups 0-14, 15-24, and over 64 and those with increased road mileage and road density have significantly increased crash risk. Total precipitation is significant and positive in the NB models, but not significant with FB. Spatial correlation, time trend, and space-time interactions are significant in the FB injury crash models. County-level FB models reveal the existence of spatial correlation in crash data and provide a mechanism to quantify, and reduce the effect of, this correlation. Addressing spatial correlation is likely to be even more important in road segment and intersection-level crash models, where spatial correlation is likely to be even more pronounced.

  19. Advanced spatio-temporal filtering techniques for photogrammetric image sequence analysis in civil engineering material testing

    NASA Astrophysics Data System (ADS)

    Liebold, F.; Maas, H.-G.

    2016-01-01

    The paper shows advanced spatial, temporal and spatio-temporal filtering techniques which may be used to reduce noise effects in photogrammetric image sequence analysis tasks and tools. As a practical example, the techniques are validated in a photogrammetric spatio-temporal crack detection and analysis tool applied in load tests in civil engineering material testing. The load test technique is based on monocular image sequences of a test object under varying load conditions. The first image of a sequence is defined as a reference image under zero load, wherein interest points are determined and connected in a triangular irregular network structure. For each epoch, these triangles are compared to the reference image triangles to search for deformations. The result of the feature point tracking and triangle comparison process is a spatio-temporally resolved strain value field, wherein cracks can be detected, located and measured via local discrepancies. The strains can be visualized as a color-coded map. In order to improve the measuring system and to reduce noise, the strain values of each triangle must be treated in a filtering process. The paper shows the results of various filter techniques in the spatial and in the temporal domain as well as spatio-temporal filtering techniques applied to these data. The best results were obtained by a bilateral filter in the spatial domain and by a spatio-temporal EOF (empirical orthogonal function) filtering technique.

  20. [Advanced data analysis and visualization for clinical laboratory].

    PubMed

    Inada, Masanori; Yoneyama, Akiko

    2011-01-01

    This paper describes visualization techniques that help identify hidden structures in clinical laboratory data. The visualization of data is helpful for a rapid and better understanding of the characteristics of data sets. Various charts help the user identify trends in data. Scatter plots help prevent misinterpretations due to invalid data by identifying outliers. The representation of experimental data in figures is always useful for communicating results to others. Currently, flexible methods such as smoothing methods and latent structure analysis are available owing to the presence of advanced hardware and software. Principle component analysis, which is a well-known technique used to reduce multidimensional data sets, can be carried out on a personal computer. These methods could lead to advanced visualization with regard to exploratory data analysis. In this paper, we present 3 examples in order to introduce advanced data analysis. In the first example, a smoothing spline was fitted to a time-series from the control chart which is not in a state of statistical control. The trend line was clearly extracted from the daily measurements of the control samples. In the second example, principal component analysis was used to identify a new diagnostic indicator for Graves' disease. The multi-dimensional data obtained from patients were reduced to lower dimensions, and the principle components thus obtained summarized the variation in the data set. In the final example, a latent structure analysis for a Gaussian mixture model was used to draw complex density functions suitable for actual laboratory data. As a result, 5 clusters were extracted. The mixed density function of these clusters represented the data distribution graphically. The methods used in the above examples make the creation of complicated models for clinical laboratories more simple and flexible.

  1. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, Theodore H. H.

    1991-01-01

    The following tasks on the study of advanced stress analysis methods applicable to turbine engine structures are described: (1) constructions of special elements which contain traction-free circular boundaries; (2) formulation of new version of mixed variational principles and new version of hybrid stress elements; (3) establishment of methods for suppression of kinematic deformation modes; (4) construction of semiLoof plate and shell elements by assumed stress hybrid method; and (5) elastic-plastic analysis by viscoplasticity theory using the mechanical subelement model.

  2. Advances in Computational Stability Analysis of Composite Aerospace Structures

    SciTech Connect

    Degenhardt, R.; Araujo, F. C. de

    2010-09-30

    European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.

  3. Advanced Models for Aeroelastic Analysis of Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Keith, Theo G., Jr.; Mahajan, Aparajit

    1996-01-01

    This report describes an integrated, multidisciplinary simulation capability for aeroelastic analysis and optimization of advanced propulsion systems. This research is intended to improve engine development, acquisition, and maintenance costs. One of the proposed simulations is aeroelasticity of blades, cowls, and struts in an ultra-high bypass fan. These ducted fans are expected to have significant performance, fuel, and noise improvements over existing engines. An interface program was written to use modal information from COBSTAN and NASTRAN blade models in aeroelastic analysis with a single rotation ducted fan aerodynamic code.

  4. Spatial analysis of storm depths from an Arizona raingage network

    NASA Technical Reports Server (NTRS)

    Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodriguez-Iturbe, I.

    1986-01-01

    Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.

  5. Advances in nonmarket valuation econometrics: Spatial heterogeneity in hedonic pricing models and preference heterogeneity in stated preference models

    NASA Astrophysics Data System (ADS)

    Yoo, Jin Woo

    In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania

  6. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

    PubMed Central

    Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

  7. Spatial and temporal thermal analysis of acousto-optic deflectors using finite element analysis model.

    PubMed

    Jiang, Runhua; Zhou, Zhenqiao; Lv, Xiaohua; Zeng, Shaoqun; Huang, Zhifeng; Zhou, Huaichun

    2012-07-01

    Thermal effects greatly influence the optical properties of the acousto-optic deflectors (AODs). Thermal analysis plays an important role in modern AOD design. However, the lack of an effective method of analysis limits the prediction in the thermal performance. In this paper, we propose a finite element analysis model to analyze the thermal effects of a TeO(2)-based AOD. Both transducer heating and acoustic absorption are considered as thermal sources. The anisotropy of sound propagation is taken into account for determining the acoustic absorption. Based on this model, a transient thermal analysis is employed using ANSYS software. The spatial temperature distributions in the crystal and the temperature changes over time are acquired. The simulation results are validated by experimental results. The effect of heat source and heat convection on temperature distribution is discussed. This numerical model and analytical method of thermal analysis would be helpful in the thermal design and practical applications of AODs.

  8. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

    PubMed

    Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

  9. GIS as an Integration Tool for Hydrologic Modeling: Spatial Data Management, Analysis and Visualization

    NASA Astrophysics Data System (ADS)

    Setegn, S. G.; Lawrence, A.; Mahmoudi, M.

    2015-12-01

    The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy (DOE) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. The first phase of model development was initiated in 2014 using the MIKE SHE/MIKE 11 hydrological modeling package which has a geographic information systems (GIS) user interface built into its system that can directly use spatial GIS databases (geodatabases) for model inputs. This study developed an ArcGIS geodatabase to support the hydrological modeling work for SRS. The coupling of a geodatabase with MIKE SHE/MIKE 11 numerical models can serve as an efficient tool that significantly reduces the time needed for data preparation. The geodatabase provides an advanced spatial data structure needed to address the management, processing, and analysis of large GIS and timeseries datasets derived from multiple sources that are used for numerical model calibration, uncertainty analysis, and simulation of flow and contaminant fate and transport during extreme climatic events. The geodatabase developed is based on the ArcHydro and ArcGIS Base Map data models with modifications made for project specific input parameters. The significance of this approach was to ensure its replicability for potential application in other watersheds. This paper describes the process of development of the SRS geodatabase and the application of GIS tools to pre-process and analyze hydrological model data; automate repetitive geoprocessing tasks; and produce maps for visualization of the surface water hydrology of the Tims Branch watershed. Key Words: GIS, hydrological modeling, geodatabase, hydrology, MIKE SHE/MIKE 11

  10. Validation Database Based Thermal Analysis of an Advanced RPS Concept

    NASA Technical Reports Server (NTRS)

    Balint, Tibor S.; Emis, Nickolas D.

    2006-01-01

    Advanced RPS concepts can be conceived, designed and assessed using high-end computational analysis tools. These predictions may provide an initial insight into the potential performance of these models, but verification and validation are necessary and required steps to gain confidence in the numerical analysis results. This paper discusses the findings from a numerical validation exercise for a small advanced RPS concept, based on a thermal analysis methodology developed at JPL and on a validation database obtained from experiments performed at Oregon State University. Both the numerical and experimental configurations utilized a single GPHS module enabled design, resembling a Mod-RTG concept. The analysis focused on operating and environmental conditions during the storage phase only. This validation exercise helped to refine key thermal analysis and modeling parameters, such as heat transfer coefficients, and conductivity and radiation heat transfer values. Improved understanding of the Mod-RTG concept through validation of the thermal model allows for future improvements to this power system concept.

  11. Structural Configuration Systems Analysis for Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Welstead, Jason R.; Quinlan, Jesse R.; Guynn, Mark D.

    2016-01-01

    Structural configuration analysis of an advanced aircraft fuselage concept is investigated. This concept is characterized by a double-bubble section fuselage with rear mounted engines. Based on lessons learned from structural systems analysis of unconventional aircraft, high-fidelity finite-element models (FEM) are developed for evaluating structural performance of three double-bubble section configurations. Structural sizing and stress analysis are applied for design improvement and weight reduction. Among the three double-bubble configurations, the double-D cross-section fuselage design was found to have a relatively lower structural weight. The structural FEM weights of these three double-bubble fuselage section concepts are also compared with several cylindrical fuselage models. Since these fuselage concepts are different in size, shape and material, the fuselage structural FEM weights are normalized by the corresponding passenger floor area for a relative comparison. This structural systems analysis indicates that an advanced composite double-D section fuselage may have a relative structural weight ratio advantage over a conventional aluminum fuselage. Ten commercial and conceptual aircraft fuselage structural weight estimates, which are empirically derived from the corresponding maximum takeoff gross weight, are also presented and compared with the FEM- based estimates for possible correlation. A conceptual full vehicle FEM model with a double-D fuselage is also developed for preliminary structural analysis and weight estimation.

  12. Insights to urban dynamics through landscape spatial pattern analysis

    NASA Astrophysics Data System (ADS)

    TV, Ramachandra; Aithal, Bharath H.; Sanna, Durgappa D.

    2012-08-01

    Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of land use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good governance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growth in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973-1992), 129.56% (during 1992-1999), 106.7% (1999-2002), 114.51% (2002-2006) and 126.19% from 2006 to 2010. The Study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levels. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon's entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon's entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about the sprawl. Principal component

  13. Spatial analysis of feline immunodeficiency virus infection in cougars.

    PubMed

    Wheeler, David C; Waller, Lance A; Biek, Roman

    2010-07-01

    The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations.

  14. A study of spatial data management and analysis systems

    NASA Technical Reports Server (NTRS)

    Christopher, Clyde; Galle, Richard

    1989-01-01

    The Earth Resources Laboratory of the NASA Stennis Space Center is a center of space related technology for Earth observations. It has assumed the task, in a joint effort with Jackson State University, to reach out to the science community and acquire information pertaining to characteristics of spatially oriented data processing.

  15. Spatial Analysis of Feline Immunodeficiency Virus Infection in Cougars

    PubMed Central

    Wheeler, David C.; Waller, Lance A.; Biek, Roman

    2010-01-01

    The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations. PMID:21197421

  16. Spatial and Statistical Analysis of Leptospirosis in Guilan Province, Iran

    NASA Astrophysics Data System (ADS)

    Nia, A. Mohammadi; Alimohammadi, A.; Habibi, R.; Shirzadi, M. R.

    2015-12-01

    The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009-2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran's I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.

  17. Spatial autocorrelation analysis of hyperspectral imagery for feature selection

    SciTech Connect

    Warner, T.A.; Shank, M.C.

    1997-04-01

    The spatial information in a single spectral image can be estimated from the spatial autocorrelation, which is a measure of how the local variation compares with the overall variance in a scene. In images of random noise, the local variation tends to be similar to the overall variance. In contrast, scenes in which large features can be discerned have clusters of pixels with similar values, which cause the local variation to be much smaller on average than the overall scene variance. Feature selection is the process of finding a subset of the original bands that provides an optimal trade-off between probability of error and classification cost. Three feature selection problems are addressed in this paper: (1) narrow band feature selection, which is the selection of a subset of individual bands; (2) broad band feature selection, in which groups of adjacent bands are selected, and (3) nonadjacent multiple band feature selection, in which selection of the groups of bands is not limited to adjacent bands. Spatial autocorrelation is useful in all three feature selection problems. Tests with simulated data indicate that the spatial autocorrelation based methods consistently identify the best bands or groups of bands. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of eastern Washington state are used to illustrate the technique on real data.

  18. Phenylketonuria and Complex Spatial Visualization: An Analysis of Information Processing.

    ERIC Educational Resources Information Center

    Brunner, Robert L.; And Others

    1987-01-01

    The study of the ability of 16 early treated phenylketonuric (PKU) patients (ages 6-23 years) to solve complex spatial problems suggested that choice of problem-solving strategy, attention span, and accuracy of mental representation may be affected in PKU patients, despite efforts to maintain well-controlled phenylalanine concentrations in the…

  19. Model Analysis of Spatial Patterns in Mountain Pine Beetle Outbreaks.

    PubMed

    Logan; White; Bentz; Powell

    1998-06-01

    The mountain pine beetle [MPB, Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae)] is an aggressive bark beetle, one that typically needs to kill host trees in order to successfully reproduce. This ecological adaptation has resulted in an organism that is both economically important and ecologically significant. Even though significant resources have been expended on MPB research, and a great deal of knowledge exists regarding individual aspects of MPB ecology, some of the most basic questions regarding outbreaks remain unanswered. In our opinion, one reason for the lack of synthesis and predictive power is the inadequate treatment of spatial dynamics in outbreak theories. This paper explicitly addresses the role of spatial dynamics in the precipitation and propagation of MPB outbreaks. We first describe a spatially dynamic model of the MPB/forest interaction that includes chemical ecology, spatial redistribution of beetles, attack, and resulting host mortality. The model is a system of 6 coupled, partial differential equations with 7 state variables and 20 parameters. It represents an attempt to capture the relatively complex predator/prey interaction between MPB and host trees by including the minimum phenomenological descriptions necessary for ecological credibility. This system of equations describes the temporal dynamics of: beetle attraction as a function of pheromone concentration; the change in numbers of flying and nesting beetles; tree resistance/susceptibility; and tree recovery from attack. Spatial dynamics are modeled by fluxes due to gradients in pheromones and kairomones, and the random redistribution of beetles in absence of semiochemicals. We then use the parameterized model to explore three issues central to the ecology of MPB/forest interaction. The first of these is in response to the need for objective ways to compare patterns of successful beetle attacks as they evolve in space. Simulation results indicate that at endemic levels, the

  20. Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

    NASA Astrophysics Data System (ADS)

    Berezowski, T.; Nossent, J.; Chormański, J.; Batelaan, O.

    2015-04-01

    As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly increasing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis method for spatial input data (snow cover fraction - SCF) for a distributed rainfall-runoff model to investigate when the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focussed on the relation between the SCF sensitivity and the physical and spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland, for which a distributed WetSpa model is set up to simulate 2 years of daily runoff. The sensitivity analysis uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which employs different response functions for each spatial parameter representing a 4 × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as geomorphology, soil texture, land use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for our spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model. The developed method can be easily applied to other models and other spatial data.

  1. Advances in the chemical analysis and biological activities of chuanxiong.

    PubMed

    Li, Weixia; Tang, Yuping; Chen, Yanyan; Duan, Jin-Ao

    2012-01-01

    Chuanxiong Rhizoma (Chuan-Xiong, CX), the dried rhizome of Ligusticum chuanxiong Hort. (Umbelliferae), is one of the most popular plant medicines in the World. Modern research indicates that organic acids, phthalides, alkaloids, polysaccharides, ceramides and cerebrosides are main components responsible for the bioactivities and properties of CX. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support CX's use worldwide. In the past two decades, rapid development of technology has advanced many aspects of CX research. The aim of this review is to illustrate the recent advances in the chemical analysis and biological activities of CX, and to highlight new applications and challenges. Emphasis is placed on recent trends and emerging techniques. PMID:22955453

  2. Whole-genome CNV analysis: advances in computational approaches

    PubMed Central

    Pirooznia, Mehdi; Goes, Fernando S.; Zandi, Peter P.

    2015-01-01

    Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development. PMID:25918519

  3. Spatial Autocorrelation Analysis of Chinese Inter-Provincial Industrial Chemical Oxygen Demand Discharge

    PubMed Central

    Zhao, Xiaofeng; Huang, Xianjin; Liu, Yibo

    2012-01-01

    A spatial autocorrelation analysis method is adopted to process the spatial dynamic change of industrial Chemical Oxygen Demand (COD) discharge in China over the past 15 years. Studies show that amount and intensity of industrial COD discharges are on a decrease, and the tendency is more remarkable for discharge intensity. There are large differences between inter-provincial discharge amount and intensity, and with different spatial differentiation features. Global spatial autocorrelation analysis reveals that Global Moran’s I of discharge amount and intensity is on the decrease. In space, there is an evolution from an agglomeration pattern to a discretization pattern. Local spatial autocorrelation analysis shows that the agglomeration area of industrial COD discharge amount and intensity varies greatly in space with time. Stringent environmental regulations and increased funding for environmental protections are the crucial factors to cut down industrial COD discharge amount and intensity. PMID:22829788

  4. Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

    SciTech Connect

    Prado, T. L.; Galuzio, P. P.; Lopes, S. R.; Viana, R. L.

    2014-03-15

    Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image.

  5. Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

    NASA Astrophysics Data System (ADS)

    Prado, T. L.; Galuzio, P. P.; Lopes, S. R.; Viana, R. L.

    2014-03-01

    Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image.

  6. A spatial analysis of phosphorus in the Mississippi river basin.

    PubMed

    Jacobson, Linda M; David, Mark B; Drinkwater, Laurie E

    2011-01-01

    Phosphorus (P) in rivers in the Mississippi River basin (MRB) contributes to hypoxia in the Gulf of Mexico and impairs local water quality. We analyzed the spatial pattern of P in the MRB to determine the counties with the greatest January to June P riverine yields and the most critical factors related to this P loss. Using a database of P inputs and landscape characteristics from 1997 through 2006 for each county in the MRB, we created regression models relating riverine total P (TP), dissolved reactive P (DRP), and particulate P (PP) yields for watersheds within the MRB to these factors. Riverine yields of P were estimated from the average concentration of each form of P during January to June for the 10-yr period, multiplied by the average daily flow, and then summed for the 6-mo period. The fraction of land planted in crops, human consumption of P, and precipitation were found to best predict TP yields with a spatial error regression model ( = 0.48, = 101). Dissolved reactive P yields were predicted by fertilizer P inputs, human consumption of P, and precipitation in a multiple regression model ( = 0.42, = 73), whereas PP yields were explained by crop fraction, human consumption of P, and soil bulk density in a spatial error regression model ( = 0.49, = 61). Overall, the Upper Midwest's Cornbelt region and lower Mississippi basin had the counties with the greatest P yields. These results help to point out specific areas where agricultural conservation practices that reduce losses to streams and rivers and point source P removal might limit the intensity or spatial occurrence of Gulf of Mexico hypoxia and improve local water quality. PMID:21546679

  7. Analysis of diode lasers with lateral spatial variations in thickness

    NASA Astrophysics Data System (ADS)

    Streifer, W.; Burnham, R. D.; Scifres, D. R.

    1980-07-01

    Diode lasers with active and/or cladding regions whose thicknesses vary spatially parallel to the p-n junction are analyzed. It is shown that lateral real-refractive-index waveguiding occurs and that a diffusion gradient exists which propels the injected charges into the lasing modal volume. Lateral mode patterns and thresholds are calculated and sensitivity to higher-order lateral mode oscillation is evaluated for various stripe widths and spreading resistances. Results are shown to agree well with experimental data.

  8. Automated defect spatial signature analysis for semiconductor manufacturing process

    DOEpatents

    Tobin, Jr., Kenneth W.; Gleason, Shaun S.; Karnowski, Thomas P.; Sari-Sarraf, Hamed

    1999-01-01

    An apparatus and method for performing automated defect spatial signature alysis on a data set representing defect coordinates and wafer processing information includes categorizing data from the data set into a plurality of high level categories, classifying the categorized data contained in each high level category into user-labeled signature events, and correlating the categorized, classified signature events to a present or incipient anomalous process condition.

  9. The Nexus of Place and Finance in the Analysis of Educational Attainment: A Spatial Econometric Approach

    ERIC Educational Resources Information Center

    Sutton, Farah

    2012-01-01

    This study examines the spatial distribution of educational attainment and then builds upon current predictive frameworks for understanding patterns of educational attainment by applying a spatial econometric method of analysis. The research from this study enables a new approach to the policy discussion on how to improve educational attainment…

  10. Rate distortion analysis for spatially scalable video coding.

    PubMed

    Zhang, Rong; Comer, Mary L

    2010-11-01

    In this paper, we derive the rate distortion lower bounds of spatially scalable video coding techniques. The methods we evaluate are subband and pyramid motion compensation where temporal redundancies in the same spatial layer as well as interlayer spatial redundancies are exploited in the enhancement layer encoding. The rate distortion bounds are derived from rate distortion theory for stationary Gaussian signals where mean square error is used as the distortion criteria. Assuming that the base layer is encoded by a non-scalable video coder, we derive the rate distortion functions for the enhancement layer, which depend on the power spectral density of the input signal, the motion prediction error probability density function and the base layer encoding performance. We will show that pyramid and subband methods are expected to outperform independently encoding the enhancement layer using motion-compensated prediction, in terms of rate distortion efficiency, when the base layer is encoded at a relatively higher quality or less accurate displacement estimation happens in the enhancement layer. PMID:20519155

  11. Spatial-decomposition analysis of electrical conductivity in ionic liquid.

    PubMed

    Tu, Kai-Min; Ishizuka, Ryosuke; Matubayasi, Nobuyuki

    2014-12-28

    The electrical conductivity of room temperature ionic liquid (IL) is investigated with molecular dynamics simulation. A trajectory of 1 μs in total is analyzed for the ionic liquid [C4mim][NTf2] (1-n-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, and the anion is also called TFSI or TFSA), and the ion motions are examined in direct connection to the conductivity within the framework formulated previously [K.-M. Tu, R. Ishizuka, and N. Matubayasi, J. Chem. Phys. 141, 044126 (2014)]. As a transport coefficient, the computed electrical conductivity is in fair agreement with the experiment. The conductivity is then decomposed into the autocorrelation term of Nernst-Einstein form and the cross-correlation term describing the two-body motions of ions, and the cross-correlation term is further decomposed spatially to incorporate the structural insights on ion configurations into the dynamic picture. It is observed that the ion-pair contribution to the conductivity is not spatially localized and extends beyond the first coordination shell. The extent of localization of the cross-correlation effect in the conductivity is in correspondence to that of the spatial correlation represented by radial distribution function, which persists over nanometer scale.

  12. An advanced probabilistic structural analysis method for implicit performance functions

    NASA Technical Reports Server (NTRS)

    Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

    1989-01-01

    In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

  13. Temporal and Spatial Analysis of Monogenetic Volcanic Fields

    NASA Astrophysics Data System (ADS)

    Kiyosugi, Koji

    Achieving an understanding of the nature of monogenetic volcanic fields depends on identification of the spatial and temporal patterns of volcanism in these fields, and their relationships to structures mapped in the shallow crust and inferred in the deep crust and mantle through interpretation of geochemical, radiometric and geophysical data. We investigate the spatial and temporal distributions of volcanism in the Abu Monogenetic Volcano Group, Southwest Japan. E-W elongated volcano distribution, which is identified by a nonparametric kernel method, is found to be consistent with the spatial extent of P-wave velocity anomalies in the lower crust and upper mantle, supporting the idea that the spatial density map of volcanic vents reflects the geometry of a mantle diapir. Estimated basalt supply to the lower crust is constant. This observation and the spatial distribution of volcanic vents suggest stability of magma productivity and essentially constant two-dimensional size of the source mantle diapir. We mapped conduits, dike segments, and sills in the San Rafael sub-volcanic field, Utah, where the shallowest part of a Pliocene magmatic system is exceptionally well exposed. The distribution of conduits matches the major features of dike distribution, including development of clusters and distribution of outliers. The comparison of San Rafael conduit distribution and the distributions of volcanoes in several recently active volcanic fields supports the use of statistical models, such as nonparametric kernel methods, in probabilistic hazard assessment for distributed volcanism. We developed a new recurrence rate calculation method that uses a Monte Carlo procedure to better reflect and understand the impact of uncertainties of radiometric age determinations on uncertainty of recurrence rate estimates for volcanic activity in the Abu, Yucca Mountain Region, and Izu-Tobu volcanic fields. Results suggest that the recurrence rates of volcanic fields can change by more

  14. Composite Structure Modeling and Analysis of Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Sorokach, Michael R.

    2015-01-01

    NASA Environmentally Responsible Aviation (ERA) project and the Boeing Company are collabrating to advance the unitized damage arresting composite airframe technology with application to the Hybrid-Wing-Body (HWB) aircraft. The testing of a HWB fuselage section with Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) construction is presently being conducted at NASA Langley. Based on lessons learned from previous HWB structural design studies, improved finite-element models (FEM) of the HWB multi-bay and bulkhead assembly are developed to evaluate the performance of the PRSEUS construction. In order to assess the comparative weight reduction benefits of the PRSEUS technology, conventional cylindrical skin-stringer-frame models of a cylindrical and a double-bubble section fuselage concepts are developed. Stress analysis with design cabin-pressure load and scenario based case studies are conducted for design improvement in each case. Alternate analysis with stitched composite hat-stringers and C-frames are also presented, in addition to the foam-core sandwich frame and pultruded rod-stringer construction. The FEM structural stress, strain and weights are computed and compared for relative weight/strength benefit assessment. The structural analysis and specific weight comparison of these stitched composite advanced aircraft fuselage concepts demonstrated that the pressurized HWB fuselage section assembly can be structurally as efficient as the conventional cylindrical fuselage section with composite stringer-frame and PRSEUS construction, and significantly better than the conventional aluminum construction and the double-bubble section concept.

  15. Advancing the Science of Spatial Neglect Rehabilitation: An Improved Statistical Approach with Mixed Linear Modeling

    PubMed Central

    Goedert, Kelly M.; Boston, Raymond C.; Barrett, A. M.

    2013-01-01

    Valid research on neglect rehabilitation demands a statistical approach commensurate with the characteristics of neglect rehabilitation data: neglect arises from impairment in distinct brain networks leading to large between-subject variability in baseline symptoms and recovery trajectories. Studies enrolling medically ill, disabled patients, may suffer from missing, unbalanced data, and small sample sizes. Finally, assessment of rehabilitation requires a description of continuous recovery trajectories. Unfortunately, the statistical method currently employed in most studies of neglect treatment [repeated measures analysis of variance (ANOVA), rANOVA] does not well-address these issues. Here we review an alternative, mixed linear modeling (MLM), that is more appropriate for assessing change over time. MLM better accounts for between-subject heterogeneity in baseline neglect severity and in recovery trajectory. MLM does not require complete or balanced data, nor does it make strict assumptions regarding the data structure. Furthermore, because MLM better models between-subject heterogeneity it often results in increased power to observe treatment effects with smaller samples. After reviewing current practices in the field, and the assumptions of rANOVA, we provide an introduction to MLM. We review its assumptions, uses, advantages, and disadvantages. Using real and simulated data, we illustrate how MLM may improve the ability to detect effects of treatment over ANOVA, particularly with the small samples typical of neglect research. Furthermore, our simulation analyses result in recommendations for the design of future rehabilitation studies. Because between-subject heterogeneity is one important reason why studies of neglect treatments often yield conflicting results, employing statistical procedures that model this heterogeneity more accurately will increase the efficiency of our efforts to find treatments to improve the lives of individuals with neglect. PMID

  16. Environmental condition assessment of US military installations using GIS based spatial multi-criteria decision analysis.

    PubMed

    Singer, Steve; Wang, Guangxing; Howard, Heidi; Anderson, Alan

    2012-08-01

    Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are

  17. Building waste management core indicators through Spatial Material Flow Analysis: Net recovery and transport intensity indexes

    SciTech Connect

    Font Vivanco, David; Puig Ventosa, Ignasi; Gabarrell Durany, Xavier

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer Sustainability and proximity principles have a key role in waste management. Black-Right-Pointing-Pointer Core indicators are needed in order to quantify and evaluate them. Black-Right-Pointing-Pointer A systematic, step-by-step approach is developed in this study for their development. Black-Right-Pointing-Pointer Transport may play a significant role in terms of environmental and economic costs. Black-Right-Pointing-Pointer Policy action is required in order to advance in the consecution of these principles. - Abstract: In this paper, the material and spatial characterization of the flows within a municipal solid waste (MSW) management system are combined through a Network-Based Spatial Material Flow Analysis. Using this information, two core indicators are developed for the bio-waste fraction, the Net Recovery Index (NRI) and the Transport Intensity Index (TII), which are aimed at assessing progress towards policy-related sustainable MSW management strategies and objectives. The NRI approaches the capacity of a MSW management system for converting waste into resources through a systematic metabolic approach, whereas the TII addresses efficiency in terms of the transport requirements to manage a specific waste flow throughout the entire MSW management life cycle. Therefore, both indicators could be useful in assessing key MSW management policy strategies, such as the consecution of higher recycling levels (sustainability principle) or the minimization of transport by locating treatment facilities closer to generation sources (proximity principle). To apply this methodological approach, the bio-waste management system of the region of Catalonia (Spain) has been chosen as a case study. Results show the adequacy of both indicators for identifying those points within the system with higher capacity to compromise its environmental, economic and social performance and therefore establishing clear targets for policy

  18. Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

    NASA Astrophysics Data System (ADS)

    Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

    Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA

  19. Advanced Wireless Power Transfer Vehicle and Infrastructure Analysis (Presentation)

    SciTech Connect

    Gonder, J.; Brooker, A.; Burton, E.; Wang, J.; Konan, A.

    2014-06-01

    This presentation discusses current research at NREL on advanced wireless power transfer vehicle and infrastructure analysis. The potential benefits of E-roadway include more electrified driving miles from battery electric vehicles, plug-in hybrid electric vehicles, or even properly equipped hybrid electric vehicles (i.e., more electrified miles could be obtained from a given battery size, or electrified driving miles could be maintained while using smaller and less expensive batteries, thereby increasing cost competitiveness and potential market penetration). The system optimization aspect is key given the potential impact of this technology on the vehicles, the power grid and the road infrastructure.

  20. Advanced water window x-ray microscope design and analysis

    NASA Technical Reports Server (NTRS)

    Shealy, D. L.; Wang, C.; Jiang, W.; Lin, J.

    1992-01-01

    The project was focused on the design and analysis of an advanced water window soft-x-ray microscope. The activities were accomplished by completing three tasks contained in the statement of work of this contract. The new results confirm that in order to achieve resolutions greater than three times the wavelength of the incident radiation, it will be necessary to use aspherical mirror surfaces and to use graded multilayer coatings on the secondary (to accommodate the large variations of the angle of incidence over the secondary when operating the microscope at numerical apertures of 0.35 or greater). The results are included in a manuscript which is enclosed in the Appendix.

  1. Computer modeling for advanced life support system analysis.

    PubMed

    Drysdale, A

    1997-01-01

    This article discusses the equivalent mass approach to advanced life support system analysis, describes a computer model developed to use this approach, and presents early results from modeling the NASA JSC BioPlex. The model is built using an object oriented approach and G2, a commercially available modeling package Cost factor equivalencies are given for the Volosin scenarios. Plant data from NASA KSC and Utah State University (USU) are used, together with configuration data from the BioPlex design effort. Initial results focus on the importance of obtaining high plant productivity with a flight-like configuration. PMID:11540448

  2. Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

    NASA Technical Reports Server (NTRS)

    Doyle, Monica; ONeil, Daniel A.; Christensen, Carissa B.

    2005-01-01

    The Advanced Technology Lifecycle Analysis System (ATLAS) is a decision support tool designed to aid program managers and strategic planners in determining how to invest technology research and development dollars. It is an Excel-based modeling package that allows a user to build complex space architectures and evaluate the impact of various technology choices. ATLAS contains system models, cost and operations models, a campaign timeline and a centralized technology database. Technology data for all system models is drawn from a common database, the ATLAS Technology Tool Box (TTB). The TTB provides a comprehensive, architecture-independent technology database that is keyed to current and future timeframes.

  3. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data Products for the High Spatial Resolution Imager on NASA's EOS-AMI Platform

    NASA Technical Reports Server (NTRS)

    Abrams, M.

    1999-01-01

    The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution, multispectral imager with along-track stereo capabilities scheduled for launch on the first NASA spacecraft of the Earth Observing System (EOS AM-1) in mid-1999.

  4. Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

    NASA Astrophysics Data System (ADS)

    Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

    2013-12-01

    The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

  5. Advanced analysis of metal distributions in human hair

    SciTech Connect

    Kempson, Ivan M.; Skinner, William M.

    2008-06-09

    A variety of techniques (secondary electron microscopy with energy dispersive X-ray analysis, time-of-flight-secondary ion mass spectrometry, and synchrotron X-ray fluorescence) were utilized to distinguish metal contamination occurring in hair arising from endogenous uptake from an individual exposed to a polluted environment, in this case a lead smelter. Evidence was sought for elements less affected by contamination and potentially indicative of biogenic activity. The unique combination of surface sensitivity, spatial resolution, and detection limits used here has provided new insight regarding hair analysis. Metals such as Ca, Fe, and Pb appeared to have little representative value of endogenous uptake and were mainly due to contamination. Cu and Zn, however, demonstrate behaviors worthy of further investigation into relating hair concentrations to endogenous function.

  6. Advanced analysis of metal distributions in human hair.

    PubMed

    Kempson, Ivan M; Skinner, William M; Kirkbride, K Paul

    2006-05-15

    A variety of techniques (secondary electron microscopy with energy dispersive X-ray analysis, time-of-flight--secondary ion mass spectrometry, and synchrotron X-ray fluorescence) were utilized to distinguish metal contamination occurring in hair arising from endogenous uptake from an individual exposed to a polluted environment, in this case a lead smelter. Evidence was sought for elements less affected by contamination and potentially indicative of biogenic activity. The unique combination of surface sensitivity, spatial resolution, and detection limits used here has provided new insight regarding hair analysis. Metals such as Ca, Fe, and Pb appeared to have little representative value of endogenous uptake and were mainly due to contamination. Cu and Zn, however, demonstrate behaviors worthy of further investigation into relating hair concentrations to endogenous function. PMID:16749716

  7. Spatial analysis of the distribution of intestinal nematode infections in Uganda.

    PubMed Central

    Brooker, S.; Kabatereine, N. B.; Tukahebwa, E. M.; Kazibwe, F.

    2004-01-01

    The spatial epidemiology of intestinal nematodes in Uganda was investigated using generalized additive models and geostatistical methods. The prevalence of Ascaris lumbricoides and Trichuris trichiura was unevenly distributed in the country with prevalence greatest in southwest Uganda whereas hookworm was more homogeneously distributed. A. lumbricoides and T. Trichiura prevalence were nonlinearly related to satellite sensor-based estimates of land surface temperature; hookworm was nonlinearly associated with rainfall. Semivariogram analysis indicated that T. trichiura prevalence exhibited no spatial structure and that A. lumbricoides exhibited some spatial dependency at small spatial distances, once large-scale, mainly environmental, trends had been removed. In contrast, there was much more spatial structure in hookworm prevalence although the underlying factors are at present unclear. The implications of the results are discussed in relation to parasite spatial epidemiology and the prediction of infection distributions. PMID:15635963

  8. Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

    USGS Publications Warehouse

    Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

    2014-01-01

    Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

  9. Analysis of SWOT spatial and temporal samplings over continents

    NASA Astrophysics Data System (ADS)

    Biancamaria, Sylvain; Lamy, Alain; Mognard, Nelly

    2014-05-01

    The future Surface Water and Ocean Topography (SWOT) satellite mission, collaboratively developed by NASA, CNES and CSA, is a joint oceanography/continental hydrology mission planned for launch in 2020. In June 2013, a new SWOT orbit has been selected with a 77.6° inclination, a 21 days repeat cycle and a 891 km altitude. The main satellite payload (a Ka-band SAR Interferometer), will provide 2D maps of water elevation, mask and slope over two swaths, both having a 50 km extent. These two swaths will be separated by a 20 km nadir gap. Most of the studies concerning SWOT published since 2007 have considered a former orbit with a 78° inclination, 22 day repeat orbit and a 970 km altitude and a 60 km extent for each swath. None of them have studied the newly selected orbit and the impact of the 20 km nadir gap on the spatial coverage has not been much explored. The purpose of the work presented here is to investigate the spatial and temporal coverage given this new orbit and the actual swath extent (2*50 km swaths with the 20 km nadir gap in between) and compare it to the former SWOT configuration. It is shown that the new configuration will have almost no impact on the computation of monthly averages, however it will impact the spatial coverage. Because of the nadir gap, the orbit repeatitivity and the swaths extent, 3.6% of the continental surfaces in between 78°S and 78°N will never be observed by SWOT (which was previously equal to 2.2% with the former SWOT configuration). The equatorial regions will be the most impacted, as uncovered area could go up to ~14% locally, whereas it never exceeded 9% with the previous SWOT configuration.

  10. Engineering genders: A spatial analysis of engineering, gender, and learning

    NASA Astrophysics Data System (ADS)

    Weidler-Lewis, Joanna R.

    This three article dissertation is an investigation into the ontology of learning insofar as learning is a process of becoming. In each article I explore the general questions of who is learning, in what ways, and with what consequences. The context for this research is undergraduate engineering education with particular attention to the construction of gender in this context. The first article is an examination of the organization of freshman engineering design. The second article draws on Lefebvre's spatial triad as both a theory and method for studying learning. The third article is an interview study of LGBTQA students creating their futures as engineers.

  11. Spatial analysis techniques applied to uranium prospecting in Chihuahua State, Mexico

    NASA Astrophysics Data System (ADS)

    Hinojosa de la Garza, Octavio R.; Montero Cabrera, María Elena; Sanín, Luz H.; Reyes Cortés, Manuel; Martínez Meyer, Enrique

    2014-07-01

    To estimate the distribution of uranium minerals in Chihuahua, the advanced statistical model "Maximun Entropy Method" (MaxEnt) was applied. A distinguishing feature of this method is that it can fit more complex models in case of small datasets (x and y data), as is the location of uranium ores in the State of Chihuahua. For georeferencing uranium ores, a database from the United States Geological Survey and workgroup of experts in Mexico was used. The main contribution of this paper is the proposal of maximum entropy techniques to obtain the mineral's potential distribution. For this model were used 24 environmental layers like topography, gravimetry, climate (worldclim), soil properties and others that were useful to project the uranium's distribution across the study area. For the validation of the places predicted by the model, comparisons were done with other research of the Mexican Service of Geological Survey, with direct exploration of specific areas and by talks with former exploration workers of the enterprise "Uranio de Mexico". Results. New uranium areas predicted by the model were validated, finding some relationship between the model predictions and geological faults. Conclusions. Modeling by spatial analysis provides additional information to the energy and mineral resources sectors.

  12. Geoscience after ITPart G. Familiarization with spatial analysis

    NASA Astrophysics Data System (ADS)

    Pundt, Hardy; Brinkkötter-Runde, Klaus

    2000-04-01

    Field based and GPS supported GIS are increasingly applied in various spatial disciplines. Such systems represent more sophisticated, time and cost effective tools than traditional field forms for data acquisition. Meanwhile, various systems are on the market. These mostly enable the user to define geo-objects by means of GPS information, supported by functionalities to collect and analyze geometric information. The digital acquisition of application specific attributes is often underrepresented within such systems. This is surprising because pen computer based GIS can be used to collect attributes in a profitable manner, thus adequately supporting the requirements of the user. Visualization and graphic displays of spatial data are helpful means to improve such a data collection process. In section one and two basic aspects of visualization and current uses of visualization techniques for field based GIS are described. Section three mentions new developments within the framework of wearable computing and augmented reality. Section four describes current activities aimed at the realization of real time online field based GIS. This includes efforts to realize an online GIS data link to improve the efficiency and the quality of fieldwork. A brief discussion in section five leads to conclusions and some key issues for future research.

  13. Numerical analysis of the spatial range of the Kondo effect

    SciTech Connect

    Busser, C. A.; Martins, G. B.; Ribeiro, L. Costa; Vernek, E.; Anda, E. V.; Dagotto, Elbio R

    2010-01-01

    The spatial length of the Kondo screening is still a controversial issue related to Kondo physics. While renormalization-group and Bethe-Ansatz solutions have provided detailed information about the thermodynamics of magnetic impurities, they are insufficient to study the effect on the surrounding electrons, i.e., the spatial range of the correlations created by the Kondo effect between the localized magnetic moment and the conduction electrons. The objective of this work is to present a quantitative way of measuring the extension of these correlations by studying their effect directly on the local density of states (LDOS) at arbitrary distances from the impurity. The numerical techniques used, the embedded cluster approximation, the finite-U slave bosons, and numerical renormalization group, calculate the Green s functions in real space. With this information, one can calculate how the local density of states away from the impurity is modified by its presence, below and above the Kondo temperature, and then estimate the range of the disturbances in the noninteracting Fermi sea due to the Kondo effect, and how it changes with the Kondo temperature TK. The results obtained agree with results obtained through spin-spin correlations, showing that the LDOS captures the phenomenology of the Kondo cloud as well.

  14. Tool for Sizing Analysis of the Advanced Life Support System

    NASA Technical Reports Server (NTRS)

    Yeh, Hue-Hsie Jannivine; Brown, Cheryl B.; Jeng, Frank J.

    2005-01-01

    Advanced Life Support Sizing Analysis Tool (ALSSAT) is a computer model for sizing and analyzing designs of environmental-control and life support systems (ECLSS) for spacecraft and surface habitats involved in the exploration of Mars and Moon. It performs conceptual designs of advanced life support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water, and process wastes in order to reduce the need of resource resupply. By assuming steady-state operations, ALSSAT is a means of investigating combinations of such subsystems technologies and thereby assisting in determining the most cost-effective technology combination available. In fact, ALSSAT can perform sizing analysis of the ALS subsystems that are operated dynamically or steady in nature. Using the Microsoft Excel spreadsheet software with Visual Basic programming language, ALSSAT has been developed to perform multiple-case trade studies based on the calculated ECLSS mass, volume, power, and Equivalent System Mass, as well as parametric studies by varying the input parameters. ALSSAT s modular format is specifically designed for the ease of future maintenance and upgrades.

  15. Application of spatial features to satellite land-use analysis. [spectral signature variations

    NASA Technical Reports Server (NTRS)

    Smith, J.; Hornung, R.; Berry, J.

    1975-01-01

    A Level I land-use analysis of selected training areas of the Colorado Front Range was carried out using digital ERTS-A satellite imagery. Level I land-use categories included urban, agriculture (irrigated and dryland farming), rangeland, and forests. The spatial variations in spectral response for these land-use classes were analyzed using discrete two-dimensional Fourier transforms to isolate and extract spatial features. Analysis was performed on ERTS frame 1352-17134 (July 10, 1973) and frame number 1388-17131 (August 15, 1973). On training sets, spatial features yielded 80 to 100 percent classification accuracies with commission errors ranging from 0 to 20 percent.

  16. Spatial compression algorithm for the analysis of very large multivariate images

    DOEpatents

    Keenan, Michael R.

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  17. Adaptive Modeling, Engineering Analysis and Design of Advanced Aerospace Vehicles

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Hsu, Su-Yuen; Mason, Brian H.; Hicks, Mike D.; Jones, William T.; Sleight, David W.; Chun, Julio; Spangler, Jan L.; Kamhawi, Hilmi; Dahl, Jorgen L.

    2006-01-01

    This paper describes initial progress towards the development and enhancement of a set of software tools for rapid adaptive modeling, and conceptual design of advanced aerospace vehicle concepts. With demanding structural and aerodynamic performance requirements, these high fidelity geometry based modeling tools are essential for rapid and accurate engineering analysis at the early concept development stage. This adaptive modeling tool was used for generating vehicle parametric geometry, outer mold line and detailed internal structural layout of wing, fuselage, skin, spars, ribs, control surfaces, frames, bulkheads, floors, etc., that facilitated rapid finite element analysis, sizing study and weight optimization. The high quality outer mold line enabled rapid aerodynamic analysis in order to provide reliable design data at critical flight conditions. Example application for structural design of a conventional aircraft and a high altitude long endurance vehicle configuration are presented. This work was performed under the Conceptual Design Shop sub-project within the Efficient Aerodynamic Shape and Integration project, under the former Vehicle Systems Program. The project objective was to design and assess unconventional atmospheric vehicle concepts efficiently and confidently. The implementation may also dramatically facilitate physics-based systems analysis for the NASA Fundamental Aeronautics Mission. In addition to providing technology for design and development of unconventional aircraft, the techniques for generation of accurate geometry and internal sub-structure and the automated interface with the high fidelity analysis codes could also be applied towards the design of vehicles for the NASA Exploration and Space Science Mission projects.

  18. Information analysis of a spatial database for ecological land classification

    NASA Technical Reports Server (NTRS)

    Davis, Frank W.; Dozier, Jeff

    1990-01-01

    An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

  19. Spectral analysis and filtering techniques in digital spatial data processing

    USGS Publications Warehouse

    Pan, Jeng-Jong

    1989-01-01

    A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

  20. A spatial and genetic analysis of Cowbird host selection

    USGS Publications Warehouse

    Hahn, D.C.; Sedgwick, J.A.; Painter, I.S.; Casna, N.J.; Morrison, Michael L.; Hall, Linnea S.; Robinson, Scott K.; Rothstein, Stephen I.; Hahn, D. Caldwell; Rich, Terrell D.

    1999-01-01

    Our study of brood parasitism patterns in forest communities revealed the egg-laying frequency and host selection patterns of female cowbirds. By integrating molecular genetics and spatial data, we have the first published estimate on cowbird laying rates in field studies. The 29 females in the study laid only 1-5 eggs each, much lower than previous estimates from captive cowbirds and extrapolations from ovarian development in capture/recapture studies that had suggested that as many as 40 eggs could be laid per individual cowbird. Cowbird females also were shown for the first time to lay significantly more eggs within the home range areas they established rather than outside the home range. No patterns were uncovered for individual females preferentially parasitizing particular host species

  1. Optimizing depth estimates from magnetic anomalies using spatial analysis tools

    NASA Astrophysics Data System (ADS)

    Curto, Julia B.; Diniz, Tatiana; Vidotti, Roberta M.; Blakely, Richard J.; Fuck, Reinhardt A.

    2015-11-01

    We offer a methodology to analyze the spatial and statistical properties of the tilt derivative of magnetic anomalies, thus facilitating the mapping of the location and depth of concealed magnetic sources. This methodology uses commonly available graphical information system (GIS) software to estimate and interpolate horizontal distances between key attributes of the tilt derivative, which then are used to estimate depth and location of causative bodies. Application of the method to synthetic data illustrates its reliability to determine depths to magnetic contacts. We also achieved consistent depth results using real data from the northwest portion of the Paraná Basin, Brazil, where magnetic anomaly interpretations are complicated by low geomagnetic inclinations and rocks with remanent magnetization. The tilt-derivative method provides more continuous and higher resolution contact information than the 3D Euler deconvolution technique.

  2. Detecting Hotspots from Taxi Trajectory Data Using Spatial Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhao, P. X.; Qin, K.; Zhou, Q.; Liu, C. K.; Chen, Y. X.

    2015-07-01

    A method of trajectory clustering based on decision graph and data field is proposed in this paper. The method utilizes data field to describe spatial distribution of trajectory points, and uses decision graph to discover cluster centres. It can automatically determine cluster parameters and is suitable to trajectory clustering. The method is applied to trajectory clustering on taxi trajectory data, which are on the holiday (May 1st, 2014), weekday (Wednesday, May 7th, 2014) and weekend (Saturday, May 10th, 2014) respectively, in Wuhan City, China. The hotspots in four hours (8:00-9:00, 12:00-13:00, 18:00-19:00 and 23:00-24:00) for three days are discovered and visualized in heat maps. In the future, we will further research the spatiotemporal distribution and laws of these hotspots, and use more data to carry out the experiments.

  3. Combining microsimulation and spatial interaction models for retail location analysis

    NASA Astrophysics Data System (ADS)

    Nakaya, Tomoki; Fotheringham, A. Stewart; Hanaoka, Kazumasa; Clarke, Graham; Ballas, Dimitris; Yano, Keiji

    2007-12-01

    Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.

  4. Spatial correlation analysis of cascading failures: congestions and blackouts.

    PubMed

    Daqing, Li; Yinan, Jiang; Rui, Kang; Havlin, Shlomo

    2014-06-20

    Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.

  5. Spatial correlation analysis of cascading failures: congestions and blackouts.

    PubMed

    Daqing, Li; Yinan, Jiang; Rui, Kang; Havlin, Shlomo

    2014-01-01

    Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs. PMID:24946927

  6. Advanced probabilistic risk analysis using RAVEN and RELAP-7

    SciTech Connect

    Rabiti, Cristian; Alfonsi, Andrea; Mandelli, Diego; Cogliati, Joshua; Kinoshita, Robert

    2014-06-01

    RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [1], is advancing its capability to perform statistical analyses of stochastic dynamic systems. This is aligned with its mission to provide the tools needed by the Risk Informed Safety Margin Characterization (RISMC) path-lead [2] under the Department Of Energy (DOE) Light Water Reactor Sustainability program [3]. In particular this task is focused on the synergetic development with the RELAP-7 [4] code to advance the state of the art on the safety analysis of nuclear power plants (NPP). The investigation of the probabilistic evolution of accident scenarios for a complex system such as a nuclear power plant is not a trivial challenge. The complexity of the system to be modeled leads to demanding computational requirements even to simulate one of the many possible evolutions of an accident scenario (tens of CPU/hour). At the same time, the probabilistic analysis requires thousands of runs to investigate outcomes characterized by low probability and severe consequence (tail problem). The milestone reported in June of 2013 [5] described the capability of RAVEN to implement complex control logic and provide an adequate support for the exploration of the probabilistic space using a Monte Carlo sampling strategy. Unfortunately the Monte Carlo approach is ineffective with a problem of this complexity. In the following year of development, the RAVEN code has been extended with more sophisticated sampling strategies (grids, Latin Hypercube, and adaptive sampling). This milestone report illustrates the effectiveness of those methodologies in performing the assessment of the probability of core damage following the onset of a Station Black Out (SBO) situation in a boiling water reactor (BWR). The first part of the report provides an overview of the available probabilistic analysis capabilities, ranging from the different types of distributions available, possible sampling

  7. A modified SUnSAL-TV algorithm for hyperspectral unmixing based on spatial homogeneity analysis

    NASA Astrophysics Data System (ADS)

    Yuqian, Wang; Zhenfeng, Shao; Lei, Zhang; Weixun, Zhou

    2014-03-01

    The sparse regression framework has been introduced by many works to solve the linear spectral unmixing problem due to the knowledge that a pixel is usually mixed by less endmembers compared with the endmembers in spectral libraries or the entire hyperspectral data sets. Traditional sparse unmixing techniques focus on analyzing the spectral properties of hyperspectral imagery without incorporating spatial information. But the integration of spatial information would be beneficial to promote the performance of the linear unmixing process. An algorithm called sparse unmixing via variable splitting augmented Lagrangian and total variation (SUnSAL-TV) adds a total variation spatial regularizer besides the sparsity-inducing regularizer to the final unmixing objective function. The total variation spatial regularization is helpful to promote the fractional abundance smoothness. However, the abundance smoothness varies in the image. In this paper, the spatial smoothness is estimated through homogeneity analysis. Then the spatial regularizer is weighted for each pixel by a homogeneity index. The modified algorithm, called homogeneity analysis based SUnSAL-TV (SUnSAL-TVH), integrates the spatial information with finer modelling of spatial smoothness and is supposed insensitive to the noise and more stable. Experiments on synthetic data sets are taken and indicate the validity of our algorithm.

  8. Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

    PubMed

    Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

    2016-02-01

    Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

  9. Spatial and environmental connectivity analysis in a cholera vaccine trial.

    PubMed

    Emch, Michael; Ali, Mohammad; Root, Elisabeth D; Yunus, Mohammad

    2009-02-01

    This paper develops theory and methods for vaccine trials that utilize spatial and environmental information. Satellite imagery is used to identify whether households are connected to one another via water bodies in a study area in rural Bangladesh. Then relationships between neighborhood-level cholera vaccine coverage and placebo incidence and neighborhood-level spatial variables are measured. The study hypothesis is that unvaccinated people who are environmentally connected to people who have been vaccinated will be at lower risk compared to unvaccinated people who are environmentally connected to people who have not been vaccinated. We use four datasets including: a cholera vaccine trial database, a longitudinal demographic database of the rural population from which the vaccine trial participants were selected, a household-level geographic information system (GIS) database of the same study area, and high resolution Quickbird satellite imagery. An environmental connectivity metric was constructed by integrating the satellite imagery with the vaccine and demographic databases linked with GIS. The results show that there is a relationship between neighborhood rates of cholera vaccination and placebo incidence. Thus, people are indirectly protected when more people in their environmentally connected neighborhood are vaccinated. This result is similar to our previous work that used a simpler Euclidean distance neighborhood to measure neighborhood vaccine coverage [Ali, M., Emch, M., von Seidlein, L., Yunus, M., Sack, D. A., Holmgren, J., et al. (2005). Herd immunity conferred by killed oral cholera vaccines in Bangladesh. Lancet, 366(9479), 44-49]. Our new method of measuring environmental connectivity is more precise since it takes into account the transmission mode of cholera and therefore this study validates our assertion that the oral cholera vaccine provides indirect protection in addition to direct protection.

  10. Using codispersion analysis to quantify and understand spatial patterns in species-environment relationships.

    PubMed

    Buckley, Hannah L; Case, Bradley S; Zimmerman, Jess K; Thompson, Jill; Myers, Jonathan A; Ellison, Aaron M

    2016-07-01

    The analysis of spatial patterns in species-environment relationships can provide new insights into the niche requirements and potential co-occurrence of species, but species abundance and environmental data are routinely collected at different spatial scales. Here, we investigate the use of codispersion analysis to measure and assess the scale, directionality and significance of complex relationships between plants and their environment in large forest plots. We applied codispersion analysis to both simulated and field data on spatially located tree species basal area and environmental variables. The significance of the observed bivariate spatial associations between the basal area of key species and underlying environmental variables was tested using three null models. Codispersion analysis reliably detected directionality (anisotropy) in bivariate species-environment relationships and identified relevant scales of effects. Null model-based significance tests applied to codispersion analyses of forest plot data enabled us to infer the extent to which environmental conditions, tree sizes and/or tree spatial positions underpinned the observed basal area-environment relationships, or whether relationships were a result of other unmeasured factors. Codispersion analysis, combined with appropriate null models, can be used to infer hypothesized ecological processes from spatial patterns, allowing us to start disentangling the possible drivers of plant species-environment relationships.

  11. Using codispersion analysis to quantify and understand spatial patterns in species-environment relationships.

    PubMed

    Buckley, Hannah L; Case, Bradley S; Zimmerman, Jess K; Thompson, Jill; Myers, Jonathan A; Ellison, Aaron M

    2016-07-01

    The analysis of spatial patterns in species-environment relationships can provide new insights into the niche requirements and potential co-occurrence of species, but species abundance and environmental data are routinely collected at different spatial scales. Here, we investigate the use of codispersion analysis to measure and assess the scale, directionality and significance of complex relationships between plants and their environment in large forest plots. We applied codispersion analysis to both simulated and field data on spatially located tree species basal area and environmental variables. The significance of the observed bivariate spatial associations between the basal area of key species and underlying environmental variables was tested using three null models. Codispersion analysis reliably detected directionality (anisotropy) in bivariate species-environment relationships and identified relevant scales of effects. Null model-based significance tests applied to codispersion analyses of forest plot data enabled us to infer the extent to which environmental conditions, tree sizes and/or tree spatial positions underpinned the observed basal area-environment relationships, or whether relationships were a result of other unmeasured factors. Codispersion analysis, combined with appropriate null models, can be used to infer hypothesized ecological processes from spatial patterns, allowing us to start disentangling the possible drivers of plant species-environment relationships. PMID:27037819

  12. Dynamics of land change in India: a fine-scale spatial analysis

    NASA Astrophysics Data System (ADS)

    Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.

    2015-12-01

    Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.

  13. Ontology Driven Analysis of Spatio-temporal Phenomena, Aimed At Spatial Planning And Environmental Forecasting

    NASA Astrophysics Data System (ADS)

    Iwaniak, A.; Łukowicz, J.; Strzelecki, M.; Kaczmarek, I.

    2013-10-01

    Spatial planning is a crucial area for balancing civilization development with environmental protection. Spatial planning has a multidisciplinary nature. It must take into account the dynamics of the processes, which could affect the integrity of the environmental system. That is why we need a new approach to modelling phenomena occurring in space. Such approach is offered by ontologies, based on Description Logic (DL) and related to inference systems. Ontology is a system for the knowledge representation, including conceptual scheme and based on this scheme representation of reality. Ontologies can be enriched with additional logical systems. The authors present a way of building domain ontologies for spatial planning, including the representation of spatio-temporal phenomena. Description Logic is supplemented by structures of temporal logic. As a result, the analysis for exploring the topological relations between spatial objects will be extended to include temporal relationships: coincidence, precedence and succession, cause and effect relationship. Spatio-temporal models with temporal logic structures, encoded in ontologies, could be a subject of inference process, performed by semantic reasoners (reasoner engines). Spatio-temporal representations are offered, by so-called upper ontologies, such as GFO, BFO, OCHRE and others. Temporal structures provided in such ontologies, are useful for the analysis of data obtained from environmental and development monitoring systems and for description and representation of historical phenomena. They allow creating the models and scenarios of expected spatial transformation. They will support analysis for spatial development design, decision-making in spatial planning and forecasting of environmental impact.

  14. Recent advances in (soil moisture) triple collocation analysis

    NASA Astrophysics Data System (ADS)

    Gruber, A.; Su, C.-H.; Zwieback, S.; Crow, W.; Dorigo, W.; Wagner, W.

    2016-03-01

    To date, triple collocation (TC) analysis is one of the most important methods for the global-scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method. Different notations that are used to formulate the TC problem are shown to be mathematically identical. While many studies have investigated issues related to possible violations of the underlying assumptions, only few TC modifications have been proposed to mitigate the impact of these violations. Moreover, assumptions, which are often understood as a limitation that is unique to TC analysis are shown to be common also to other conventional performance metrics. Noteworthy advances in TC analysis have been made in the way error estimates are being presented by moving from the investigation of absolute error variance estimates to the investigation of signal-to-noise ratio (SNR) metrics. Here we review existing error presentations and propose the combined investigation of the SNR (expressed in logarithmic units), the unscaled error variances, and the soil moisture sensitivities of the data sets as an optimal strategy for the evaluation of remotely-sensed soil moisture data sets.

  15. Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis

    PubMed Central

    Zipf, Alexander

    2016-01-01

    Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

  16. Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

    PubMed

    Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

    2016-01-01

    Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.

  17. Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

    PubMed Central

    2012-01-01

    Background Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e.g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our

  18. Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

    PubMed

    Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

    2016-01-01

    Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

  19. Violence, drug markets and racial composition: challenging stereotypes through spatial analysis.

    PubMed

    Lum, Cynthia

    2011-01-01

    Places in which there is a strong spatial connection between violence and drug activity can often evoke particular stereotypes. They are believed to be places marked by high levels of social disorganisation, unemployment, disorder and racial heterogeneity. Yet scholars have argued that the spatial relationship between drug market activity and violence is more complicated and that other factors may explain this geographical connection. In the first article of this two-part series, different types of spatial analysis were employed to describe crime concentrations of drugs and violence. Evidence was found that challenges the notion that places with drug activity are inevitably more violent. This second paper examines what factors predict these variations in drug–violence spatial patterns in Seattle when derived using different spatial methods. The findings indicate that racial composition, disorder and unemployment may not be as salient as once believed in predicting places that are violent drug markets. PMID:22165156

  20. Probabilistic seismic demand analysis using advanced ground motion intensity measures

    USGS Publications Warehouse

    Tothong, P.; Luco, N.

    2007-01-01

    One of the objectives in performance-based earthquake engineering is to quantify the seismic reliability of a structure at a site. For that purpose, probabilistic seismic demand analysis (PSDA) is used as a tool to estimate the mean annual frequency of exceeding a specified value of a structural demand parameter (e.g. interstorey drift). This paper compares and contrasts the use, in PSDA, of certain advanced scalar versus vector and conventional scalar ground motion intensity measures (IMs). One of the benefits of using a well-chosen IM is that more accurate evaluations of seismic performance are achieved without the need to perform detailed ground motion record selection for the nonlinear dynamic structural analyses involved in PSDA (e.g. record selection with respect to seismic parameters such as earthquake magnitude, source-to-site distance, and ground motion epsilon). For structural demands that are dominated by a first mode of vibration, using inelastic spectral displacement (Sdi) can be advantageous relative to the conventionally used elastic spectral acceleration (Sa) and the vector IM consisting of Sa and epsilon (??). This paper demonstrates that this is true for ordinary and for near-source pulse-like earthquake records. The latter ground motions cannot be adequately characterized by either Sa alone or the vector of Sa and ??. For structural demands with significant higher-mode contributions (under either of the two types of ground motions), even Sdi (alone) is not sufficient, so an advanced scalar IM that additionally incorporates higher modes is used.

  1. Recent advances in computational structural reliability analysis methods

    NASA Technical Reports Server (NTRS)

    Thacker, Ben H.; Wu, Y.-T.; Millwater, Harry R.; Torng, Tony Y.; Riha, David S.

    1993-01-01

    The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

  2. Identifying Naturally Occurring Retirement Communities: A Spatial Analysis

    PubMed Central

    Rivera-Hernandez, Maricruz; Yamashita, Takashi; Kinney, Jennifer M.

    2016-01-01

    Objectives Guided by the concept of “aging in place” and potential policy implications, the study analyzed naturally occurring retirement communities (NORCs; 40% or greater house owners and renters aged 65 years and older) and whether there were spatiotemporal patterns in Ohio between 2000 and 2010. Method Data were derived from the 2000 and 2010 census tracts. Geovisualization was used to visually examine the distribution of NORCs in 2000 and 2010. Global Moran’s I was used to quantify the spatial distribution of NORCs in Ohio and Local Moran’s I was used to identify clusters of NORCs (i.e., hot spots). Results The number of NORCs slightly decreased despite the overall increase of the older population from 2000 to 2010. NORCs were identified in one of the 3 most populous counties (i.e., Cuyahoga) and its neighboring counties. A number of hot spots were identified in Cuyahoga County (among Ohio’s most populous and NORC-rich counties), both in 2000 and 2010. There were different patterns including emerging, disappearing, and enduring NORCs and disproportionate distributions of NORCs across the state between 2000 and 2010. Discussion Locating NORCs could aid governments to create “aging in place” sensitive policies to address issues of independence, social care, health care, volunteerism, and community participation. PMID:24958694

  3. Spatial analysis of harmonic oscillation of gypsy moth outbreak intensity.

    PubMed

    Haynes, Kyle J; Liebhold, Andrew M; Johnson, Derek M

    2009-03-01

    Outbreaks of many forest-defoliating insects are synchronous over broad geographic areas and occur with a period of approximately 10 years. Within the range of the gypsy moth in North America, however, there is considerable geographic heterogeneity in strength of periodicity and the frequency of outbreaks. Furthermore, gypsy moth outbreaks exhibit two significant periodicities: a dominant period of 8-10 years and a subdominant period of 4-5 years. In this study, we used a simulation model and spatially referenced time series of outbreak intensity data from the Northeastern United States to show that the bimodal periodicity in the intensity of gypsy moth outbreaks is largely a result of harmonic oscillations in gypsy moth abundance at and above a 4 km(2) scale of resolution. We also used geographically weighted regression models to explore the effects of gypsy moth host-tree abundance on the periodicity of gypsy moths. We found that the strength of 5-year cycles increased relative to the strength of 10-year cycles with increasing host tree abundance. We suggest that this pattern emerges because high host-tree availability enhances the growth rates of gypsy moth populations.

  4. Utilizing Exploratory Spatial Data Analysis to Examine Health and Environmental Disparities in Disadvantaged Neighborhoods

    PubMed Central

    Osiecki, Kristin M.; Kim, Seijeoung; Chukwudozie, Ifeanyi B.; Calhoun, Elizabeth A.

    2013-01-01

    Health disparities research has focused primarily on racial and socioeconomic differences in health outcomes. Although neighborhood characteristics and the concept of built environment have been shown to affect individual health, measuring the effects of environmental risks on health has been a less developed area of disparities research. To examine spatial associations and the distribution of geographic patterns of sociodemographic characteristics, environmental cancer risk, and cancer rates, we utilized existing data from multiple sources. The findings from our initial analysis, which concerned with proximity to environmental hazards and at-risk communities, were consistent with results of previous studies, which often reported mixed relationships between health disparity indicators and environmental burden. However, further analysis with refined models showed that several key demographic and subdomains of cancer risk measures were shown to have spatial components. With the application of exploratory spatial data analysis, we were able to identify areas with both high rates of poverty and racial minorities to further examine for possible associations to environmental cancer risk. Global spatial autocorrelation found spatial clustering with percent black, percent poverty, point and non-point cancer risks requiring further spatial analysis to determine relationship of significance based on geography. This methodology was based upon particular assumptions associated with data and applications, which needed to be met. We conclude that careful assessment of the data and applications were required to properly interpret the findings in understanding the relationship between vulnerable populations and environmental burden. PMID:26594302

  5. Using advanced dispersion models and mobile monitoring to characterize spatial patterns of ultrafine particles in an urban area

    NASA Astrophysics Data System (ADS)

    Zwack, Leonard M.; Hanna, Steven R.; Spengler, John D.; Levy, Jonathan I.

    2011-09-01

    In urban settings with elevated bridges, buildings, and other complex terrain, the relationship between traffic and air pollution can be highly variable and difficult to accurately characterize. Atmospheric dispersion models are often used in this context, but incorporating background concentrations and characterizing emissions at high spatiotemporal resolution is challenging, especially for ultrafine particles (UFPs). Ambient pollutant monitoring can characterize this relationship, especially when using continuous real-time monitoring. However, it is challenging to quantify local source contributions over background or to characterize spatial patterns across a neighborhood. The goal of this study is to evaluate contributions of traffic to neighborhood-scale air pollution using a combination of regression models derived from mobile UFP monitoring observations collected in Brooklyn, NY and outputs from the Quick Urban & Industrial Complex (QUIC) model. QUIC is a dispersion model that can explicitly take into account the three-dimensional shapes of buildings. The monitoring-based regression model characterized concentration gradients from a major elevated roadway, controlling for real-time traffic volume, meteorological variables, and other local sources. QUIC was applied to simulate dispersion from this same major roadway. The relative concentration decreases with distance from the roadway estimated by the monitoring-based regression model after removal of background and by QUIC were similar. Horizontal contour plots with both models demonstrated non-uniform patterns related to building configuration and source heights. We used the best-fit relationship between the monitoring-based regression model after removal of background and the QUIC outputs ( R2 = 0.80) to estimate a UFP emissions factor of 5.7 × 10 14 particles/vehicle-km, which was relatively consistent across key model assumptions. Our joint applications of novel techniques for analyzing mobile monitoring

  6. Beam Optics Analysis - An Advanced 3D Trajectory Code

    SciTech Connect

    Ives, R. Lawrence; Bui, Thuc; Vogler, William; Neilson, Jeff; Read, Mike; Shephard, Mark; Bauer, Andrew; Datta, Dibyendu; Beal, Mark

    2006-01-03

    Calabazas Creek Research, Inc. has completed initial development of an advanced, 3D program for modeling electron trajectories in electromagnetic fields. The code is being used to design complex guns and collectors. Beam Optics Analysis (BOA) is a fully relativistic, charged particle code using adaptive, finite element meshing. Geometrical input is imported from CAD programs generating ACIS-formatted files. Parametric data is inputted using an intuitive, graphical user interface (GUI), which also provides control of convergence, accuracy, and post processing. The program includes a magnetic field solver, and magnetic information can be imported from Maxwell 2D/3D and other programs. The program supports thermionic emission and injected beams. Secondary electron emission is also supported, including multiple generations. Work on field emission is in progress as well as implementation of computer optimization of both the geometry and operating parameters. The principle features of the program and its capabilities are presented.

  7. Advanced functional network analysis in the geosciences: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  8. Thermodynamic analysis of the advanced zero emission power plant

    NASA Astrophysics Data System (ADS)

    Kotowicz, Janusz; Job, Marcin

    2016-03-01

    The paper presents the structure and parameters of advanced zero emission power plant (AZEP). This concept is based on the replacement of the combustion chamber in a gas turbine by the membrane reactor. The reactor has three basic functions: (i) oxygen separation from the air through the membrane, (ii) combustion of the fuel, and (iii) heat transfer to heat the oxygen-depleted air. In the discussed unit hot depleted air is expanded in a turbine and further feeds a bottoming steam cycle (BSC) through the main heat recovery steam generator (HRSG). Flue gas leaving the membrane reactor feeds the second HRSG. The flue gas consist mainly of CO2 and water vapor, thus, CO2 separation involves only the flue gas drying. Results of the thermodynamic analysis of described power plant are presented.

  9. Beam Optics Analysis — An Advanced 3D Trajectory Code

    NASA Astrophysics Data System (ADS)

    Ives, R. Lawrence; Bui, Thuc; Vogler, William; Neilson, Jeff; Read, Mike; Shephard, Mark; Bauer, Andrew; Datta, Dibyendu; Beal, Mark

    2006-01-01

    Calabazas Creek Research, Inc. has completed initial development of an advanced, 3D program for modeling electron trajectories in electromagnetic fields. The code is being used to design complex guns and collectors. Beam Optics Analysis (BOA) is a fully relativistic, charged particle code using adaptive, finite element meshing. Geometrical input is imported from CAD programs generating ACIS-formatted files. Parametric data is inputted using an intuitive, graphical user interface (GUI), which also provides control of convergence, accuracy, and post processing. The program includes a magnetic field solver, and magnetic information can be imported from Maxwell 2D/3D and other programs. The program supports thermionic emission and injected beams. Secondary electron emission is also supported, including multiple generations. Work on field emission is in progress as well as implementation of computer optimization of both the geometry and operating parameters. The principle features of the program and its capabilities are presented.

  10. Advanced Neutron Source Reactor thermal analysis of fuel plate defects

    SciTech Connect

    Giles, G.E.

    1995-08-01

    The Advanced Neutron Source Reactor (ANSR) is a research reactor designed to provide the highest continuous neutron beam intensity of any reactor in the world. The present technology for determining safe operations were developed for the High Flux Isotope Reactor (HFIR). These techniques are conservative and provide confidence in the safe operation of HFIR. However, the more intense requirements of ANSR necessitate the development of more accurate, but still conservative, techniques. This report details the development of a Local Analysis Technique (LAT) that provides an appropriate approach. Application of the LAT to two ANSR core designs are presented. New theories of the thermal and nuclear behavior of the U{sub 3}Si{sub 2} fuel are utilized. The implications of lower fuel enrichment and of modifying the inspection procedures are also discussed. Development of the computer codes that enable the automate execution of the LAT is included.

  11. Advanced XAS Analysis for Investigating Fuel Cell Electrocatalysts

    SciTech Connect

    Witkowska, Agnieszka; Principi, Emiliano; Di Cicco, Andrea; Marassi, Roberto

    2007-02-02

    In the paper we present an accurate structural study of a Pt-based electrode by means of XAS, accounting for both the catalytic nanoparticles size distribution and sample inhomogeneities. Morphology and size distribution of the nanoparticles were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction techniques. XAS data-analysis was performed using advanced multiple-scattering techniques (GNXAS), disentangling possible effects due to surface atom contributions in nanoparticles and sample homogeneity, contributing to a reduction of intensity of the structural signal. This approach for XAS investigation of electrodes of FC devices can represent a viable and reliable way to understand structural details, important for producing more efficient catalytic materials.

  12. Systems analysis and futuristic designs of advanced biofuel factory concepts.

    SciTech Connect

    Chianelli, Russ; Leathers, James; Thoma, Steven George; Celina, Mathias Christopher; Gupta, Vipin P.

    2007-10-01

    The U.S. is addicted to petroleum--a dependency that periodically shocks the economy, compromises national security, and adversely affects the environment. If liquid fuels remain the main energy source for U.S. transportation for the foreseeable future, the system solution is the production of new liquid fuels that can directly displace diesel and gasoline. This study focuses on advanced concepts for biofuel factory production, describing three design concepts: biopetroleum, biodiesel, and higher alcohols. A general schematic is illustrated for each concept with technical description and analysis for each factory design. Looking beyond current biofuel pursuits by industry, this study explores unconventional feedstocks (e.g., extremophiles), out-of-favor reaction processes (e.g., radiation-induced catalytic cracking), and production of new fuel sources traditionally deemed undesirable (e.g., fusel oils). These concepts lay the foundation and path for future basic science and applied engineering to displace petroleum as a transportation energy source for good.

  13. Aeroelastic analysis of advanced propellers using an efficient Euler solver

    NASA Technical Reports Server (NTRS)

    Srivastava, R.; Reddy, T. S. R.; Mehmed, O.

    1992-01-01

    A 3D Euler solver is coupled with a 3D structural dynamics model to investigate flutter of propfans. A hybrid scheme is used to reduce computational time for the Euler equations and a normal mode analysis is used for flutter calculations. Experimental and calculated flutter results are compared for an advanced propeller propfan which experienced flutter at transonic tip relative velocities. The predicted flutter calculations are in close agreement with the experimental data. A structural damping value of 0.5 percent was required to predict the behavior observed in the experiment. Computations show that the flutter behavior is dominated by the second mode, but coupling with the first mode is required. The addition of other modes to the calculations did not affect the flutter behavior.

  14. Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

    NASA Technical Reports Server (NTRS)

    Berry, J. K.; Tomlin, C. D.

    1982-01-01

    Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

  15. Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

    NASA Astrophysics Data System (ADS)

    Berezowski, T.; Nossent, J.; Chormański, J.; Batelaan, O.

    2014-10-01

    As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly growing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis (SA) method for snow cover fraction input data (SCF) for a distributed rainfall-runoff model to investigate if the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focused on the relation between the SCF sensitivity and the physical, spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland for which a distributed WetSpa model is setup to simulate two years of daily runoff. The SA uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which uses different response functions for each 4 km × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as: geomorphology, soil texture, land-use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for the spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model.

  16. Advanced in aerospace lubricant and wear metal analysis

    SciTech Connect

    Saba, C.S.; Centers, P.W.

    1995-09-01

    Wear metal analysis continues to play an effective diagnostic role for condition monitoring of gas turbine engines. Since the early 1960s the United States` military services have been using spectrometric oil analysis program (SOAP) to monitor the condition of aircraft engines. The SOAP has proven to be effective in increasing reliability, fleet readiness and avoiding losses of lives and machinery. Even though historical data have demonstrated the success of the SOAP in terms of detecting imminent engine failure verified by maintenance personnel, the SOAP is not a stand-alone technique and is limited in its detection of large metallic wear debris. In response, improved laboratory, portable, in-line and on-line diagnostic techniques to perfect SOAP and oil condition monitoring have been sought. The status of research and development as well as the direction of future developmental activities in oil analysis due to technological opportunities, advanced in engine development and changes in military mission are reviewed and discussed. 54 refs.

  17. Integration of Spatial and Social Network Analysis in Disease Transmission Studies

    PubMed Central

    Root, Elisabeth D; Giebultowicz, Sophia; Ali, Mohammad; Perez-Heydrich, Carolina; Yunus, Mohammad

    2013-01-01

    This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The paper first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database which consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties between households using a complete network design and distance matrices are also created to model spatial relationships. Moran's I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects-spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always clusters in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases however kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study has offered several strategies on how. PMID:24163443

  18. Ultrafast laser induced breakdown spectroscopy for high spatial resolution chemical analysis

    NASA Astrophysics Data System (ADS)

    Zorba, Vassilia; Mao, Xianglei; Russo, Richard E.

    2011-02-01

    Femtosecond laser induced breakdown spectroscopy (LIBS) was used to identify the spatial resolution limitations and assess the minimal detectable mass restrictions in laser-ablation based chemical analysis. The atomic emission of sodium (Na) and potassium (K) dopants in transparent dielectric Mica matrices was studied, to find that both these elements could be detected from 450 nm diameter ablation craters, full-width-at-half-maximum (FWHM). Under optimal conditions, mass as low as 220 ag was measured, demonstrating the feasibility of using laser-ablation based chemical analysis to achieve high spatial resolution elemental analysis in real-time and at atmospheric pressure conditions.

  19. Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

    PubMed Central

    Chu, Hone-Jay; Lin, Yu-Pin; Huang, Yu-Long; Wang, Yung-Chieh

    2009-01-01

    The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS), sequential Gaussian simulation (SGS) and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI) images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE). Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management. PMID:22399972

  20. Detecting the land-cover changes induced by large-physical disturbances using landscape metrics, spatial sampling, simulation and spatial analysis.

    PubMed

    Chu, Hone-Jay; Lin, Yu-Pin; Huang, Yu-Long; Wang, Yung-Chieh

    2009-01-01

    The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS), sequential Gaussian simulation (SGS) and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran'I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI) images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE). Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management. PMID:22399972

  1. [Application of spatial autocorrelation analysis to the COD, SO2 and TSP emission in Jiangsu province].

    PubMed

    Zhao, Xiao-Feng; Huang, Xian-Jin; Zhang, Xing-Yu; Zhu, De-Ming; Lai, Li; Zhong, Tai-Yang

    2009-06-15

    Spatial autocorrelation is an effective tool of spatial statistics, which is used to disclose the spatial structure of regional disparity. There are two different scales to measure regional spatial dependence: global spatial autocorrelation and local spatial autocorrelation. Based on environmental data of 13 cities in Jiangsu province from 1990 to 2006, the regional disparity of COD, SO2 and TSP emission was discussed by using spatial autocorrelation analysis methods. The results show that total emission of COD and TSP decreased respectively from 596 353 t and 1 101 404 t in 1990 to 291 762 t and 704734 t in 2006, while total emission of SO2 kept steady. In 2006, Global Moran's I of COD, SO2 and TSP emission was 0.465 7, 0.214 2 and 0.510 1 respectively. It is identified that positive spatial autocorrelation is presented and spatial aggregation pattern of COD, SO2 and TSP emission are appeared. However, spatial aggregation pattern of COD emission appears earlier than that of SO2 and TSP, and spatial aggregation degree of COD is also higher than that of SO2 and TSP. There are different spatial patterns between southern and northern Jiangsu. In southern Jiangsu, Global Moran's I of COD, SO2 and TSP emission had increased to 0.499 7, 0.320 2 and 0.298 3 up to 2006, and spatial aggregation pattern appeared remarkably. In northern Jiangsu, most of the Global Moran's I were less than -0.2, and spatial aggregation pattern disappeared accordingly. High cluster region of COD emission is Suzhou, Wuxi and Changzhou, and high cluster region of SO2 emission is Suzhou and Wuxi. However, spatial pattern of TSP emission does not change much and five cities of southern Jiangsu (Suzhou, Wuxi, Changzhou, Zhenjiang, Nanjing) are still the high cluster region. The last, the research provides an important cognition to regional environment disparity and macro-environmental strategy, and a significant means to harmonious society and eco-province construction in Jiangsu province.

  2. An exploratory spatial analysis of soil organic carbon distribution in Canadian eco-regions

    NASA Astrophysics Data System (ADS)

    Tan, S.-Y.; Li, J.

    2014-11-01

    As the largest carbon reservoir in ecosystems, soil accounts for more than twice as much carbon storage as that of vegetation biomass or the atmosphere. This paper examines spatial patterns of soil organic carbon (SOC) in Canadian forest areas at an eco-region scale of analysis. The goal is to explore the relationship of SOC levels with various climatological variables, including temperature and precipitation. The first Canadian forest soil database published in 1997 by the Canada Forest Service was analyzed along with other long-term eco-climatic data (1961 to 1991) including precipitation, air temperature, slope, aspect, elevation, and Normalized Difference Vegetation Index (NDVI) derived from remote sensing imagery. In addition, the existing eco-region framework established by Environment Canada was evaluated for mapping SOC distribution. Exploratory spatial data analysis techniques, including spatial autocorrelation analysis, were employed to examine how forest SOC is spatially distributed in Canada. Correlation analysis and spatial regression modelling were applied to determine the dominant ecological factors influencing SOC patterns at the eco-region level. At the national scale, a spatial error regression model was developed to account for spatial dependency and to estimate SOC patterns based on ecological and ecosystem factors. Based on the significant variables derived from the spatial error model, a predictive SOC map in Canadian forest areas was generated. Although overall SOC distribution is influenced by climatic and topographic variables, distribution patterns are shown to differ significantly between eco-regions. These findings help to validate the eco-region classification framework for SOC zonation mapping in Canada.

  3. An Analysis of Spatial Configuration and its Application to Research in Higher Education.

    ERIC Educational Resources Information Center

    Cole, Nancy S.; Cole, James W. L.

    This paper presents an analysis of the spatial configuration of variables in a multivariate system. The purpose of the analysis is to make clearer the relationships among the variables by locating them in a minimally-dimensioned space. Similarly, individuals are located in the smaller space and related to each other on the basis of the variables…

  4. Analysis of obstruction reason of urban sewer using spatial association rules

    NASA Astrophysics Data System (ADS)

    Zhu, Hongmei; Luo, Yu

    2009-10-01

    Sewerage network is an important part of municipal infrastructure for a city. Obstruction of sewer causes street flooding and affects people's daily life directly. To investigate reasons why some sewage pipes are blocked frequently in Kunming, China, we employ spatial analysis and data mining technology to analyze the data on the basis of a municipal sewerage geographic information system of the city. In the GIS, all of map layers and attribute tables are organized and saved in a relational database with Geodatabase model. First, we combined SQL attribute query with spatial location query to find out the sewage pipes that are blocked frequently. Then, we carried out buffer analysis and intersect analysis on the layers of the frequently-blocked pipes and buildings along the streets to extract buildings that are close to these frequently-blocked pipes. Joining the buildings in the buffer scope and the frequently-blocked pipes forms a big table prepared for spatial data mining. We used Apriori algorithm to mine spatial association rules from the data in the big table in order to search implicit reasons of obstruction of the pipes. The results from data mining indicate that strong spatial and non-spatial associate rules exist between the obstruction and restaurants in the buildings, as well as attribute slopes and diameters of these sewage pipes.

  5. Spatial Characterization of Landscapes through Multifractal Analysis of DEM

    PubMed Central

    Aguado, P. L.; Del Monte, J. P.; Moratiel, R.; Tarquis, A. M.

    2014-01-01

    Landscape evolution is driven by abiotic, biotic, and anthropic factors. The interactions among these factors and their influence at different scales create a complex dynamic. Landscapes have been shown to exhibit numerous scaling laws, from Horton's laws to more sophisticated scaling of heights in topography and river network topology. This scaling and multiscaling analysis has the potential to characterise the landscape in terms of the statistical signature of the measure selected. The study zone is a matrix obtained from a digital elevation model (DEM) (map 10 × 10 m, and height 1 m) that corresponds to homogeneous region with respect to soil characteristics and climatology known as “Monte El Pardo” although the water level of a reservoir and the topography play a main role on its organization and evolution. We have investigated whether the multifractal analysis of a DEM shows common features that can be used to reveal the underlying patterns and information associated with the landscape of the DEM mapping and studied the influence of the water level of the reservoir on the applied analysis. The results show that the use of the multifractal approach with mean absolute gradient data is a useful tool for analysing the topography represented by the DEM. PMID:25177728

  6. Advanced High Temperature Reactor Systems and Economic Analysis

    SciTech Connect

    Holcomb, David Eugene; Peretz, Fred J; Qualls, A L

    2011-09-01

    The Advanced High Temperature Reactor (AHTR) is a design concept for a large-output [3400 MW(t)] fluoride-salt-cooled high-temperature reactor (FHR). FHRs, by definition, feature low-pressure liquid fluoride salt cooling, coated-particle fuel, a high-temperature power cycle, and fully passive decay heat rejection. The AHTR's large thermal output enables direct comparison of its performance and requirements with other high output reactor concepts. As high-temperature plants, FHRs can support either high-efficiency electricity generation or industrial process heat production. The AHTR analysis presented in this report is limited to the electricity generation mission. FHRs, in principle, have the potential to be low-cost electricity producers while maintaining full passive safety. However, no FHR has been built, and no FHR design has reached the stage of maturity where realistic economic analysis can be performed. The system design effort described in this report represents early steps along the design path toward being able to predict the cost and performance characteristics of the AHTR as well as toward being able to identify the technology developments necessary to build an FHR power plant. While FHRs represent a distinct reactor class, they inherit desirable attributes from other thermal power plants whose characteristics can be studied to provide general guidance on plant configuration, anticipated performance, and costs. Molten salt reactors provide experience on the materials, procedures, and components necessary to use liquid fluoride salts. Liquid metal reactors provide design experience on using low-pressure liquid coolants, passive decay heat removal, and hot refueling. High temperature gas-cooled reactors provide experience with coated particle fuel and graphite components. Light water reactors (LWRs) show the potentials of transparent, high-heat capacity coolants with low chemical reactivity. Modern coal-fired power plants provide design experience with

  7. Lock Acquisition and Sensitivity Analysis of Advanced LIGO Interferometers

    NASA Astrophysics Data System (ADS)

    Martynov, Denis

    Laser interferometer gravitational wave observatory (LIGO) consists of two complex large-scale laser interferometers designed for direct detection of gravitational waves from distant astrophysical sources in the frequency range 10Hz - 5kHz. Direct detection of space-time ripples will support Einstein's general theory of relativity and provide invaluable information and new insight into physics of the Universe. The initial phase of LIGO started in 2002, and since then data was collected during the six science runs. Instrument sensitivity improved from run to run due to the effort of commissioning team. Initial LIGO has reached designed sensitivity during the last science run, which ended in October 2010. In parallel with commissioning and data analysis with the initial detector, LIGO group worked on research and development of the next generation of detectors. Major instrument upgrade from initial to advanced LIGO started in 2010 and lasted until 2014. This thesis describes results of commissioning work done at the LIGO Livingston site from 2013 until 2015 in parallel with and after the installation of the instrument. This thesis also discusses new techniques and tools developed at the 40m prototype including adaptive filtering, estimation of quantization noise in digital filters and design of isolation kits for ground seismometers. The first part of this thesis is devoted to the description of methods for bringing the interferometer into linear regime when collection of data becomes possible. States of longitudinal and angular controls of interferometer degrees of freedom during lock acquisition process and in low noise configuration are discussed in details. Once interferometer is locked and transitioned to low noise regime, instrument produces astrophysics data that should be calibrated to units of meters or strain. The second part of this thesis describes online calibration technique set up in both observatories to monitor the quality of the collected data in

  8. Inside Single Cells: Quantitative Analysis with Advanced Optics and Nanomaterials

    PubMed Central

    Cui, Yi; Irudayaraj, Joseph

    2014-01-01

    Single cell explorations offer a unique window to inspect molecules and events relevant to mechanisms and heterogeneity constituting the central dogma of biology. A large number of nucleic acids, proteins, metabolites and small molecules are involved in determining and fine-tuning the state and function of a single cell at a given time point. Advanced optical platforms and nanotools provide tremendous opportunities to probe intracellular components with single-molecule accuracy, as well as promising tools to adjust single cell activity. In order to obtain quantitative information (e.g. molecular quantity, kinetics and stoichiometry) within an intact cell, achieving the observation with comparable spatiotemporal resolution is a challenge. For single cell studies both the method of detection and the biocompatibility are critical factors as they determine the feasibility, especially when considering live cell analysis. Although a considerable proportion of single cell methodologies depend on specialized expertise and expensive instruments, it is our expectation that the information content and implication will outweigh the costs given the impact on life science enabled by single cell analysis. PMID:25430077

  9. Quantitative Computed Tomography and Image Analysis for Advanced Muscle Assessment

    PubMed Central

    Edmunds, Kyle Joseph; Gíslason, Magnus K.; Arnadottir, Iris D.; Marcante, Andrea; Piccione, Francesco; Gargiulo, Paolo

    2016-01-01

    Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration. PMID:27478562

  10. DSA hole defectivity analysis using advanced optical inspection tool

    NASA Astrophysics Data System (ADS)

    Harukawa, Ryota; Aoki, Masami; Cross, Andrew; Nagaswami, Venkat; Tomita, Tadatoshi; Nagahara, Seiji; Muramatsu, Makoto; Kawakami, Shinichiro; Kosugi, Hitoshi; Rathsack, Benjamen; Kitano, Takahiro; Sweis, Jason; Mokhberi, Ali

    2013-04-01

    This paper discusses the defect density detection and analysis methodology using advanced optical wafer inspection capability to enable accelerated development of a DSA process/process tools and the required inspection capability to monitor such a process. The defectivity inspection methodologies are optimized for grapho epitaxy directed self-assembly (DSA) contact holes with 25 nm sizes. A defect test reticle with programmed defects on guide patterns is designed for improved optimization of defectivity monitoring. Using this reticle, resist guide holes with a variety of sizes and shapes are patterned using an ArF immersion scanner. The negative tone development (NTD) type thermally stable resist guide is used for DSA of a polystyrene-b-poly(methyl methacrylate) (PS-b-PMMA) block copolymer (BCP). Using a variety of defects intentionally made by changing guide pattern sizes, the detection rates of each specific defectivity type has been analyzed. It is found in this work that to maximize sensitivity, a two pass scan with bright field (BF) and dark field (DF) modes provides the best overall defect type coverage and sensitivity. The performance of the two pass scan with BF and DF modes is also revealed by defect analysis for baseline defectivity on a wafer processed with nominal process conditions.

  11. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances

    PubMed Central

    Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A.; Al-Khalifa, Hend S.

    2016-01-01

    In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906

  12. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

    PubMed

    Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A; Al-Khalifa, Hend S

    2016-05-16

    In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.

  13. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

    PubMed

    Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A; Al-Khalifa, Hend S

    2016-01-01

    In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906

  14. Rescaled box counting for the topological analysis of spatial data

    SciTech Connect

    Loehle, C.

    1994-04-01

    Topological analysis of surfaces of natural objects can provide information about surface features (ridges, fragmentation, dendritic patterns) and surface roughness. Box counting is a general method useful for such surfaces, but it is currently limited to cases where the x, y, and z directions are all in the same metric. A method, rescaled box counting, is presented for overcoming these limitations. The local first omnidirectional semivariance (lag 1) is calculated for boxes of different sizes. If the semivariance is not small for small box sizes, then the z data need to be scaled up to allow detection of a difference between patches that are significantly different This rescaling converts the z metric into a distance equivalent (z units are converted into distances based on the horizontal distance over which a significant change in z is found to occur). Once rescaling is done, box counting can be used to quantify surface topology.

  15. Advanced Diagnostic and Prognostic Testbed (ADAPT) Testability Analysis Report

    NASA Technical Reports Server (NTRS)

    Ossenfort, John

    2008-01-01

    As system designs become more complex, determining the best locations to add sensors and test points for the purpose of testing and monitoring these designs becomes more difficult. Not only must the designer take into consideration all real and potential faults of the system, he or she must also find efficient ways of detecting and isolating those faults. Because sensors and cabling take up valuable space and weight on a system, and given constraints on bandwidth and power, it is even more difficult to add sensors into these complex designs after the design has been completed. As a result, a number of software tools have been developed to assist the system designer in proper placement of these sensors during the system design phase of a project. One of the key functions provided by many of these software programs is a testability analysis of the system essentially an evaluation of how observable the system behavior is using available tests. During the design phase, testability metrics can help guide the designer in improving the inherent testability of the design. This may include adding, removing, or modifying tests; breaking up feedback loops, or changing the system to reduce fault propagation. Given a set of test requirements, the analysis can also help to verify that the system will meet those requirements. Of course, a testability analysis requires that a software model of the physical system is available. For the analysis to be most effective in guiding system design, this model should ideally be constructed in parallel with these efforts. The purpose of this paper is to present the final testability results of the Advanced Diagnostic and Prognostic Testbed (ADAPT) after the system model was completed. The tool chosen to build the model and to perform the testability analysis with is the Testability Engineering and Maintenance System Designer (TEAMS-Designer). The TEAMS toolset is intended to be a solution to span all phases of the system, from design and

  16. Develop advanced nonlinear signal analysis topographical mapping system

    NASA Technical Reports Server (NTRS)

    1994-01-01

    The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of

  17. Develop advanced nonlinear signal analysis topographical mapping system

    NASA Technical Reports Server (NTRS)

    Jong, Jen-Yi

    1993-01-01

    The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate

  18. Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis.

    PubMed

    Gopal, Shruti; Miller, Robyn L; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R; Cahill, Nathan; Baum, Stefi A; Calhoun, Vince D

    2016-01-01

    Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. PMID:26106217

  19. Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China

    PubMed Central

    Wang, Zhensheng; Du, Qingyun; Liang, Shi; Nie, Ke; Lin, De-nan; Chen, Yan; Li, Jia-jia

    2014-01-01

    In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China’s aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian models to explore the spatial heterogeneity of the relative risk for hypertension admissions throughout Shenzhen in 2011. The final model specification includes an intercept and spatial components (structured and unstructured). Although the road density could be used as a covariate in modeling, it is an indirect factor on the relative risk. In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters. The results showed that the relative risk for hospital admission for hypertension has high-value clusters in the south and southeastern Shenzhen. This study aimed to identify some specific regions with high relative risk, and this information is useful for the health administrators. Further research should address more-detailed data collection and an explanation of the spatial patterns. PMID:24394218

  20. Local frequency estimation from intensity gradients in spatial carrier fringe pattern analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Ruihua; Guo, Hongwei

    2016-06-01

    Spatial carrier fringe pattern analysis is an effective tool in optical measurement, e.g. in interferometry and fringe projection technique. With it, the very large phase deformations in a spatial carrier fringe pattern may increases the bandwidth of fringe component thus leading to difficulties in retrieving its phase map. In order to overcome this problem, many local-adaptive methods have been developed for processing the spatial carrier fringe pattern with large phase variations, and in fact, the local spatial frequency estimation is central to these methods. This paper introduces a simple algorithm for estimating the local frequencies of a fringe pattern with spatial carrier. First, the intensity gradients of the fringe pattern are calculated, and then the standard deviations (SDs) of the intensity gradients at each pixel are estimated from its neighborhood. Finally the local frequencies are estimated from the SDs just calculated simply using an arccosine function. This algorithm is potential in developing effective techniques for retrieving phases from a spatial carrier fringe pattern with large phase variations. For example, we can recover the phase map by directly integrating the local frequencies or by use of an adaptive spatial carrier phase shifting algorithm (SCPS) with the local frequencies being the local phase shifts. It can also be used in Fourier transform method for exactly determining the carrier frequencies, or for extrapolating aperture in order to reduce the boundary effect. Combined with time-frequency techniques such as windowed Fourier transform and wavelet transform methods, it is helpful for alleviating the computational burdens.

  1. Characterization of droughts using Copulas: frequency analysis and spatial patterns in Guangdong, China

    NASA Astrophysics Data System (ADS)

    Hua, Dong

    2016-04-01

    Droughts have repeatedly occurred over the past decades and have inflicted significant damage to human society and ecological environment. Therefore, it is of great significance to have a better understanding of the occurrence frequency and spatial patterns of droughts. This study carried out the univariate and bivariate frequency analysis of drought duration and severity using Copulas and investigated the spatial distributions of droughts based on the joint probability distribution in Guangdong province. The quartiles descriptive statistical approach and spatial interpolation was used to map the spatial frequency distribution for the marginal distribution and joint occurrence probability of drought duration and severity; Cluster analysis was employed to characterize the spatial pattern. Results show that drought properties in water rich regions have their own unique features so there might not be a best copula for a region but a best copula for a site; further analysis demonstrated that the Gumbel Copula outperformed marginally than Frank Copula in the relatively dry regions of Guangdong Province and may serve as a reference for Copulas selection for droughts in other humid regions; the quartiles descriptive statistical approach enables the comparisons of the risk of drought properties among the meteorological stations and allows recognition of the spatial distributions of droughts in a multi-scale way. Spatial patterns based on cluster analysis indicate that total precipitation is not the only factor that influences the drought occurrence for a certain region, the temporal uneven distribution of precipitation also plays an important role, which may provide valuable information for site selection for water conservancy projects.

  2. Adverse effects of template-based warping on spatial fMRI analysis

    NASA Astrophysics Data System (ADS)

    Ng, Bernard; Abugharbieh, Rafeef; McKeown, Martin J.

    2009-02-01

    Conventional voxel-based group analysis of functional magnetic resonance imaging (fMRI) data typically requires warping each subject's brain images onto a common template to create an assumed voxel correspondence. The implicit assumption is that aligning the anatomical structures would correspondingly align the functional regions of the subjects. However, due to anatomical and functional inter-subject variability, mis-registration often occurs. Moreover, wholebrain warping is likely to distort the spatial patterns of activation, which have been shown to be important markers of task-related activation. To reduce the amount of mis-registration and distortions, warping at the brain region level has recently been proposed. In this paper, we investigate the effects of both whole-brain and region-level warping on the spatial patterns of activation statistics within certain regions of interests (ROIs). We have chosen to examine the bilateral thalami and cerebellar hemispheres during a bulb-squeezing experiment, as these regions are expected to incur taskrelated activation changes. Furthermore, the appreciable size difference between the thalamus and cerebellum allows for exploring the effects of warping on various ROI sizes. By applying our recently proposed 3D moment-based invariant spatial features to characterize the spatial pattern of fMRI activation statistics, we demonstrate that whole-brain warping generally reduced discriminability of task-related activation differences. Applying the same spatial analysis to ROIs warped at the region level showed some improvements over whole-brain warping, but warp-free analysis resulted in the best performance. We hence suggest that spatial analysis of fMRI data that includes spatial warping to a common space must be interpreted with caution.

  3. Spherical harmonic decomposition applied to spatial-temporal analysis of human high-density electroencephalogram

    NASA Astrophysics Data System (ADS)

    Wingeier, B. M.; Nunez, P. L.; Silberstein, R. B.

    2001-11-01

    We demonstrate an application of spherical harmonic decomposition to the analysis of the human electroencephalogram (EEG). We implement two methods and discuss issues specific to the analysis of hemispherical, irregularly sampled data. Spatial sampling requirements and performance of the methods are quantified using simulated data. The analysis is applied to experimental EEG data, confirming earlier reports of an approximate frequency-wave-number relationship in some bands.

  4. Using principal component analysis to monitor spatial and temporal changes in water quality.

    PubMed

    Bengraïne, Karim; Marhaba, Taha F

    2003-06-27

    Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted. The spatial analysis isolated two stations showing a possible point or non-point source of pollution. This study shows the importance of environmental monitoring associated with simple but powerful statistics to better understand a complex water system. PMID:12835021

  5. Spatial Analysis of Cryoplanation Landforms in Beringian Uplands, Alaska, USA

    NASA Astrophysics Data System (ADS)

    Nyland, K. E.; Nelson, F. E.

    2015-12-01

    Cryoplanation terraces are large periglacial landforms characteristic of cold, unglaciated mountainous environments. Terrace sequences are composed of alternating slope segments with steep rubble-covered risers and gently sloping treads, culminating in extensive summit flats. Entire Beringian upland landscapes are dominated by these features. Cryoplanation terraces are cut into bedrock and thought to evolve through locally intensified periglacial weathering and mass-movement processes in the vicinity of late-lying snowpatches. Geospatial analysis demonstrates that terrace elevation rises from 100-300 m.a.s.l. on Bering Sea islands to median values greater than 1200 m in the Yukon-Tanana Upland, near the Alaska-Canada border. The regional trends of cryoplanation terrace elevation are similar to those of cirques and reconstructed ELAs across interior and western Alaska, with gradients ranging from 0.74 to 1.2 m km-1. The similarity of these trends indicates close genetic links between glacial cirques and cryoplanation terraces, involving topographic position, continentality gradients, and the mass balance of localized snow accumulation. Cryoplanation terraces can be considered as the periglacial analogs of glacial cirques, and have greater potential as sources of paleoclimatic information than smaller periglacial features more sensitive to short-term climate variations. Process-oriented studies, age determinations, and high-resolution mapping are needed before their paleoenvironmental potential of these landforms can be fully realized.

  6. Three-dimensional analysis of anisotropic spatially reinforced structures

    NASA Technical Reports Server (NTRS)

    Bogdanovich, Alexander E.

    1993-01-01

    The material-adaptive three-dimensional analysis of inhomogeneous structures based on the meso-volume concept and application of deficient spline functions for displacement approximations is proposed. The general methodology is demonstrated on the example of a brick-type mosaic parallelepiped arbitrarily composed of anisotropic meso-volumes. A partition of each meso-volume into sub-elements, application of deficient spline functions for a local approximation of displacements and, finally, the use of the variational principle allows one to obtain displacements, strains, and stresses at anypoint within the structural part. All of the necessary external and internal boundary conditions (including the conditions of continuity of transverse stresses at interfaces between adjacent meso-volumes) can be satisfied with requisite accuracy by increasing the density of the sub-element mesh. The application of the methodology to textile composite materials is described. Several numerical examples for woven and braided rectangular composite plates and stiffened panels under transverse bending are considered. Some typical effects of stress concentrations due to the material inhomogeneities are demonstrated.

  7. Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan

    PubMed Central

    2011-01-01

    Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462

  8. Landscape equivalency analysis: methodology for estimating spatially explicit biodiversity credits.

    PubMed

    Bruggeman, Douglas J; Jones, Michael L; Lupi, Frank; Scribner, Kim T

    2005-10-01

    We propose a biodiversity credit system for trading endangered species habitat designed to minimize and reverse the negative effects of habitat loss and fragmentation, the leading cause of species endangerment in the United States. Given the increasing demand for land, approaches that explicitly balance economic goals against conservation goals are required. The Endangered Species Act balances these conflicts based on the cost to replace habitat. Conservation banking is a means to manage this balance, and we argue for its use to mitigate the effects of habitat fragmentation. Mitigating the effects of land development on biodiversity requires decisions that recognize regional ecological effects resulting from local economic decisions. We propose Landscape Equivalency Analysis (LEA), a landscape-scale approach similar to HEA, as an accounting system to calculate conservation banking credits so that habitat trades do not exacerbate regional ecological effects of local decisions. Credits purchased by public agencies or NGOs for purposes other than mitigating a take create a net investment in natural capital leading to habitat defragmentation. Credits calculated by LEA use metapopulation genetic theory to estimate sustainability criteria against which all trades are judged. The approach is rooted in well-accepted ecological, evolutionary, and economic theory, which helps compensate for the degree of uncertainty regarding the effects of habitat loss and fragmentation on endangered species. LEA requires application of greater scientific rigor than typically applied to endangered species management on private lands but provides an objective, conceptually sound basis for achieving the often conflicting goals of economic efficiency and long-term ecological sustainability. PMID:16132443

  9. Analysis of in-service failures and advances in microstructural characterization. Microstructural science Volume 26

    SciTech Connect

    Abramovici, E.; Northwood, D.O.; Shehata, M.T.; Wylie, J.

    1999-01-01

    The contents include Analysis of In-Service Failures (tutorials, transportation industry, corrosion and materials degradation, electronic and advanced materials); 1998 Sorby Award Lecture by Kay Geels, Struers A/S (Metallographic Preparation from Sorby to the Present); Advances in Microstructural Characterization (characterization techniques using high resolution and focused ion beam, characterization of microstructural clustering and correlation with performance); Advanced Applications (advanced alloys and intermetallic compounds, plasma spray coatings and other surface coatings, corrosion, and materials degradation).

  10. Thermal Analysis and Design of an Advanced Space Suit

    NASA Technical Reports Server (NTRS)

    Lin, Chin H.; Campbell, Anthony B.; French, Jonathan D.; French, D.; Nair, Satish S.; Miles, John B.

    2000-01-01

    The thermal dynamics and design of an Advanced Space Suit are considered. A transient model of the Advanced Space Suit has been developed and implemented using MATLAB/Simulink to help with sizing, with design evaluation, and with the development of an automatic thermal comfort control strategy. The model is described and the thermal characteristics of the Advanced Space suit are investigated including various parametric design studies. The steady state performance envelope for the Advanced Space Suit is defined in terms of the thermal environment and human metabolic rate and the transient response of the human-suit-MPLSS system is analyzed.

  11. [Advance directives in Switzerland: brief analysis on ethical perspectives].

    PubMed

    Bondolfi, Alberto

    2008-01-01

    The author describes the political atmosphere in Switzerland which accepts the principle of advanced directives. Until now only a few cantons have legally defined the advanced directives. At the present, during the revision of common law and especially the revision of the guardianship law, the parliament is discussing a chapter dedicated to advanced directives. In this way the statute of advanced directive will be the same in all cantons. The author underlines the importance/necessity and the partiality of the principle of autonomy in this field.

  12. Use of High Spatial Resolution Remote Sensing for Hydro-Geomorphologic Analysis of Medium-sized Arid Basins

    NASA Astrophysics Data System (ADS)

    Sadeh, Yuval; Blumberg, Dan G.; Cohen, Hai; Morin, Efrat; Maman, Shimrit

    2016-04-01

    Arid environments are often remote, expansive, difficult to access and especially vulnerable to flash flood hazards due to the poor understanding of the phenomenon and the lack of meteorological, geomorphological, and hydrological data. For many years, catchment characteristics have been observed using point-based measurements such as rain gauges and soil sample analysis; on the other hand, use of remote sensing technologies can provide spatially continuous hydrological parameters and variables. The advances in remote sensing technologies can provide new geo-spatial data using high spatial and temporal resolution for basin-scale geomorphological analysis and hydrological models. This study used high spatial resolution remote sensing for hydro-geomorphologic analysis of the arid medium size Rahaf watershed (76 km2), located in the Judean Desert, Israel. During the research a high resolution geomorphological map of Rahaf basin was created using WorldView-2 multispectral satellite imageries; surface roughness was estimated using SIR-C and COSMO-SkyMed Synthetic Aperture Radar (SAR) spaceborne sensors; and rainstorm characteristics were extracted using ground-based meteorological radar. The geomorphological mapping of Rahaf into 17 classes with good accuracy. The surface roughness extraction using SAR over the basin showed that the correlation between the COSMO-SkyMed backscatter coefficient and the surface roughness was very strong with an R2 of 0.97. This study showed that using x-band spaceborne sensors with high spatial resolution, such as COSMO-SkyMed, are more suitable for surface roughness evaluation in flat arid environments and should be in favor with longer wavelength operating sensors such as the SIR-C. The current study presents an innovative method to evaluate Manning's hydraulic roughness coefficient (n) in arid environments using radar backscattering. The weather radar rainfall data was calibrated using rain gauges located in the watershed. The

  13. Spatial analysis of early successional, temperate forest community structure

    NASA Astrophysics Data System (ADS)

    Walker, R. H.; Williams, C. A.; MacLean, R. G.; Epstein, H. E.; Vanderhoof, M. K.

    2013-12-01

    The global importance of sequestration of carbon by temperate forests makes characterizing the regrowth of these forests post-disturbance both ecologically and economically important. High intensity disturbances, such as logging, result in substantial alteration of community composition post-disturbance, creating the potential for alterations to the cycling of carbon, water, and nutrients in the ecosystem. Because logging pressure in New England continues to increase, understanding how forest ecosystems in this region respond to disturbance is crucial. This study aims to characterize interspecies interactions within New England forests by identifying synchronous and asynchronous colocation of species following a disturbance. To accomplish this, line-intercept surveys of vegetation were conducted in a clearcut forest stand located within the Harvard Forest LTER site. Survey data collected two (2010) and five (2013) years post-clearcut were analyzed using a one-dimensional Ripley's K. From 2010 to 2013, an increase in the number of interspecies relationships was observed, indicating the development of community structure. Additionally, the analysis found an increase in total vegetative cover from 2010 to 2013, and also found the majority of observed interspecies relationships to be asynchronous relationships. Together, these results imply an increase in resource competition that had the potential to drive the increase in community structure. Specifically, an increase in community structure led to the development of three distinct sub-communities: homogenous fern, tree seedling canopy over ground cover, and shrub dominated. This creates a patchy landscape in the early successional forest that allows for high species diversity (Shannon's H = 2.455). Based on the results of the Ripley's K analyses, species demonstrated definite patterns of synchronicity and asynchronicity based on both specific species interactions as well as functional group interactions. These

  14. Spatial and temporal analysis of fMRI data on word and sentence reading.

    PubMed

    Haller, Sven; Klarhoefer, Markus; Schwarzbach, Jens; Radue, Ernst W; Indefrey, Peter

    2007-10-01

    Written language comprehension at the word and the sentence level was analysed by the combination of spatial and temporal analysis of functional magnetic resonance imaging (fMRI). Spatial analysis was performed via general linear modelling (GLM). Concerning the temporal analysis, local differences in neurovascular coupling may confound a direct comparison of blood oxygenation level-dependent (BOLD) response estimates between regions. To avoid this problem, we parametrically varied linguistic task demands and compared only task-induced within-region BOLD response differences across areas. We reasoned that, in a hierarchical processing system, increasing task demands at lower processing levels induce delayed onset of higher-level processes in corresponding areas. The flow of activation is thus reflected in the size of task-induced delay increases. We estimated BOLD response delay and duration for each voxel and each participant by fitting a model function to the event-related average BOLD response. The GLM showed increasing activations with increasing linguistic demands dominantly in the left inferior frontal gyrus (IFG) and the left superior temporal gyrus (STG). The combination of spatial and temporal analysis allowed a functional differentiation of IFG subregions involved in written language comprehension. Ventral IFG region (BA 47) and STG subserve earlier processing stages than two dorsal IFG regions (BA 44 and 45). This is in accordance with the assumed early lexical semantic and late syntactic processing of these regions and illustrates the complementary information provided by spatial and temporal fMRI data analysis of the same data set.

  15. Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013

    PubMed Central

    Chen, Yan-Yan; Huang, Xi-Bao; Xiao, Ying; Jiang, Yong; Shan, Xiao-wei; Zhang, Juan; Cai, Shun-Xiang; Liu, Jian-Bing

    2015-01-01

    Background Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions. Methods In this study, spatial autocorrelation methodologies, including global Moran’s I and local Getis–Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time. Results The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran’s I > 0, P < 0.01), which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties. Conclusions The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial–temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be

  16. Crashworthiness analysis using advanced material models in DYNA3D

    SciTech Connect

    Logan, R.W.; Burger, M.J.; McMichael, L.D.; Parkinson, R.D.

    1993-10-22

    As part of an electric vehicle consortium, LLNL and Kaiser Aluminum are conducting experimental and numerical studies on crashworthy aluminum spaceframe designs. They have jointly explored the effect of heat treat on crush behavior and duplicated the experimental behavior with finite-element simulations. The major technical contributions to the state of the art in numerical simulation arise from the development and use of advanced material model descriptions for LLNL`s DYNA3D code. Constitutive model enhancements in both flow and failure have been employed for conventional materials such as low-carbon steels, and also for lighter weight materials such as aluminum and fiber composites being considered for future vehicles. The constitutive model enhancements are developed as extensions from LLNL`s work in anisotropic flow and multiaxial failure modeling. Analysis quality as a function of level of simplification of material behavior and mesh is explored, as well as the penalty in computation cost that must be paid for using more complex models and meshes. The lightweight material modeling technology is being used at the vehicle component level to explore the safety implications of small neighborhood electric vehicles manufactured almost exclusively from these materials.

  17. Safety Analysis of Soybean Processing for Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Hentges, Dawn L.

    1999-01-01

    Soybeans (cv. Hoyt) is one of the crops planned for food production within the Advanced Life Support System Integration Testbed (ALSSIT), a proposed habitat simulation for long duration lunar/Mars missions. Soybeans may be processed into a variety of food products, including soymilk, tofu, and tempeh. Due to the closed environmental system and importance of crew health maintenance, food safety is a primary concern on long duration space missions. Identification of the food safety hazards and critical control points associated with the closed ALSSIT system is essential for the development of safe food processing techniques and equipment. A Hazard Analysis Critical Control Point (HACCP) model was developed to reflect proposed production and processing protocols for ALSSIT soybeans. Soybean processing was placed in the type III risk category. During the processing of ALSSIT-grown soybeans, critical control points were identified to control microbiological hazards, particularly mycotoxins, and chemical hazards from antinutrients. Critical limits were suggested at each CCP. Food safety recommendations regarding the hazards and risks associated with growing, harvesting, and processing soybeans; biomass management; and use of multifunctional equipment were made in consideration of the limitations and restraints of the closed ALSSIT.

  18. Metabolomics analysis for biomarker discovery: advances and challenges.

    PubMed

    Monteiro, M S; Carvalho, M; Bastos, M L; Guedes de Pinho, P

    2013-01-01

    Over the last decades there has been a change in biomedical research with the search for single genes, transcripts, proteins, or metabolites being substituted by the coverage of the entire genome, transcriptome, proteome, and metabolome with the "omics" approaches. The emergence of metabolomics, defined as the comprehensive analysis of all metabolites in a system, is still recent compared to other "omics" fields, but its particular features and the improvement of both analytical techniques and pattern recognition methods has contributed greatly to its increasingly use. The feasibility of metabolomics for biomarker discovery is supported by the assumption that metabolites are important players in biological systems and that diseases cause disruption of biochemical pathways, which are not new concepts. In fact, metabolomics, meaning the parallel assessment of multiple metabolites, has been shown to have benefits in various clinical areas. Compared to classical diagnostic approaches and conventional clinical biomarkers, metabolomics offers potential advantages in sensitivity and specificity. Despite its potential, metabolomics still retains several intrinsic limitations which have a great impact on its widespread implementation - these limitations in biological and experimental measurements. This review will provide an insight to the characteristics, strengths, limitations, and recent advances in metabolomics, always keeping in mind its potential application in clinical/ health areas as a biomarker discovery tool. PMID:23210853

  19. Steady-State Analysis Model for Advanced Fuel Cycle Schemes.

    2008-03-17

    Version 00 SMAFS was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003-2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high-level waste along time are included in the model and can be displayed. The user can easily modify values of mass flows and/or cost parameters and see corresponding changes in the results. The model calculates: front-end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs.« less

  20. Steady-state Analysis Model for Advanced Fuelcycle Schemes

    2006-05-12

    The model was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003—2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down the cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high—level waste along time are included in the model and can be displayed. The user can modify easily the values of mass flows and/or cost parameters and see the corresponding changes in the results. The model calculates: front—end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs. It performs Monte Carlo simulations with changing the values of all unit costs within their respective ranges (from lower to upper bounds).« less

  1. Advanced Coursework Rates by Ethnicity: An 11-Year, Statewide Analysis

    ERIC Educational Resources Information Center

    Fowler, Janis C.

    2013-01-01

    Purpose: The purpose of this study was to examine advanced coursework completion rates, Advanced Placement (AP)/International Baccalaureate (IB) testing rates, AP/IB exam passage rates, and the percentage of AP/IB exam scores at or above the criterion that may exist among Texas public high school students from 2001 to 2012 to ascertain (a) the…

  2. Advanced methods of structural and trajectory analysis for transport aircraft

    NASA Technical Reports Server (NTRS)

    Ardema, Mark D.

    1995-01-01

    This report summarizes the efforts in two areas: (1) development of advanced methods of structural weight estimation, and (2) development of advanced methods of trajectory optimization. The majority of the effort was spent in the structural weight area. A draft of 'Analytical Fuselage and Wing Weight Estimation of Transport Aircraft', resulting from this research, is included as an appendix.

  3. Male biological clock: a critical analysis of advanced paternal age

    PubMed Central

    Ramasamy, Ranjith; Chiba, Koji; Butler, Peter; Lamb, Dolores J.

    2016-01-01

    Extensive research defines the impact of advanced maternal age on couples’ fecundity and reproductive outcomes, but significantly less research has been focused on understanding the impact of advanced paternal age. Yet it is increasingly common for couples at advanced ages to conceive children. Limited research suggests that the importance of paternal age is significantly less than that of maternal age, but advanced age of the father is implicated in a variety of conditions affecting the offspring. This review examines three aspects of advanced paternal age: the potential problems with conception and pregnancy that couples with advanced paternal age may encounter, the concept of discussing a limit to paternal age in a clinical setting, and the risks of diseases associated with advanced paternal age. As paternal age increases, it presents no absolute barrier to conception, but it does present greater risks and complications. The current body of knowledge does not justify dissuading older men from trying to initiate a pregnancy, but the medical community must do a better job of communicating to couples the current understanding of the risks of conception with advanced paternal age. PMID:25881878

  4. Integrated design and analysis of advanced airfoil shapes for gas turbine engines

    SciTech Connect

    Hill, B.A.; Rooney, P.J.

    1986-01-01

    An integral process in the mechanical design of gas turbine airfoils is the conversion of hot or running geometry into cold or as-manufactured geometry. New and advanced methods of design and analysis must be created that parallel new and technologically advanced turbine components. In particular, to achieve the high performance required of today's gas turbine engines, the industry is forced to design and manufacture increasingly complex airfoil shapes using advanced analysis and modeling techniques. This paper describes a method of integrating advanced, general purpose finite element analysis techniques in the mechanical design process.

  5. Spatial sensitivity analysis of remote sensing snow cover fraction data in a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Berezowski, Tomasz; Chormański, Jarosław; Nossent, Jiri; Batelaan, Okke

    2014-05-01

    Distributed hydrological models enhance the analysis and explanation of environmental processes. As more spatial input data and time series become available, more analysis is required of the sensitivity of the data on the simulations. Most research so far focussed on the sensitivity of precipitation data in distributed hydrological models. However, these results can not be compared until a universal approach to quantify the sensitivity of a model to spatial data is available. The frequently tested and used remote sensing data for distributed models is snow cover. Snow cover fraction (SCF) remote sensing products are easily available from the internet, e.g. MODIS snow cover product MOD10A1 (daily snow cover fraction at 500m spatial resolution). In this work a spatial sensitivity analysis (SA) of remotely sensed SCF from MOD10A1 was conducted with the distributed WetSpa model. The aim is to investigate if the WetSpa model is differently subjected to SCF uncertainty in different areas of the model domain. The analysis was extended to look not only at SA quantities but also to relate them to the physical parameters and processes in the study area. The study area is the Biebrza River catchment, Poland, which is considered semi natural catchment and subject to a spring snow melt regime. Hydrological simulations are performed with the distributed WetSpa model, with a simulation period of 2 hydrological years. For the SA the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm is used, with a set of different response functions in regular 4 x 4 km grid. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different landscape features. Moreover, the spatial patterns of the SA results are related to the WetSpa spatial parameters and to different physical processes. Based on the study results, it is clear that spatial approach of SA can be performed with the proposed algorithm and the MOD10A1 SCF is spatially sensitive in

  6. Advanced analysis of complex seismic waveforms to characterize the subsurface Earth structure

    NASA Astrophysics Data System (ADS)

    Jia, Tianxia

    2011-12-01

    This thesis includes three major parts, (1) Body wave analysis of mantle structure under the Calabria slab, (2) Spatial Average Coherency (SPAC) analysis of microtremor to characterize the subsurface structure in urban areas, and (3) Surface wave dispersion inversion for shear wave velocity structure. Although these three projects apply different techniques and investigate different parts of the Earth, their aims are the same, which is to better understand and characterize the subsurface Earth structure by analyzing complex seismic waveforms that are recorded on the Earth surface. My first project is body wave analysis of mantle structure under the Calabria slab. Its aim is to better understand the subduction structure of the Calabria slab by analyzing seismograms generated by natural earthquakes. The rollback and subduction of the Calabrian Arc beneath the southern Tyrrhenian Sea is a case study of slab morphology and slab-mantle interactions at short spatial scale. I analyzed the seismograms traversing the Calabrian slab and upper mantle wedge under the southern Tyrrhenian Sea through body wave dispersion, scattering and attenuation, which are recorded during the PASSCAL CAT/SCAN experiment. Compressional body waves exhibit dispersion correlating with slab paths, which is high-frequency components arrivals being delayed relative to low-frequency components. Body wave scattering and attenuation are also spatially correlated with slab paths. I used this correlation to estimate the positions of slab boundaries, and further suggested that the observed spatial variation in near-slab attenuation could be ascribed to mantle flow patterns around the slab. My second project is Spatial Average Coherency (SPAC) analysis of microtremors for subsurface structure characterization. Shear-wave velocity (Vs) information in soil and rock has been recognized as a critical parameter for site-specific ground motion prediction study, which is highly necessary for urban areas located

  7. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

    NASA Astrophysics Data System (ADS)

    Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

    2016-04-01

    Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.

  8. Point pattern analysis with spatially varying covariate effects, applied to the study of cerebrovascular deaths.

    PubMed

    Pinto Junior, Jony Arrais; Gamerman, Dani; Paez, Marina Silva; Fonseca Alves, Regina Helena

    2015-03-30

    This article proposes a modeling approach for handling spatial heterogeneity present in the study of the geographical pattern of deaths due to cerebrovascular disease.The framework involvesa point pattern analysis with components exhibiting spatial variation. Preliminary studies indicate that mortality of this disease and the effect of relevant covariates do not exhibit uniform geographic distribution. Our model extends a previously proposed model in the literature that uses spatial and non-spatial variables by allowing for spatial variation of the effect of non-spatial covariates. A number of relative risk indicators are derived by comparing different covariate levels, different geographic locations, or both. The methodology is applied to the study of the geographical death pattern of cerebrovascular deaths in the city of Rio de Janeiro. The results compare well against existing alternatives, including fixed covariate effects. Our model is able to capture and highlight important data information that would not be noticed otherwise, providing information that is required for appropriate health decision-making.

  9. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

    PubMed Central

    Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

    2016-01-01

    Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ. PMID:27068335

  10. Generic Repository Concepts and Thermal Analysis for Advanced Fuel Cycles

    SciTech Connect

    Hardin, Ernest; Blink, James; Carter, Joe; Massimiliano, Fratoni; Greenberg, Harris; Howard, Rob L

    2011-01-01

    The current posture of the used nuclear fuel management program in the U.S. following termination of the Yucca Mountain Project, is to pursue research and development (R&D) of generic (i.e., non-site specific) technologies for storage, transportation and disposal. Disposal R&D is directed toward understanding and demonstrating the performance of reference geologic disposal concepts selected to represent the current state-of-the-art in geologic disposal. One of the principal constraints on waste packaging and emplacement in a geologic repository is management of the waste-generated heat. This paper describes the selection of reference disposal concepts, and thermal management strategies for waste from advanced fuel cycles. A geologic disposal concept for spent nuclear fuel (SNF) or high-level waste (HLW) consists of three components: waste inventory, geologic setting, and concept of operations. A set of reference geologic disposal concepts has been developed by the U.S. Department of Energy (DOE) Used Fuel Disposition Campaign, for crystalline rock, clay/shale, bedded salt, and deep borehole (crystalline basement) geologic settings. We performed thermal analysis of these concepts using waste inventory cases representing a range of advanced fuel cycles. Concepts of operation consisting of emplacement mode, repository layout, and engineered barrier descriptions, were selected based on international progress and previous experience in the U.S. repository program. All of the disposal concepts selected for this study use enclosed emplacement modes, whereby waste packages are in direct contact with encapsulating engineered or natural materials. The encapsulating materials (typically clay-based or rock salt) have low intrinsic permeability and plastic rheology that closes voids so that low permeability is maintained. Uniformly low permeability also contributes to chemically reducing conditions common in soft clay, shale, and salt formations. Enclosed modes are associated

  11. Spatial statistical analysis of basal stem root disease under natural field epidemic of oil palm

    NASA Astrophysics Data System (ADS)

    Kamu, Assis; Phin, Chong Khim; Seman, Idris Abu; Wan, Hoong Hak; Mun, Ho Chong

    2015-02-01

    Oil palm or scientifically known as Elaeis guineensis Jacq. is the most important commodity crop in Malaysia and has greatly contributed to the economy growth of the country. As far as disease is concerned in the industry, Basal Stem Rot (BSR) caused by Ganoderma boninence remains the most important disease. BSR disease is the most widely studied with information available for oil palm disease in Malaysia. However, there is still limited study on the spatial as well as temporal pattern or distribution of the disease especially under natural field epidemic condition in oil palm plantation. The objective of this study is to spatially identify the pattern of BSR disease under natural field epidemic using two geospatial analytical techniques, which are quadrat analysis for the first order properties of partial pattern analysis and nearest-neighbor analysis (NNA) for the second order properties of partial pattern analysis. Two study sites were selected with different age of tree. Both sites are located in Tawau, Sabah and managed by the same company. The results showed that at least one of the point pattern analysis used which is NNA (i.e. the second order properties of partial pattern analysis) has confirmed the disease is complete spatial randomness. This suggests the spread of the disease is not from tree to tree and the age of palm does not play a significance role in determining the spatial pattern of the disease. From the spatial pattern of the disease, it would help in the disease management program and for the industry in the future. The statistical modelling is expected to help in identifying the right model to estimate the yield loss of oil palm due to BSR disease in the future.

  12. The spatial metaphor of Utopia in Russian culture and in analysis.

    PubMed

    Tsivinsky, Vladimir

    2014-02-01

    The spatial metaphor of Utopia is considered from a Jungian perspective along with its role in Russian culture and in analysis. Such post-Jungian concepts as the cultural complex and the archetypal story pattern of a victim are used in considering the desperate longing for a rescuer in patients' narratives and in Russian society. A clinical vignette is provided to illustrate these ideas.

  13. Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change

    ERIC Educational Resources Information Center

    Wang, Ninghua Nathan

    2013-01-01

    Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…

  14. Misfits and the Imagined American High School: A Spatial Analysis of Student Identities and Schooling

    ERIC Educational Resources Information Center

    Convertino, Christina

    2015-01-01

    This article provides a socio-spatial analysis of youth identities within the context of school choice reforms. Unable to conform to cultural ideals inscribed in the American school, a diverse group of youth forced out of traditional schools mediate the local production of school choice initiatives through the formation of youth identities as…

  15. Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

    NASA Astrophysics Data System (ADS)

    Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

    2014-12-01

    Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

  16. The onset of absolute instability of rotating Hagen-Poiseuille flow: A spatial stability analysis

    NASA Astrophysics Data System (ADS)

    Fernandez-Feria, R.; del Pino, C.

    2002-09-01

    A spatial, viscous stability analysis of Poiseuille pipe flow with superimposed solid body rotation is considered. For each value of the swirl parameter (inverse Rossby number) L>0, there exists a critical Reynolds number Rec)(L above which the flow first becomes convectively unstable to nonaxisymmetric disturbances with azimuthal wave number n=-1. This neutral stability curve confirms previous temporal stability analyses. From this spatial stability analysis, we propose here a relatively simple procedure to look for the onset of absolute instability that satisfies the so-called Briggs-Bers criterion. We find that, for perturbations with n=-1, the flow first becomes absolutely unstable above another critical Reynolds number Ret)(L>Rec)(L, provided that L>0.38, with Ret[right arrow]Rec as L[right arrow]infinity. Other values of the azimuthal wave number n are also considered. For Re>Ret)(L, the disturbances grow both upstream and downstream of the source, and the spatial stability analysis becomes inappropriate. However, for Ret, the spatial analysis provides a useful description on how convectively unstable perturbations become absolutely unstable in this kind of flow.

  17. The onset of absolute instability of rotating Hagen-Poiseuille flow: A spatial stability analysis

    NASA Astrophysics Data System (ADS)

    Fernandez-Feria, R.; del Pino, C.

    2002-09-01

    A spatial, viscous stability analysis of Poiseuille pipe flow with superimposed solid body rotation is considered. For each value of the swirl parameter (inverse Rossby number) L>0, there exists a critical Reynolds number Rec(L) above which the flow first becomes convectively unstable to nonaxisymmetric disturbances with azimuthal wave number n=-1. This neutral stability curve confirms previous temporal stability analyses. From this spatial stability analysis, we propose here a relatively simple procedure to look for the onset of absolute instability that satisfies the so-called Briggs-Bers criterion. We find that, for perturbations with n=-1, the flow first becomes absolutely unstable above another critical Reynolds number Ret(L)>Rec(L), provided that L>0.38, with Ret→Rec as L→∞. Other values of the azimuthal wave number n are also considered. For Re>Ret(L), the disturbances grow both upstream and downstream of the source, and the spatial stability analysis becomes inappropriate. However, for Respatial analysis provides a useful description on how convectively unstable perturbations become absolutely unstable in this kind of flow.

  18. Genetic Algorithms Application for the Photoacoustic Signal Temporal Shape Analysis and Energy Density Spatial Distribution Calculation

    NASA Astrophysics Data System (ADS)

    Lukić, M.; Ćojbašić, Ž.; Rabasović, M. D.; Markushev, D. D.; Todorović, D. M.

    2013-09-01

    Recently, a few numerical methods based on the photoacoustic (PA) signal temporal shape analysis and energy density spatial distribution calculation, which is directly related to the laser beam spatial profile, have been presented. It has been shown that these methods allow a precise reproduction of the spatial profile and the radius of the laser beam, determining the vibrational-to-translational (V-T) relaxation time with good accuracy. Their applicability has been shown and confirmed for the analysis of an arbitrary symmetric laser beam spatial profile in cylindrical geometry. Here, the application of genetic optimization for solving the problem of a simultaneous laser beam spatial profile and V-T relaxation time determination by pulsed PAs is presented. Real-coded genetic algorithms are used to calculate the mentioned relaxation time by fitting the experimental signal with the theoretical one. The aim is to find combinations of PA signal parameters, namely, the radius of the laser beam and the V-T relaxation time that provide the best match with the given signal. A calculated PA signal with a known profile is used to simulate an experimental signal, and the sum of the square deviations representing deviations of the given and fitted signals is minimized by means of genetic optimization. In that way, the genetic algorithms are used to simultaneously estimate the radius of the laser beam and the V-T relaxation time efficiently and with high accuracy. Compared to previous methods, the presented method is much simpler and requires less time to compute.

  19. Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain

    PubMed Central

    Chou, Shen-Ju; Wang, Chindi; Sintupisut, Nardnisa; Niou, Zhen-Xian; Lin, Chih-Hsu; Li, Ker-Chau; Yeang, Chen-Hsiang

    2016-01-01

    Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary, and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior, and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development. PMID:26786896

  20. Exploratory Analysis of Spatial-Temporal Patterns of Air Pollution in the City

    NASA Astrophysics Data System (ADS)

    Champendal, Alexandre; Kanevski, Mikhail; Huguenot, Pierre-Emmanuel; Golay, Jean

    2013-04-01

    Air pollution in the city is an important problem influencing environment, well-being of society, economy, management of urban zones, etc. The problem is extremely difficult due to a very complex distribution of the pollution sources, morphology of the city and dispersion processes leading to multivariate nature of the phenomena and high local spatial-temporal variability. The task of understanding, modelling and prediction of spatial-temporal patterns of air pollution in urban zones is an interesting and challenging topic having many research axes from science-based modelling to geostatistics and data mining. The present research mainly deals with a comprehensive exploratory analysis of spatial-temporal air pollution data using statistical, geostatistical and machine learning tools. This analysis helps to 1) understand and model spatial-temporal correlations using variography, 2) explore the temporal evolution of spatial correlation matrix; 3) analyse and visualize an interconnection between measurement stations using network science tools; 4) quantify the availability and predictability of structured patterns. The real data case study deals with spatial-temporal air pollution data of canton Geneva (2002-2011). Carbon dioxide (NO2) have caught our attention. It has effects on health: nitrogen dioxide can irritate the lungs, effects on plants; NO2 contributes to the phenomenon of acid rain. The negative effects of nitrogen dioxides on plants are reducing the growth, production and pesticide resistance. And finally the effects on materials: nitrogen dioxides increase the corrosion. Well-defined patterns of spatial-temporal correlations were detected. The analysis and visualization of spatial correlation matrix for 91 stations were carried out using the network science tools and high levels of clustering were revealed. Moving Window Correlation Matrix and Spatio-temporal variography methods were applied to define and explore the dynamic of our data. More than just

  1. Analysis of the Impact of Soil Heterogeneity on the Spatial Variation of Unsaturated Flow

    NASA Astrophysics Data System (ADS)

    Patterson, Matthew; Gimenez, Daniel; Kerry, Ruth; Goovaerts, Pierre

    2016-04-01

    the numerical model HYDRUS 3D (PC-Progress, Prague, Czech Republic) based on the numerical indices assigned by LISA, was automated. Each of the 100 realizations were run at 10 different inflow rates ranging from 1.44 cm/d to 74.4 cm/d. Each of the 1000 simulations produced resulted in an output of 487 spatially-varied outflows, allowing spatial analysis of the model outputs and comparison to the spatial outputs from the column experiment. Analysis of the effects of the size and spatial location of the synthetic hydraulic property clusters at different flow rates on the spatial distribution of outflow will be presented and discussed.

  2. Learning Bayesian networks from big meteorological spatial datasets. An alternative to complex network analysis

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Jose Manuel; San Martín, Daniel; Herrera, Sixto; Santiago Cofiño, Antonio

    2016-04-01

    The growing availability of spatial datasets (observations, reanalysis, and regional and global climate models) demands efficient multivariate spatial modeling techniques for many problems of interest (e.g. teleconnection analysis, multi-site downscaling, etc.). Complex networks have been recently applied in this context using graphs built from pairwise correlations between the different stations (or grid boxes) forming the dataset. However, this analysis does not take into account the full dependence structure underlying the data, gien by all possible marginal and conditional dependencies among the stations, and does not allow a probabilistic analysis of the dataset. In this talk we introduce Bayesian networks as an alternative multivariate analysis and modeling data-driven technique which allows building a joint probability distribution of the stations including all relevant dependencies in the dataset. Bayesian networks is a sound machine learning technique using a graph to 1) encode the main dependencies among the variables and 2) to obtain a factorization of the joint probability distribution of the stations given by a reduced number of parameters. For a particular problem, the resulting graph provides a qualitative analysis of the spatial relationships in the dataset (alternative to complex network analysis), and the resulting model allows for a probabilistic analysis of the dataset. Bayesian networks have been widely applied in many fields, but their use in climate problems is hampered by the large number of variables (stations) involved in this field, since the complexity of the existing algorithms to learn from data the graphical structure grows nonlinearly with the number of variables. In this contribution we present a modified local learning algorithm for Bayesian networks adapted to this problem, which allows inferring the graphical structure for thousands of stations (from observations) and/or gridboxes (from model simulations) thus providing new

  3. Advanced DInSAR analysis at Campi Flegrei and Vesuvius, Italy

    NASA Astrophysics Data System (ADS)

    Tiampo, K. F.; Camacho, A. G.; Fernandez, J.; Gonzalez, P. J.; Samsonov, S. V.

    2015-12-01

    Geodetic data, the spatial and temporal surface expression of complex geophysical processes in the earth, is being acquired today at unprecedented rates and accuracies. Differential interferometric synthetic aperture radar (DInSAR) is a satellite remote sensing technique used extensively today for mapping ground deformation with high spatial resolution and sub-centimeter precision over large areas that is particularly useful for volcanic monitoring [Massonnet and Feigl, 1998; Rosen et al., 2000]. Here we apply the advanced Multidimensional Small Baseline Subset (MSBAS) InSAR algorithm [Samsonov and d'Oreye, 2012] to several thousand Envisat and RADARSAT-2 images from 1993-2013 and compute time series of ground deformation over the Naples Bay region of Italy. Vesuvius and Campi Flegrei are located in this area in close proximity to the densely populated city of Naples and, as a result, it is one of the most hazardous volcanic areas in the world. We obtain time series of ground deformation at high spatial and temporal resolution that span, for the first time, twenty years. Campi Flegrei underwent continuous subsidence through 1999. Uplift began in 2005, reaching approximately 13 cm by 2013. We model the observed deformation to determine source parameters for subsidence and uplift epochs [Samsonov et al., 2014]. In addition, a typical DInSAR image can contain significant signals from with several different, nonvolcanic sources. For example, we clearly observe decade-long elevation-dependent seasonal oscillations of the vertical displacement component at Vesuvius that are substantially larger than the long-term deformation rate (<0.6 cm/yr). As a result, we employ an eigenpattern decomposition technique known as Karhunen-Loeve expansion (KLE) analysis in order to identify the unique, finite set of correlated deformation patterns associated with volcanic sources at different depths [Tiampo et al., 2004; Tiampo et al., 2012]. Both the inflation and deflation mechanisms

  4. Advancements in 3D Structural Analysis of Geothermal Systems

    SciTech Connect

    Siler, Drew L; Faulds, James E; Mayhew, Brett; McNamara, David

    2013-06-23

    Robust geothermal activity in the Great Basin, USA is a product of both anomalously high regional heat flow and active fault-controlled extension. Elevated permeability associated with some fault systems provides pathways for circulation of geothermal fluids. Constraining the local-scale 3D geometry of these structures and their roles as fluid flow conduits is crucial in order to mitigate both the costs and risks of geothermal exploration and to identify blind (no surface expression) geothermal resources. Ongoing studies have indicated that much of the robust geothermal activity in the Great Basin is associated with high density faulting at structurally complex fault intersection/interaction areas, such as accommodation/transfer zones between discrete fault systems, step-overs or relay ramps in fault systems, intersection zones between faults with different strikes or different senses of slip, and horse-tailing fault terminations. These conceptualized models are crucial for locating and characterizing geothermal systems in a regional context. At the local scale, however, pinpointing drilling targets and characterizing resource potential within known or probable geothermal areas requires precise 3D characterization of the system. Employing a variety of surface and subsurface data sets, we have conducted detailed 3D geologic analyses of two Great Basin geothermal systems. Using EarthVision (Dynamic Graphics Inc., Alameda, CA) we constructed 3D geologic models of both the actively producing Brady’s geothermal system and a ‘greenfield’ geothermal prospect at Astor Pass, NV. These 3D models allow spatial comparison of disparate data sets in 3D and are the basis for quantitative structural analyses that can aid geothermal resource assessment and be used to pinpoint discrete drilling targets. The relatively abundant data set at Brady’s, ~80 km NE of Reno, NV, includes 24 wells with lithologies interpreted from careful analysis of cuttings and core, a 1

  5. Advanced waveform decomposition for high-speed videoendoscopy analysis.

    PubMed

    Ikuma, Takeshi; Kunduk, Melda; McWhorter, Andrew J

    2013-05-01

    This article presents a novel approach to analyze nonperiodic vocal fold behavior of high-speed videoendoscopy (HSV) data. Although HSV can capture true vibrational motions of the vocal folds, its clinical advantage over the videostroboscopy has not widely been accepted. One of the key advantages of the HSV over the videostroboscopy is its ability to capture vocal folds' nonperiodic behavior, which is more prominent in pathological vocal folds. However, such nonperiodicity in the HSV data has not been fully explored quantitatively beyond simple perturbation analysis. This article presents an advanced waveform modeling and decomposition technique for HSV-based waveforms. Waveforms are modeled to have three components: harmonic signal, deterministic nonharmonic signal, and random nonharmonic signal. This decomposition is motivated by the fact that voice disorders introduce signal content that is nonharmonic but carries deterministic quality such as subharmonic or modulating content. The proposed model is aimed to isolate such disordered behaviors as deterministic nonharmonic signal and quantify them. In addition to the model, the article outlines model parameter estimation procedures and a family of harmonics-to-noise ratio (HNR) parameters. The proposed HNR parameters include harmonics-to-deterministic-noise ratio (HDNR) and harmonics-to-random-noise ratio. A preliminary study demonstrates the effectiveness of the extended model and its HNR parameters. Vocal folds with and without benign lesions (Nwith = 13; Nwithout = 20) were studied with HSV glottal area waveforms. All three HNR parameters significantly distinguished the disordered condition, and the HDNR reported the largest effect size (Cohen's d = 2.04).

  6. NEIGHBOUR-IN: Image processing software for spatial analysis of animal grouping

    PubMed Central

    Caubet, Yves; Richard, Freddie-Jeanne

    2015-01-01

    Abstract Animal grouping is a very complex process that occurs in many species, involving many individuals under the influence of different mechanisms. To investigate this process, we have created an image processing software, called NEIGHBOUR-IN, designed to analyse individuals’ coordinates belonging to up to three different groups. The software also includes statistical analysis and indexes to discriminate aggregates based on spatial localisation of individuals and their neighbours. After the description of the software, the indexes computed by the software are illustrated using both artificial patterns and case studies using the spatial distribution of woodlice. The added strengths of this software and methods are also discussed. PMID:26261448

  7. A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

    PubMed Central

    2013-01-01

    Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study

  8. A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

    USGS Publications Warehouse

    Saman, D.M.; Cole, H.P.; Odoi, A.; Myers, M.L.; Carey, D.I.; Westneat, S.C.

    2012-01-01

    Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns. Methods: A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns. Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001). Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky. ?? 2012 Saman et al.

  9. Pre-Surgical fMRI Data Analysis Using a Spatially Adaptive Conditionally Autoregressive Model

    PubMed Central

    Liu, Zhuqing; Berrocal, Veronica J.; Bartsch, Andreas J.; Johnson, Timothy D.

    2015-01-01

    Spatial smoothing is an essential step in the analysis of functional magnetic resonance imaging (fMRI) data. One standard smoothing method is to convolve the image data with a three-dimensional Gaussian kernel that applies a fixed amount of smoothing to the entire image. In pre-surgical brain image analysis where spatial accuracy is paramount, this method, however, is not reasonable as it can blur the boundaries between activated and deactivated regions of the brain. Moreover, while in a standard fMRI analysis strict false positive control is desired, for pre-surgical planning false negatives are of greater concern. To this end, we propose a novel spatially adaptive conditionally autoregressive model with variances in the full conditional of the means that are proportional to error variances, allowing the degree of smoothing to vary across the brain. Additionally, we present a new loss function that allows for the asymmetric treatment of false positives and false negatives. We compare our proposed model with two existing spatially adaptive conditionally autoregressive models. Simulation studies show that our model outperforms these other models; as a real model application, we apply the proposed model to the pre-surgical fMRI data of two patients to assess peri- and intra-tumoral brain activity. PMID:27042244

  10. Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

    USGS Publications Warehouse

    Pearson, D.K.; Gary, R.H.; Wilson, Z.D.

    2007-01-01

    Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

  11. Analysis of the spatial discretization modeling watershed using the hydrology distributed model CEQUEAU

    NASA Astrophysics Data System (ADS)

    Guerra-Cobián, V. H.; Ba, K. M.; Díaz-Delgado, C.; Quentin, E.; Carsteanu, A. A.; Salas-Limón, D.

    2009-04-01

    Today, the use of hydrological models is essential, since they can be used to analyze various aspects such as runoff, flooding, the operation of dams and supply systems, water use, and use and protection of groundwater. In this research, we examined the effect on the spatial variation of the discretization in sixteen watersheds on distributed hydrological model simulations CEQUEAU. The overall objective was to propose criteria for determining the optimum size of mesh for the watershed discretization. The main methodological steps that were undertaken focused on the selection of hydrometric stations, the creation of hydrometeorlogical databases through the acquisition and adaptation of geodata. Furthermore, within the framework of research, we developed a new hydrogeomatic module that works in GIS Idrisi, which was part of the information used in hydrological modeling. The model CEQUEAU was performed in watershed study, using the Nash criterion for evaluating the results of simulations. Finally, statistical analysis was performed of the results, to propose criteria to determine the optimal size of mesh. The results of the analysis of spatial discretization were broadly satisfactory, because, in the simulations were obtained on average Nash coefficient between 0.6538 and 0.9823. The application of statistical techniques to the results of the analysis of spatial discretization, there were two multiple linear regression models with R2 values for each of 0.780 and 0.817. These equations obtained can be used as a criterion for determining the optimum size of spatial discretization watershed.

  12. Advanced propfan analysis for the family of commuter airplanes

    NASA Technical Reports Server (NTRS)

    Swift, Gerald A.; Creighton, Tom; Haddad, Raphael; Hendrich, Louis; Hensley, Doug; Morgan, Louise; Russell, Mark

    1987-01-01

    Advanced propfans were selected to be used throughout the family of commuters. These propulsion systems offer a 25 to 28 percent fuel savings over comparably sized turbofans operating in the 1990s. A brief study of the propulsion systems available for the family of commuters is provided and the selection of the advanced turboprops justified. The propeller and engine designs and performance are discussed. The integration of these designs are examined. Also addressed is the noise considerations and constraints due to propfan installation.

  13. Spectral Analysis of Spatial Series Data of Pathologic Tissue: A Study on Small Intestine in ICR Mouse

    NASA Astrophysics Data System (ADS)

    Mise, Keiji; Sumi, Ayako; Kobayashi, Nobumichi; Torigoe, Toshihiko; Ohtomo, Norio

    2009-01-01

    We examined the usefulness of spectral analysis for investigating quantitatively the spatial pattern of pathologic tissue. To interpret the results obtained from real tissue, we constructed a two-dimensional spatial model of the tissue. Spectral analysis was applied to the spatial series data, which were obtained from the real tissue and model. From the results of spectral analysis, spatial patterns of the tissue and model were characterized quantitatively in reference to the frequencies and powers of the spectral peaks in power spectral densities (PSDs). The results for the model were essentially consistent with those for the tissue. It was concluded that the model was capable of adequately explaining the spatial pattern of the tissue. It is anticipated that spectral analysis will become a useful tool for characterizing the spatial pattern of the tissue quantitatively, resulting in an automated first screening of pathological specimens.

  14. Spatial structures in a reaction-diffusion system--detailed analysis of the "Brusselator".

    PubMed

    Kubícek, M; Rýzler, V; Marek, M

    1978-07-01

    Continuous dependence of spatially nonuniform concentration profiles for the 'Brussellator" reaction mechanims on the characteristic length of the system is given both for zero flux and fixed boundary conditions. Branches of solutions arising through primary bifurcation form closed curves. Secondary bifurcations giving rise to spatially asymmetric solutions exist for fixed boundary conditions. Results of a stability analysis of individual solutions are discussed. A method of composing complex spatial profiles for higher lengths from elementary solutions for smaller lenghts is suggested and tested in the case of zero flux boundary conditions. Emergence of subsequently more complex stable patterns in dependence on increasing length of the system suggests many similarities to gradual build up of complex morphogenetic patterns. PMID:687769

  15. Spatial bandwidth analysis of fast backward Fresnel diffraction for precise computer-generated hologram design.

    PubMed

    Liang, Jinyang; Becker, Michael F

    2014-09-20

    Designing near-field computer-generated holograms (CGHs) for a spatial light modulator (SLM) requires backward diffraction calculations. However, direct implementation of the discrete computational model of the Fresnel diffraction integral often produces inaccurate reconstruction. Finite sizes of the SLM and the target image, as well as aliasing, are major sources of error. Here we present a new design prescription for precise near-field CGHs based on comprehensive analysis of the spatial bandwidth. We demonstrate that, by controlling two free variables related to the target image, the designed hologram is free from aliasing and can have minimum error. To achieve this, we analyze the geometry of the target image, hologram, and Fourier transform plane of the target image to derive conditions for minimizing reconstruction error due to truncation of spatial frequencies lying outside of the hologram. The design prescription is verified by examples showing reconstruction error versus controlled parameters. Finally, it is applied to precise three-dimensional image reconstruction.

  16. Assessing spatial resolution versus sensitivity from laser speckle contrast imaging: application to frequency analysis.

    PubMed

    Bricq, Stéphanie; Mahé, Guillaume; Rousseau, David; Humeau-Heurtier, Anne; Chapeau-Blondeau, François; Varela, Julio Rojas; Abraham, Pierre

    2012-10-01

    For blood perfusion monitoring, laser speckle contrast (LSC) imaging is a recent non-contact technique that has the characteristic of delivering noise-like speckled images. To exploit LSC images for quantitative physiological measurements, we developed an approach that implements controlled spatial averaging to reduce the detrimental impact of the noise and improve measurement sensitivity. By this approach, spatial resolution and measurement sensitivity can be traded-off in a flexible way depending on the quantitative prospect of the study. As an application, detectability of the cardiac activity from LSC images of forearm using power spectrum analysis is studied through the construction of spatial activity maps offering a window on the blood flow perfusion and its regional distribution. Comparisons with results obtained with signals of laser Doppler flowmetry probes are performed. PMID:22644256

  17. Disentangling working memory processes during spatial span assessment: a modeling analysis of preferred eye movement strategies.

    PubMed

    Patt, Virginie M; Thomas, Michael L; Minassian, Arpi; Geyer, Mark A; Brown, Gregory G; Perry, William

    2014-01-01

    The neurocognitive processes involved during classic spatial working memory (SWM) assessment were investigated by examining naturally preferred eye movement strategies. Cognitively healthy adult volunteers were tested in a computerized version of the Corsi Block-Tapping Task--a spatial span task requiring the short term maintenance of a series of locations presented in a specific order--coupled with eye tracking. Modeling analysis was developed to characterize eye-tracking patterns across all task phases, including encoding, retention, and recall. Results revealed a natural preference for local gaze maintenance during both encoding and retention, with fewer than 40% fixated targets. These findings contrasted with the stimulus retracing pattern expected during recall as a result of task demands, with 80% fixated targets. Along with participants' self-reported strategies of mentally "making shapes," these results suggest the involvement of covert attention shifts and higher order cognitive Gestalt processes during spatial span tasks, challenging instrument validity as a single measure of SWM storage capacity.

  18. A Spatial Analysis of GEOID03 and GEOID09 in Connecticut

    NASA Astrophysics Data System (ADS)

    Arifuzzaman, Kazi; Hintz, Raymond J.

    2016-06-01

    The National Geodetic Survey (NGS) recommends using a hybrid geoid model to derive orthometric heights from ellipsoid heights. The accuracy of GEOID03 and GEOID09 were assessed independently in Connecticut. The present research analyses the spatial behavior of residuals derived from the comparison of differential levelled NAVD 88 orthometric heights and GPS-derived orthometric heights (using GEOID03 & GEOID09) at 72 benchmarks in Connecticut. Both geometrical and geostatistical analyses were performed on the residuals. A planar regression model indicates a weak spatial relation for residuals derived from GEOID03. This weakness was not noted in the analysis of residuals derived from GEOID09. Results of a four-parameter regression model does not indicate any need for a correction surface. A kriging surface was created with a fitted spherical semivariogram model and suggests GEOID09 captures more spatial variability of geoid undulation than GEOID03 in Connecticut.

  19. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    SciTech Connect

    Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena Safa; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

    2014-12-02

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

  20. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    NASA Astrophysics Data System (ADS)

    Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

    2014-12-01

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

  1. Advances in Parameter and Uncertainty Quantification Using Bayesian Hierarchical Techniques with a Spatially Referenced Watershed Model (Invited)

    NASA Astrophysics Data System (ADS)

    Alexander, R. B.; Boyer, E. W.; Schwarz, G. E.; Smith, R. A.

    2013-12-01

    Estimating water and material stores and fluxes in watershed studies is frequently complicated by uncertainties in quantifying hydrological and biogeochemical effects of factors such as land use, soils, and climate. Although these process-related effects are commonly measured and modeled in separate catchments, researchers are especially challenged by their complexity across catchments and diverse environmental settings, leading to a poor understanding of how model parameters and prediction uncertainties vary spatially. To address these concerns, we illustrate the use of Bayesian hierarchical modeling techniques with a dynamic version of the spatially referenced watershed model SPARROW (SPAtially Referenced Regression On Watershed attributes). The dynamic SPARROW model is designed to predict streamflow and other water cycle components (e.g., evapotranspiration, soil and groundwater storage) for monthly varying hydrological regimes, using mechanistic functions, mass conservation constraints, and statistically estimated parameters. In this application, the model domain includes nearly 30,000 NHD (National Hydrologic Data) stream reaches and their associated catchments in the Susquehanna River Basin. We report the results of our comparisons of alternative models of varying complexity, including models with different explanatory variables as well as hierarchical models that account for spatial and temporal variability in model parameters and variance (error) components. The model errors are evaluated for changes with season and catchment size and correlations in time and space. The hierarchical models consist of a two-tiered structure in which climate forcing parameters are modeled as random variables, conditioned on watershed properties. Quantification of spatial and temporal variations in the hydrological parameters and model uncertainties in this approach leads to more efficient (lower variance) and less biased model predictions throughout the river network

  2. Evidence for fish dispersal from spatial analysis of stream network topology

    USGS Publications Warehouse

    Hitt, N.P.; Angermeier, P.L.

    2008-01-01

    Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

  3. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    PubMed

    Badreldin, Nasem; Uria-Diez, J; Mateu, J; Youssef, Ali; Stal, Cornelis; El-Bana, Magdy; Magdy, Ahmed; Goossens, Rudi

    2015-05-01

    Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well. PMID:25838060

  4. Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination

    PubMed Central

    Ha, Hoehun; Rogerson, Peter A.; Olson, James R.; Han, Daikwon; Bian, Ling; Shao, Wanyun

    2016-01-01

    Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221

  5. Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

    PubMed Central

    Lakhankar, Tarendra; Jones, Andrew S.; Combs, Cynthia L.; Sengupta, Manajit; Vonder Haar, Thomas H.; Khanbilvardi, Reza

    2010-01-01

    Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations. PMID:22315576

  6. Gender, space, and the location changes of jobs and people: a spatial simultaneous equations analysis.

    PubMed

    Hoogstra, Gerke J

    2012-01-01

    This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes autoregressive and cross-regressive spatial lags to detect relations both within and among these groups. Spatial weights matrices reflecting different bands of travel times are used to calculate the spatial lags and to gauge the spatial nature of these relations. The empirical results show that although population–employment interaction is more localized for women's employment, no gender difference exists in the direction of interaction. Employment growth for both men and women is more influenced by population growth than vice versa. The interaction within employment groups is even more important than population growth. Women's, and especially men's, local employment growth mostly benefits from the same employment growth in neighboring locations. Finally, interaction between these groups is practically absent, although men's employment growth may have a negative impact on women's employment growth within small geographic areas. In summary, the results confirm the crucial roles of gender and space, and offer important insights into possible relations within and among subgroups of jobs and people.

  7. Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.

    PubMed

    Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun

    2016-09-14

    Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.

  8. Semi-blind signal extraction for communication signals by combining independent component analysis and spatial constraints.

    PubMed

    Wang, Xiang; Huang, Zhitao; Zhou, Yiyu

    2012-01-01

    Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms. PMID:23012531

  9. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    PubMed

    Badreldin, Nasem; Uria-Diez, J; Mateu, J; Youssef, Ali; Stal, Cornelis; El-Bana, Magdy; Magdy, Ahmed; Goossens, Rudi

    2015-05-01

    Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well.

  10. Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints

    PubMed Central

    Wang, Xiang; Huang, Zhitao; Zhou, Yiyu

    2012-01-01

    Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms. PMID:23012531

  11. Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.

    PubMed

    Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun

    2016-01-01

    Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221

  12. Current practices in spatial analysis of cancer data: mapping health statistics to inform policymakers and the public

    PubMed Central

    Bell, B Sue; Hoskins, Richard E; Pickle, Linda Williams; Wartenberg, Daniel

    2006-01-01

    Background To communicate population-based cancer statistics, cancer researchers have a long tradition of presenting data in a spatial representation, or map. Historically, health data were presented in printed atlases in which the map producer selected the content and format. The availability of geographic information systems (GIS) with comprehensive mapping and spatial analysis capability for desktop and Internet mapping has greatly expanded the number of producers and consumers of health maps, including policymakers and the public. Because health maps, particularly ones that show elevated cancer rates, historically have raised public concerns, it is essential that these maps be designed to be accurate, clear, and interpretable for the broad range of users who may view them. This article focuses on designing maps to communicate effectively. It is based on years of research into the use of health maps for communicating among public health researchers. Results The basics for designing maps that communicate effectively are similar to the basics for any mode of communication. Tasks include deciding on the purpose, knowing the audience and its characteristics, choosing a media suitable for both the purpose and the audience, and finally testing the map design to ensure that it suits the purpose with the intended audience, and communicates accurately and effectively. Special considerations for health maps include ensuring confidentiality and reflecting the uncertainty of small area statistics. Statistical maps need to be based on sound practices and principles developed by the statistical and cartographic communities. Conclusion The biggest challenge is to ensure that maps of health statistics inform without misinforming. Advances in the sciences of cartography, statistics, and visualization of spatial data are constantly expanding the toolkit available to mapmakers to meet this challenge. Asking potential users to answer questions or to talk about what they see is

  13. Different Factors for Different Causes: Analysis of the Spatial Aggregations of Fire Ignitions in Catalonia (Spain).

    PubMed

    González-Olabarria, José Ramón; Mola-Yudego, Blas; Coll, Lluis

    2015-07-01

    The present study analyzes the effects of different socioeconomic factors on the frequency of fire ignition occurrence, according to different original causes. The data include a set of documented ignition points in the region of Catalonia for the period 1995-2008. The analysis focused on the spatial aggregation patterns of the ignitions for each specific ignition cause. The point-based data on ignitions were interpolated into municipality-level information using kernel methods as the basis for defining five ignition density levels. Afterwards, the combination of socioeconomic factors influencing the ignition density levels of the municipalities was analyzed for each documented cause of ignition using a principal component analysis. The obtained results confirmed the idea that both the spatial aggregation patterns of fire ignitions and the factors defining their occurrence were specific for each of the causes of ignition. Intentional fires and those of unknown origin were found to have similar spatial aggregation patterns, and the presence of high ignition density areas was related to high population and high unemployment rates. Additionally, it was found that fires originated from forest work, agricultural activities, pasture burning, and lightning had a very specific behavior on their own, differing from the similarities found on the spatial aggregation of ignitions originated from smokers, electric lines, machinery, campfires, and those of intentional or unknown origin. PMID:25736559

  14. Regional flood frequency analysis using spatial proximity and basin characteristics: Quantile regression vs. parameter regression technique

    NASA Astrophysics Data System (ADS)

    Ahn, Kuk-Hyun; Palmer, Richard

    2016-09-01

    Despite wide use of regression-based regional flood frequency analysis (RFFA) methods, the majority are based on either ordinary least squares (OLS) or generalized least squares (GLS). This paper proposes 'spatial proximity' based RFFA methods using the spatial lagged model (SLM) and spatial error model (SEM). The proposed methods are represented by two frameworks: the quantile regression technique (QRT) and parameter regression technique (PRT). The QRT develops prediction equations for flooding quantiles in average recurrence intervals (ARIs) of 2, 5, 10, 20, and 100 years whereas the PRT provides prediction of three parameters for the selected distribution. The proposed methods are tested using data incorporating 30 basin characteristics from 237 basins in Northeastern United States. Results show that generalized extreme value (GEV) distribution properly represents flood frequencies in the study gages. Also, basin area, stream network, and precipitation seasonality are found to be the most effective explanatory variables in prediction modeling by the QRT and PRT. 'Spatial proximity' based RFFA methods provide reliable flood quantile estimates compared to simpler methods. Compared to the QRT, the PRT may be recommended due to its accuracy and computational simplicity. The results presented in this paper may serve as one possible guidepost for hydrologists interested in flood analysis at ungaged sites.

  15. Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

    NASA Astrophysics Data System (ADS)

    Erfanifard, Y.; Rezayan, F.

    2014-10-01

    Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

  16. Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry

    PubMed Central

    Ahmadi, Ali; Soori, Hamid; Mehrabi, Yadollah; Etemad, Koorosh

    2015-01-01

    Background: Myocardial infarction (MI) is a leading cause of mortality and morbidity in Iran. No spatial analysis of MI has been conducted to date. The present study was conducted to determine the pattern of MI incidence and to identify the associated factors in Iran by province. Materials and Methods: This study has two parts. One part is prospective and hospital-based, and the other part is an ecological study. In this study, the data of 20,750 new MI cases registered in Iranian Myocardial Infarction Registry in 2012 were used. For spatial analysis in global and local, spatial autocorrelation, Moran's I, Getis-Ord, and logistic regression models were used. Data were analyzed by Stata software and ArcGIS 9.3. Results: Based on autocorrelation coefficient, a specific pattern was observed in the distribution of MI incidence in different provinces (Moran's I: 0.75, P < 0.001). Spatial pattern of incidence was approximately the same in men and women. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran). Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned. Hypertension, smoking, and BMI contributed to clustering with, respectively, 2.36, 1.31, and 1.31 odds ratio. Conclusion: Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran. Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system. PMID:26487871

  17. Spatial analysis of drumlins within the Arran, Guelph, and Galt drumlin fields of southern Ontario, Canada

    NASA Astrophysics Data System (ADS)

    Maclachlan, John

    2016-04-01

    Reconstruction of former ice conditions and glacier dynamics in previously glaciated terrains requires understanding of the processes and controls on the development of subglacial landforms such as drumlins. This paper presents a quantitative analysis of the spatial distribution of drumlins identified from digital elevation model (DEM) data within three drumlin fields in southern Ontario, Canada (the Arran, Galt and Guelph drumlin fields) formed in the Late Wisconsin by the Ontario and Georgian Bay ice lobes of the Laurentide Ice Sheet. Detailed field description of a partially excavated drumlin within the Guelph drumlin field provides firther insight to compliment the geomorphometric analysis. Drumlins are identified and their morphological parameters documented using a computer-based process that allows direct comparison of forms within and between individual fields. Statistical analysis of the morphological characteristics and spatial distribution of drumlins within each of the three drumlin fields, using kernel density and nearest neighbour analysis, indicates that drumlins of particular types show distinct patterns of clustering that appear to be are related to several different factors including length of time under ice, bedrock topography, and ice velocity. Sediments exposed in an excavated drumlin within the Guelph drumlin field show a relatively undisturbed older fluvial or glaciofluvial crudely stratified sands draped by a thin veneer of coarse grained deformation till. This stratigraphy is similar to that described from modern drumlins in Iceland and is consistent with models of drumlin formation by subglacial deformation processes. The methodology of drumlin analysis can be applied to the study of any drumlin field with an adequate coverage of digital spatial data. The ability to consistently identify and characterize drumlin morphology and distribution will allow more objective and systematic comparison of these landforms both within and between

  18. Advanced Satellite Research Project: SCAR Research Database. Bibliographic analysis

    NASA Technical Reports Server (NTRS)

    Pelton, Joseph N.

    1991-01-01

    The literature search was provided to locate and analyze the most recent literature that was relevant to the research. This was done by cross-relating books, articles, monographs, and journals that relate to the following topics: (1) Experimental Systems - Advanced Communications Technology Satellite (ACTS), and (2) Integrated System Digital Network (ISDN) and Advance Communication Techniques (ISDN and satellites, ISDN standards, broadband ISDN, flame relay and switching, computer networks and satellites, satellite orbits and technology, satellite transmission quality, and network configuration). Bibliographic essay on literature citations and articles reviewed during the literature search task is provided.

  19. Nonlinear displacement analysis of advanced propeller structures using NASTRAN

    NASA Technical Reports Server (NTRS)

    Lawrence, C.; Kielb, R. E.

    1984-01-01

    The steady state displacements of a rotating advanced turboprop are computed using the geometrically nonlinear capabilities of COSMIC NASTRAN Rigid Format 4 and MSC NASTRAN Solution 64. A description of the modified Newton-Raphson algorithm used by Solution 64 and the iterative scheme used by Rigid Format 4 is provided. A representative advanced turboprop, SR3, was used for the study. Displacements for SR3 are computed for rotational speeds up to 10,000 rpm. The results show Solution 64 to be superior for computating displacements of flexible rotating structures. This is attributed to its ability to update the displacement dependent centrifugal force during the solution process.

  20. A comparative analysis of two highly spatially resolved European atmospheric emission inventories

    NASA Astrophysics Data System (ADS)

    Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

    2013-08-01

    A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES

  1. NASA World Wind: Infrastructure for Spatial Data

    NASA Technical Reports Server (NTRS)

    Hogan, Patrick

    2011-01-01

    The world has great need for analysis of Earth observation data, be it climate change, carbon monitoring, disaster response, national defense or simply local resource management. To best provide for spatial and time-dependent information analysis, the world benefits from an open standards and open source infrastructure for spatial data. In the spirit of NASA's motto "for the benefit of all" NASA invites the world community to collaboratively advance this core technology. The World Wind infrastructure for spatial data both unites and challenges the world for innovative solutions analyzing spatial data while also allowing absolute command and control over any respective information exchange medium.

  2. Advancing effects analysis for integrated, large-scale wildfire risk assessment.

    PubMed

    Thompson, Matthew P; Calkin, David E; Gilbertson-Day, Julie W; Ager, Alan A

    2011-08-01

    In this article, we describe the design and development of a quantitative, geospatial risk assessment tool intended to facilitate monitoring trends in wildfire risk over time and to provide information useful in prioritizing fuels treatments and mitigation measures. The research effort is designed to develop, from a strategic view, a first approximation of how both fire likelihood and intensity influence risk to social, economic, and ecological values at regional and national scales. Three main components are required to generate wildfire risk outputs: (1) burn probability maps generated from wildfire simulations, (2) spatially identified highly valued resources (HVRs), and (3) response functions that describe the effects of fire (beneficial or detrimental) on the HVR. Analyzing fire effects has to date presented a major challenge to integrated risk assessments, due to a limited understanding of the type and magnitude of changes wrought by wildfire to ecological and other nonmarket values. This work advances wildfire effects analysis, recognizing knowledge uncertainty and appropriately managing it through the use of an expert systems approach. Specifically, this work entailed consultation with 10 fire and fuels program management officials from federal agencies with fire management responsibilities in order to define quantitative resource response relationships as a function of fire intensity. Here, we demonstrate a proof-of-concept application of the wildland fire risk assessment tool, using the state of Oregon as a case study.

  3. VECTAN II: A computer program for the spatial analysis of the vectorcardiogram.

    PubMed

    Golden, D P; Hoffler, G W; Wolthuis, R A; Johnson, R L

    1975-07-01

    This paper presents the operation of a digital computer program, VECTAN II, for the spatial analysis of the vectorcardiogram (VCG). The program incorporates a unique waveform recognition algorithm based on the spatial vector length which has been shown to perform better than previous algorithms. The waveform analysis employed by the program considers the vectorcardiogram as a three dimensional entity rather than as scalar or planar representations. VECTAN II is designed chiefly to measure and quantify the VCG response of normal subjects to a controlled stress by analyzing one VCG complex every five seconds throughout a long experiment. The program has been used to analyzeom the NASA Johnson Space Center Cardiovascular Laboratory, from the pre- and postflight medical examinations of the Apollo 15, 16 and 17 crewmen, and from onboard Skylab experiments. PMID:1099164

  4. VECTAN II - A computer program for the spatial analysis of the vectorcardiogram

    NASA Technical Reports Server (NTRS)

    Golden, D. P., Jr.; Hoffler, G. W.; Johnson, R. L.; Wolthuis, R. A.

    1975-01-01

    This paper presents the operation of a digital computer program, VECTAN II, for the spatial analysis of the vectorcardiogram (VCG). The program incorporates a unique waveform recognition algorithm based on the spatial vector length which has been shown to perform better than previous algorithms. The waveform analysis employed by the program considers the vectorcardiogram as a three dimensional entity rather than as scalar or planar representations. VECTAN II is designed chiefly to measure and quantify the VCG response of normal subjects to a controlled stress by analyzing one VCG complex every five seconds throughout a long experiment. The program has been used to analyze data from the NASA Johnson Space Center Cardiovascular Laboratory, from the pre- and postflight medical examinations of the Apollo 15, 16 and 17 crewmen, and from onboard Skylab experiments.

  5. An analysis of spatial clustering and implications for wildlife management: a burrowing owl example.

    PubMed

    Fisher, Joshua B; Trulio, Lynne A; Biging, Gregory S; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley's K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley's K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses. PMID:17253092

  6. Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

    NASA Technical Reports Server (NTRS)

    Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

    2012-01-01

    An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

  7. An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

    NASA Astrophysics Data System (ADS)

    Fisher, Joshua B.; Trulio, Lynne A.; Biging, Gregory S.; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl ( Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.

  8. An analysis of spatial clustering and implications for wildlife management: a burrowing owl example.

    PubMed

    Fisher, Joshua B; Trulio, Lynne A; Biging, Gregory S; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley's K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley's K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.

  9. VECTAN II: A computer program for the spatial analysis of the vectorcardiogram.

    PubMed

    Golden, D P; Hoffler, G W; Wolthuis, R A; Johnson, R L

    1975-07-01

    This paper presents the operation of a digital computer program, VECTAN II, for the spatial analysis of the vectorcardiogram (VCG). The program incorporates a unique waveform recognition algorithm based on the spatial vector length which has been shown to perform better than previous algorithms. The waveform analysis employed by the program considers the vectorcardiogram as a three dimensional entity rather than as scalar or planar representations. VECTAN II is designed chiefly to measure and quantify the VCG response of normal subjects to a controlled stress by analyzing one VCG complex every five seconds throughout a long experiment. The program has been used to analyzeom the NASA Johnson Space Center Cardiovascular Laboratory, from the pre- and postflight medical examinations of the Apollo 15, 16 and 17 crewmen, and from onboard Skylab experiments.

  10. Design, analysis and test verification of advanced encapsulation systems

    NASA Technical Reports Server (NTRS)

    Garcia, A., III

    1983-01-01

    The analytical methodology for advanced encapsulation designs for the development of photovoltaic modules is presented. Analytical models are developed to test optical, thermal, electrical and structural properties of the various encapsulation systems. Model data is compared to relevant test data to improve model accuracy and develop general principles for the design of photovoltaic modules.

  11. A Simultaneous Analysis Problem for Advanced General Chemistry Laboratories.

    ERIC Educational Resources Information Center

    Leary, J. J.; Gallaher, T. N.

    1983-01-01

    Oxidation of magnesium metal in air has been used as an introductory experiment for determining the formula of a compound. The experiment described employs essentially the same laboratory procedure but is significantly more advanced in terms of information sought. Procedures and sample calculations/results are provided. (JN)

  12. Strategy and software for the statistical spatial analysis of 3D intracellular distributions.

    PubMed

    Biot, Eric; Crowell, Elizabeth; Burguet, Jasmine; Höfte, Herman; Vernhettes, Samantha; Andrey, Philippe

    2016-07-01

    The localization of proteins in specific domains or compartments in the 3D cellular space is essential for many fundamental processes in eukaryotic cells. Deciphering spatial organization principles within cells is a challenging task, in particular because of the large morphological variations between individual cells. We present here an approach for normalizing variations in cell morphology and for statistically analyzing spatial distributions of intracellular compartments from collections of 3D images. The method relies on the processing and analysis of 3D geometrical models that are generated from image stacks and that are used to build representations at progressively increasing levels of integration, ultimately revealing statistical significant traits of spatial distributions. To make this methodology widely available to end-users, we implemented our algorithmic pipeline into a user-friendly, multi-platform, and freely available software. To validate our approach, we generated 3D statistical maps of endomembrane compartments at subcellular resolution within an average epidermal root cell from collections of image stacks. This revealed unsuspected polar distribution patterns of organelles that were not detectable in individual images. By reversing the classical 'measure-then-average' paradigm, one major benefit of the proposed strategy is the production and display of statistical 3D representations of spatial organizations, thus fully preserving the spatial dimension of image data and at the same time allowing their integration over individual observations. The approach and software are generic and should be of general interest for experimental and modeling studies of spatial organizations at multiple scales (subcellular, cellular, tissular) in biological systems.

  13. Spatial analysis of PM10 and cardiovascular mortality in the Seoul metropolitan area

    PubMed Central

    Lim, Yu-Ra; Bae, Hyun-Joo; Lim, Youn-Hee; Yu, Seungdo; Kim, Geun-Bae; Cho, Yong-Sung

    2014-01-01

    Objectives Numerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than 10 μm in aerodynamic diameter (PM10). The aim of the present study was to examine the spatial distribution of PM10 concentrations and cardiovascular mortality and to investigate the spatial correlation between PM10 and cardiovascular mortality using spatial scan statistic (SaTScan) and a regression model. Methods From 2008 to 2010, the spatial distribution of PM10 in the Seoul metropolitan area was examined via kriging. In addition, a group of cardiovascular mortality cases was analyzed using SaTScan-based cluster exploration. Geographically weighted regression (GWR) was applied to investigate the correlation between PM10 concentrations and cardiovascular mortality. Results An examination of the regional distribution of the cardiovascular mortality was higher in provincial districts (gu) belonging to Incheon and the northern part of Gyeonggido than in other regions. In a comparison of PM10 concentrations and mortality cluster (MC) regions, all those belonging to MC 1 and MC 2 were found to belong to particulate matter (PM) 1 and PM 2 with high concentrations of air pollutants. In addition, the GWR showed that PM10 has a statistically significant relation to cardiovascular mortality. Conclusions To investigate the relation between air pollution and health impact, spatial analyses can be utilized based on kriging, cluster exploration, and GWR for a more systematic and quantitative analysis. It has been proven that cardiovascular mortality is spatially related to the concentration of PM10. PMID:25116367

  14. Helmintic infections in water buffaloes on Italian farms: a spatial analysis.

    PubMed

    Rinaldi, Laura; Musella, Vincenzo; Veneziano, Vincenzo; Condoleo, Renato U; Cringoli, Giuseppe

    2009-05-01

    The present paper reports the results of a cross-sectional survey aimed at obtaining up-to-date information on the spatial distribution of different groups and/or species of helminths in water buffaloes from central Italy. Geographical information systems (GIS) and spatial analysis were used to plan the sampling procedures, to display the results as maps and to detect spatial clusters of helminths in the study area. The survey was conducted on 127 water buffalo farms, which were selected in the study area using a grid sampling approach, followed by proportional allocation. Faecal samples (n. = 1,883) collected from the 127 farms were examined using the Flotac dual technique. Gastrointestinal strongyles were the most frequent helminths (33.1%) on the tested farms, followed by the liver fluke Fasciola hepatica (7.1%), the rumen fluke Calicophoron daubneyi (7.1%), the nematode Strongyloides spp. (3.1%), the lancet liver fluke Dicrocoelium dendriticum (2.4%) and the tapeworm Moniezia spp. (2.4%). In order to display the spatial distribution of the various helminths detected on the water buffalo farms (used as epidemiological unit in our study), point maps were drawn within the GIS. In addition, for each helminth, clustering of test-positive farms were investigated based on location determined by exact coordinates. Using spatial scan statistic, spatial clusters were found for the flukes F. hepatica and C. daubneyi and the cestode Moniezia spp.; these findings are consistent with the life cycle of these parasites, which have strong environmental determinants. In conclusion, the present study demonstrated that, with the appropriate survey-based data at hand, GIS is a useful tool to study epidemiological patterns of infections in veterinary health, in particular in water buffaloes.

  15. Advanced demodulation technique for the extraction of tissue optical properties and structural orientation contrast in the spatial frequency domain

    PubMed Central

    Nadeau, Kyle P.; Durkin, Anthony J.; Tromberg, Bruce J.

    2014-01-01

    Abstract. We have developed a method for extracting spatial frequency information content from biological tissue, which is used to calculate tissue optical properties and determine tissue structural orientation. This demodulation method employs a two-dimensional Hilbert transform using a spiral phase function in Fourier space. The approach presented here allows for the determination of tissue optical properties using a single frame of data for each modulation frequency, increasing imaging speed by two to threefold versus conventional, three-phase spatial frequency domain imaging (SFDI). This new single-phase Hilbert transform approach recovers optical property and scattering orientation index values within 1% and 10% of three-phase SFDI, respectively. These results suggest that, using the Hilbert demodulation technique, SFDI data acquisition speed can be increased significantly while preserving data quality, which will help us move forward toward the implementation of a real-time SFDI platform. PMID:24858131

  16. Frames of reference for helicopter electronic maps - The relevance of spatial cognition and componential analysis

    NASA Technical Reports Server (NTRS)

    Harwood, Kelly; Wickens, Christopher D.

    1991-01-01

    Computer-generated map displays for NOE and low-level helicopter flight were formed according to prior research on maps, navigational problem solving, and spatial cognition in large-scale environments. The north-up map emphasized consistency of object location, wheareas, the track-up map emphasized map-terrain congruency. A component analysis indicates that different cognitive components, e.g., orienting and absolute object location, are supported to varying degrees by properties of different frames of reference.

  17. A tool for the quantitative spatial analysis of mammary gland epithelium

    SciTech Connect

    Ortiz de Solorzano, Carlos; Fernandez-Gonzalez, Rodrigo

    2004-04-09

    In this paper we present a method for the spatial analysis of complex cellular systems based on a multiscale study of neighborhood relationships. A function to measure those relationships, M, is introduced. The refined Relative Neighborhood Graph is then presented as a method to establish vicinity relationships within layered cellular structures, and particularized to epithelial cell nuclei in the mammary gland. Finally, the method is illustrated with two examples that show interactions within one population of epithelial cells and between two different populations.

  18. The spatial metaphor of Utopia in Russian culture and in analysis.

    PubMed

    Tsivinsky, Vladimir

    2014-02-01

    The spatial metaphor of Utopia is considered from a Jungian perspective along with its role in Russian culture and in analysis. Such post-Jungian concepts as the cultural complex and the archetypal story pattern of a victim are used in considering the desperate longing for a rescuer in patients' narratives and in Russian society. A clinical vignette is provided to illustrate these ideas. PMID:24467352

  19. Preliminary spatial analysis of combined BATSE/Ulysses gamma-ray burst locations

    SciTech Connect

    Kippen, R. Marc; Hurley, Kevin; Pendleton, Geoffrey N.

    1998-05-16

    We present the preliminary spatial analysis of 278 bursts that have been localized by BATSE and the two-spacecraft Compton/Ulysses Interplanetary Network. The large number and superior accuracy of the combined BATSE/Ulysses locations provides improved sensitivity to small-angle source properties. We find that the locations are consistent with large- and small-scale isotropy, with no significant small-angle clustering. We constrain the fraction of sources in clusters and discuss the implications for burst repetition.

  20. Spatial landscape evolution analysis of dike-pond in Foshan City based on RS and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Mo; Wang, Longchao; Zhao, Yong

    2008-10-01

    Dike-pond system is one of the most tradition agriculture with local characteristics in the Pearl River Delta. This study selects Foshan city in the Pearl River Delta as study area. Three temporal Landsat TM images are used to monitoring the area changes of dike-pond system with Remote Sensing techniques in the last two decades. Discussing the spatial landscape evolution characteristics of dike-pond system integrated GIS techniques and statistics analysis method.

  1. A Behavioral Analysis of Spatial Neglect and its Recovery After Stroke

    PubMed Central

    Rengachary, Jennifer; He, Biyu J.; Shulman, Gordon L.; Corbetta, Maurizio

    2011-01-01

    In a longitudinal study of recovery of left neglect following stroke using reaction time computerized assessment, we find that lateralized spatial deficits of attention and perception to be more severe than disturbance of action. Perceptual-attention deficits also show the most variability in the course of recovery, making them prime candidates for intervention. In an anatomical analysis of MRI findings, ventral frontal cortex damage was correlated with the most severe neglect, reflecting impaired fronto-parietal communication. PMID:21519374

  2. Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

    NASA Technical Reports Server (NTRS)

    Newman, Perry A.; Hou, Gene J. W.; Taylor, Arthur C., III

    1996-01-01

    Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

  3. Integrating Advanced High School Chemistry Research with Organic Chemistry and Instrumental Methods of Analysis

    ERIC Educational Resources Information Center

    Kennedy, Brian J.

    2008-01-01

    This paper describes and discusses the unique chemistry course opportunities beyond the advanced placement-level available at a science and technology magnet high school. Students may select entry-level courses such as honors and advanced placement chemistry; they may also take electives in organic chemistry with instrumental methods of analysis;…

  4. Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

    USGS Publications Warehouse

    Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

    2003-01-01

    We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

  5. An integrated analysis-synthesis array system for spatial sound fields.

    PubMed

    Bai, Mingsian R; Hua, Yi-Hsin; Kuo, Chia-Hao; Hsieh, Yu-Hao

    2015-03-01

    An integrated recording and reproduction array system for spatial audio is presented within a generic framework akin to the analysis-synthesis filterbanks in discrete time signal processing. In the analysis stage, a microphone array "encodes" the sound field by using the plane-wave decomposition. Direction of arrival of plane-wave components that comprise the sound field of interest are estimated by multiple signal classification. Next, the source signals are extracted by using a deconvolution procedure. In the synthesis stage, a loudspeaker array "decodes" the sound field by reconstructing the plane-wave components obtained in the analysis stage. This synthesis stage is carried out by pressure matching in the interior domain of the loudspeaker array. The deconvolution problem is solved by truncated singular value decomposition or convex optimization algorithms. For high-frequency reproduction that suffers from the spatial aliasing problem, vector panning is utilized. Listening tests are undertaken to evaluate the deconvolution method, vector panning, and a hybrid approach that combines both methods to cover frequency ranges below and above the spatial aliasing frequency. Localization and timbral attributes are considered in the subjective evaluation. The results show that the hybrid approach performs the best in overall preference. In addition, there is a trade-off between reproduction performance and the external radiation.

  6. Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method

    NASA Astrophysics Data System (ADS)

    Cheng, Haiying; Yan, Yumei; Duong, Timothy Q.

    2009-02-01

    Noninvasive monitoring of blood flow in retinal circulation will reveal the progression and treatment of ocular disorders, such as diabetic retinopathy, age-related macular degeneration and glaucoma. A non-invasive and direct BF measurement technique with high spatial-temporal resolution is needed for retinal imaging. Laser speckle imaging (LSI) is such a method. Currently, there are two analysis methods for LSI: spatial statistics LSI (SS-LSI) and temporal statistical LSI (TS-LSI). Comparing these two analysis methods, SS-LSI has higher signal to noise ratio (SNR) and TSLSI is less susceptible to artifacts from stationary speckle. We proposed a hybrid temporal and spatial analysis method (HTS-LSI) to measure the retinal blood flow. Gas challenge experiment was performed and images were analyzed by HTS-LSI. Results showed that HTS-LSI can not only remove the stationary speckle but also increase the SNR. Under 100% O2, retinal BF decreased by 20-30%. This was consistent with the results observed with laser Doppler technique. As retinal blood flow is a critical physiological parameter and its perturbation has been implicated in the early stages of many retinal diseases, HTS-LSI will be an efficient method in early detection of retina diseases.

  7. A spatially explicit analysis of seedling recruitment in the terrestrial orchid Orchis purpurea.

    PubMed

    Jacquemyn, Hans; Brys, Rein; Vandepitte, Katrien; Honnay, Olivier; Roldán-Ruiz, Isabel; Wiegand, Thorsten

    2007-01-01

    Seed dispersal and the subsequent recruitment of new individuals into a population are important processes affecting the population dynamics, genetic diversity and spatial genetic structure of plant populations. Spatial patterns of seedling recruitment were investigated in two populations of the terrestrial orchid Orchis purpurea using both univariate and bivariate point pattern analysis, parentage analysis and seed germination experiments. Both adults and recruits showed a clustered spatial distribution with cluster radii of c. 4-5 m. The parentage analysis resulted in offspring-dispersal distances that were slightly larger than distances obtained from the point pattern analyses. The suitability of microsites for germination differed among sites, with strong constraints in one site and almost no constraints in the other. These results provide a clear and coherent picture of recruitment patterns in a tuberous, perennial orchid. Seed dispersal is limited to a few metres from the mother plant, whereas the availability of suitable germination conditions may vary strongly from one site to the next. Because of a time lag of 3-4 yr between seed dispersal and actual recruitment, and irregular flowering and fruiting patterns of adult plants, interpretation of recruitment patterns using point patterns analyses ideally should take into account the demographic properties of orchid populations.

  8. An integrated analysis-synthesis array system for spatial sound fields.

    PubMed

    Bai, Mingsian R; Hua, Yi-Hsin; Kuo, Chia-Hao; Hsieh, Yu-Hao

    2015-03-01

    An integrated recording and reproduction array system for spatial audio is presented within a generic framework akin to the analysis-synthesis filterbanks in discrete time signal processing. In the analysis stage, a microphone array "encodes" the sound field by using the plane-wave decomposition. Direction of arrival of plane-wave components that comprise the sound field of interest are estimated by multiple signal classification. Next, the source signals are extracted by using a deconvolution procedure. In the synthesis stage, a loudspeaker array "decodes" the sound field by reconstructing the plane-wave components obtained in the analysis stage. This synthesis stage is carried out by pressure matching in the interior domain of the loudspeaker array. The deconvolution problem is solved by truncated singular value decomposition or convex optimization algorithms. For high-frequency reproduction that suffers from the spatial aliasing problem, vector panning is utilized. Listening tests are undertaken to evaluate the deconvolution method, vector panning, and a hybrid approach that combines both methods to cover frequency ranges below and above the spatial aliasing frequency. Localization and timbral attributes are considered in the subjective evaluation. The results show that the hybrid approach performs the best in overall preference. In addition, there is a trade-off between reproduction performance and the external radiation. PMID:25786949

  9. Advanced wavefront measurement and analysis of laser system modeling

    SciTech Connect

    Wolfe, C.R.; Auerback, J.M.

    1994-11-15

    High spatial resolution measurements of the reflected or transmitted wavefronts of large aperture optical components used in high peak power laser systems is now possible. These measurements are produced by phase shifting interferometry. The wavefront data is in the form of 3-D phase maps that reconstruct the wavefront shape. The emphasis of this work is on the characterization of wavefront features in the mid-spatial wavelength range (from 0.1 to 10.0 mm) and has been accomplished for the first time. Wavefront structure from optical components with spatial wavelengths in this range are of concern because their effects in high peak power laser systems. At high peak power, this phase modulation can convert to large magnitude intensity modulation by non-linear processes. This can lead to optical damage. We have developed software to input the measured phase map data into beam propagation codes in order to model this conversion process. We are analyzing this data to: (1) Characterize the wavefront structure produced by current optical components, (2) Refine our understanding of laser system performance, (3) Develop a database from which future optical component specifications can be derived.

  10. Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high

  11. Recent advances in microchip electrophoresis for amino acid analysis.

    PubMed

    Ou, Gaozhi; Feng, Xiaojun; Du, Wei; Liu, Xin; Liu, Bi-Feng

    2013-10-01

    With the maturation of microfluidic technologies, microchip electrophoresis has been widely employed for amino acid analysis owing to its advantages of low sample consumption, reduced analysis time, high throughput, and potential for integration and automation. In this article, we review the recent progress in amino acid analysis using microchip electrophoresis during the period from 2007 to 2012. Innovations in microchip materials, surface modification, sample introduction, microchip electrophoresis, and detection methods are documented, as well as nascent applications of amino acid analysis in single-cell analysis, microdialysis sampling, food analysis, and extraterrestrial exploration. Without doubt, more applications of microchip electrophoresis in amino acid analysis may be expected soon.

  12. Recent advances in microchip electrophoresis for amino acid analysis.

    PubMed

    Ou, Gaozhi; Feng, Xiaojun; Du, Wei; Liu, Xin; Liu, Bi-Feng

    2013-10-01

    With the maturation of microfluidic technologies, microchip electrophoresis has been widely employed for amino acid analysis owing to its advantages of low sample consumption, reduced analysis time, high throughput, and potential for integration and automation. In this article, we review the recent progress in amino acid analysis using microchip electrophoresis during the period from 2007 to 2012. Innovations in microchip materials, surface modification, sample introduction, microchip electrophoresis, and detection methods are documented, as well as nascent applications of amino acid analysis in single-cell analysis, microdialysis sampling, food analysis, and extraterrestrial exploration. Without doubt, more applications of microchip electrophoresis in amino acid analysis may be expected soon. PMID:23436170

  13. The emergence of spatial cyberinfrastructure.

    PubMed

    Wright, Dawn J; Wang, Shaowen

    2011-04-01

    Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge. PMID:21467227

  14. Spatial and sampling analysis for a sensor viewing a pixelized projector

    NASA Astrophysics Data System (ADS)

    Sieglinger, Breck A.; Flynn, David S.; Coker, Charles F.

    1997-07-01

    This paper presents an analysis of spatial blurring and sampling effects for a sensor viewing a pixelized scene projector. It addresses the ability of a projector to simulate an arbitrary continuous radiance scene using a field of discrete elements. The spatial fidelity of the projector as seen by an imaging sensor is shown to depend critically on the width of the sensor MTF or spatial response function, and the angular spacing between projector pixels. Quantitative results are presented based on a simulation that compares the output of a sensor viewing a reference scene to the output of the sensor viewing a projector display of the reference scene. Dependence on the blur of the sensor and projector, the scene content, and alignment both of features in the scene and sensor samples with the projector pixel locations are addressed. We attempt to determine the projector characteristics required to perform hardware-in-the-loop testing with adequate spatial realism to evaluate seeker functions like autonomous detection, measuring radiant intensities and angular positions or unresolved objects, or performing autonomous recognition and aimpoint selection for resolved objects.

  15. Spatial-Temporal Epidemiology of Tuberculosis in Mainland China: An Analysis Based on Bayesian Theory

    PubMed Central

    Cao, Kai; Yang, Kun; Wang, Chao; Guo, Jin; Tao, Lixin; Liu, Qingrong; Gehendra, Mahara; Zhang, Yingjie; Guo, Xiuhua

    2016-01-01

    Objective: To explore the spatial-temporal interaction effect within a Bayesian framework and to probe the ecological influential factors for tuberculosis. Methods: Six different statistical models containing parameters of time, space, spatial-temporal interaction and their combination were constructed based on a Bayesian framework. The optimum model was selected according to the deviance information criterion (DIC) value. Coefficients of climate variables were then estimated using the best fitting model. Results: The model containing spatial-temporal interaction parameter was the best fitting one, with the smallest DIC value (−4,508,660). Ecological analysis results showed the relative risks (RRs) of average temperature, rainfall, wind speed, humidity, and air pressure were 1.00324 (95% CI, 1.00150–1.00550), 1.01010 (95% CI, 1.01007–1.01013), 0.83518 (95% CI, 0.93732–0.96138), 0.97496 (95% CI, 0.97181–1.01386), and 1.01007 (95% CI, 1.01003–1.01011), respectively. Conclusions: The spatial-temporal interaction was statistically meaningful and the prevalence of tuberculosis was influenced by the time and space interaction effect. Average temperature, rainfall, wind speed, and air pressure influenced tuberculosis. Average humidity had no influence on tuberculosis. PMID:27164117

  16. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather.

    PubMed

    Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

    2013-09-01

    Concurrently high values of the maximum potential wind speed of updrafts (W max) and 0-6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

  17. Analysis of the community structure of abyssal kinetoplastids revealed similar communities at larger spatial scales

    PubMed Central

    Salani, Faezeh Shah; Arndt, Hartmut; Hausmann, Klaus; Nitsche, Frank; Scheckenbach, Frank

    2012-01-01

    Knowledge of the spatial scales of diversity is necessary to evaluate the mechanisms driving biodiversity and biogeography in the vast but poorly understood deep sea. The community structure of kinetoplastids, an important group of microbial eukaryotes belonging to the Euglenozoa, from all abyssal plains of the South Atlantic and two areas of the eastern Mediterranean was studied using partial small subunit ribosomal DNA gene clone libraries. A total of 1364 clones from 10 different regions were retrieved. The analysis revealed statistically not distinguishable communities from both the South-East Atlantic (Angola and Guinea Basin) and the South-West Atlantic (Angola and Brazil Basin) at spatial scales of 1000–3000 km, whereas all other communities were significantly differentiated from one another. It seems likely that multiple processes operate at the same time to shape communities of deep-sea kinetoplastids. Nevertheless, constant and homogenous environmental conditions over large spatial scales at abyssal depths, together with high dispersal capabilities of microbial eukaryotes, maintain best the results of statistically indistinguishable communities at larger spatial scales. PMID:22071346

  18. Time-dependent analysis of 8 days of CN spatial profiles in comet P/Halley

    NASA Technical Reports Server (NTRS)

    Combi, Michael; Huang, Bormin; Cochran, Anita; Fink, Uwe; Schulz, Rita

    1994-01-01

    CN profiles in comet P/Halley were constructed from observations taken at three observatories during an 8 day period in April 1986. These data provide a time series of CN spatial profiles spanning just over one 7.37 day period from 1986 April 7 to April 15 and sample distances from the nucleus from just over 10(exp 3) km to 10(exp 6) km. The effect of the 7.37 day periodic variation on the CN distribution in P/Halley has been examined by using the time-dependent model applied earlier to a subset of the data. Because of the large spatial scale of the data on April 7, 8, and 9 (approx. 10(exp 6) km), and the corresponding transport time in the coma, information present in the spatial profiles regarding the gas production rate actually covers nearly two full periods. These spatially extended profiles clearly show the wavy structures outside 10(exp 5) km. Such structures were predicted in a previous analysis (Combi & Fink 1993) that was based solely on the photometric light curve and on profiles which only extended to distances less than 10(exp 5) km. We are now able to reproduce the highly variable Halley correction for the variation in gas production rate.

  19. Mean field analysis of a spatial stochastic model of a gene regulatory network.

    PubMed

    Sturrock, M; Murray, P J; Matzavinos, A; Chaplain, M A J

    2015-10-01

    A gene regulatory network may be defined as a collection of DNA segments which interact with each other indirectly through their RNA and protein products. Such a network is said to contain a negative feedback loop if its products inhibit gene transcription, and a positive feedback loop if a gene product promotes its own production. Negative feedback loops can create oscillations in mRNA and protein levels while positive feedback loops are primarily responsible for signal amplification. It is often the case in real biological systems that both negative and positive feedback loops operate in parameter regimes that result in low copy numbers of gene products. In this paper we investigate the spatio-temporal dynamics of a single feedback loop in a eukaryotic cell. We first develop a simplified spatial stochastic model of a canonical feedback system (either positive or negative). Using a Gillespie's algorithm, we compute sample trajectories and analyse their corresponding statistics. We then derive a system of equations that describe the spatio-temporal evolution of the stochastic means. Subsequently, we examine the spatially homogeneous case and compare the results of numerical simulations with the spatially explicit case. Finally, using a combination of steady-state analysis and data clustering techniques, we explore model behaviour across a subregion of the parameter space that is difficult to access experimentally and compare the parameter landscape of our spatio-temporal and spatially-homogeneous models.

  20. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

    PubMed Central

    Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

    2013-01-01

    Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

  1. Socio-Demographic Predictors and Distribution of Pulmonary Tuberculosis (TB) in Xinjiang, China: A Spatial Analysis

    PubMed Central

    Wubuli, Atikaimu; Xue, Feng; Jiang, Daobin; Yao, Xuemei; Upur, Halmurat; Wushouer, Qimanguli

    2015-01-01

    Objectives Xinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions. Methods Numbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran’s I statistic. Anselin’s local Moran’s I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis. Results Incidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin’s Local Moran’s I identified the “hotspots” which were consistently located in the southwest regions composed of 20 to 28 districts, and the “coldspots” which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of “hotspots” and “coldspots” with different intensity; 30 county/districts clustered as “hotspots”, while 47 county/districts clustered as

  2. An advanced structural analysis/synthesis capability - ACCESS 2

    NASA Technical Reports Server (NTRS)

    Schmit, L. A.; Miura, H.

    1976-01-01

    An advanced automated design procedure for minimum-weight design of structures (ACCESS 2) is reported. Design variable linking, constraint deletion, and explicit constraint approximation are used to combine effectively finite-element and nonlinear mathematical programming techniques. The approximation-concepts approach to structural synthesis is extended to problems involving fiber composite structure, thermal effects, and natural frequency constraints in addition to the usual static stress and displacement limitations. Sample results illustrating these features are given.

  3. An advanced structural analysis/synthesis capability - ACCESS 2

    NASA Technical Reports Server (NTRS)

    Schmit, L. A.; Miura, H.

    1978-01-01

    An advanced automated design procedure for minimum weight design of structures (ACCESS 2) is reported. Design variable linking, constraint deletion, and explicit constraint approximation are used to effectively combine finite element and nonlinear mathematical programming techniques. The approximation concepts approach to structural synthesis is extended to problems involving fiber composite structure, thermal effects and natural frequency constraints in addition to the usual static stress and displacement limitations. Sample results illustrating these new features are given.

  4. Structural response of an advanced combustor liner: Test and analysis

    NASA Technical Reports Server (NTRS)

    Moorhead, Paul E.; Thompson, Robert L.; Tong, M.; Higgins, M.

    1987-01-01

    An advanced (segmented) combustor liner supplied by Pratt and Whitney Aircraft was tested in the structural component test rig at Lewis Research Center. It was found that the segmented liner operated at much lower temperatures than the conventional liner (about 400 F lower) for the same heat flux. At the lower temperatures and low thermal gradients, little distortion to the segments was observed. The operating conditions were not severe enough to distort or damage the segmented liner.

  5. Spatial and temporal analysis of DIII-D 3D magnetic diagnostic data

    NASA Astrophysics Data System (ADS)

    Strait, E. J.; King, J. D.; Hanson, J. M.; Logan, N. C.

    2016-11-01

    An extensive set of magnetic diagnostics in DIII-D is aimed at measuring non-axisymmetric "3D" features of tokamak plasmas, with typical amplitudes ˜10-3 to 10-5 of the total magnetic field. We describe hardware and software techniques used at DIII-D to condition the individual signals and analysis to estimate the spatial structure from an ensemble of discrete measurements. Applications of the analysis include detection of non-rotating MHD instabilities, plasma control, and validation of MHD stability and 3D equilibrium models.

  6. Spatio-Temporal Analysis of UHI using Geo-Spatial Techniques: A case study of Ahmedabad

    NASA Astrophysics Data System (ADS)

    Vyas, A.; Shastri, B.; Joshi, Y.

    2014-11-01

    vulnerabilities to human health, the marginal population affected largely as the natural environment is their only home or their main shelter. Furthermore elderly people also affected in greater amount as their weakening immunes system. Major effects of UHI on environment include: a) Air Quality, b) Energy consumption and c) Human health. To study the causes and effect of UHI of any urban area, the first step is to demarcate the spatial distribution of UHI and its intensity over different time period of the day as well as difference in the temperature of urban area with the surrounding rural areas. Secondly, study of land use land cover change in the area also helps in identifying causes of heat accumulation for particular region. After marking up of intensity, analysis of different zones for understanding the relationship between UHI and urban morphological features can be done which further became suggestive towards planning of urban center that mitigates the effect of UHI. Mainly two approaches are there to demarcate UHI study as: - Field data collection and observations - Remote sensing data analysis For a long period of time observations from interior of the city and outwards of it can analyze by a climatic methods, by observing many days as well as many times of a day continuously to analyze the daily variation law of the heat island effects. As the city is for its developmental approaches may cover an area of hundreds of square kilometers, the ground observation data is not able to provide enough detail about the urban heat island distribution characteristics. The most precise method is the Satellite Remote Sensing method. The UHI phenomenon can be analyzed by using the thermal infrared data obtained meteorological satellite sensing. The atmospheric attenuation can be corrected for the remote sensing data by use of meteorological soundings and ground observation data. Ideally the heat island effect over a city is not same for any other city. Satellite images from AVHRR

  7. Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

    NASA Astrophysics Data System (ADS)

    Rupa, Chandra; Mujumdar, Pradeep

    2016-04-01

    In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings

  8. Bayesian analysis of spatially-dependent functional responses with spatially-dependent multi-dimensional functional predictors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in technology have led to the collection of high-dimensional data not previously encountered in many scientific environments. As a result, scientists are often faced with the challenging task of including these high-dimensional data into statistical models. For example, data from sen...

  9. The Third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization was held on 24-26 Sept. 1990. Sessions were on the following topics: dynamics and controls; multilevel optimization; sensitivity analysis; aerodynamic design software systems; optimization theory; analysis and design; shape optimization; vehicle components; structural optimization; aeroelasticity; artificial intelligence; multidisciplinary optimization; and composites.

  10. Regional land salinization assessment and simulation through cellular automaton-Markov modeling and spatial pattern analysis.

    PubMed

    Zhou, De; Lin, Zhulu; Liu, Liming

    2012-11-15

    Land salinization and desalinization are complex processes affected by both biophysical and human-induced driving factors. Conventional approaches of land salinization assessment and simulation are either too time consuming or focus only on biophysical factors. The cellular automaton (CA)-Markov model, when coupled with spatial pattern analysis, is well suited for regional assessments and simulations of salt-affected landscapes since both biophysical and socioeconomic data can be efficiently incorporated into a geographic information system framework. Our hypothesis set forth that the CA-Markov model can serve as an alternative tool for regional assessment and simulation of land salinization or desalinization. Our results suggest that the CA-Markov model, when incorporating biophysical and human-induced factors, performs better than the model which did not account for these factors when simulating the salt-affected landscape of the Yinchuan Plain (China) in 2009. In general, the CA-Markov model is best suited for short-term simulations and the performance of the CA-Markov model is largely determined by the availability of high-quality, high-resolution socioeconomic data. The coupling of the CA-Markov model with spatial pattern analysis provides an improved understanding of spatial and temporal variations of salt-affected landscape changes and an option to test different soil management scenarios for salinity management.

  11. Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis.

    PubMed

    Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Jiang, Baofa

    2016-04-01

    The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77-7.61), diarrhea (OR = 2.16, 95% CI = 1.24-3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04-35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region. PMID:26903612

  12. Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

    USGS Publications Warehouse

    ,

    2009-01-01

    Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is useful for analyzing a wide variety of spatial data. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This fact sheet presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup during 2008 and 2009. After a summary of GIS Workgroup capabilities, brief descriptions of activities by project at the local and national levels are presented. Projects are grouped by the fiscal year (October-September 2008 or 2009) the project ends and include overviews, project images, and Internet links to additional project information and related publications or articles.

  13. Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

    NASA Astrophysics Data System (ADS)

    Gaitan, S.; ten Veldhuis, J. A. E.

    2015-06-01

    Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

  14. Do the Most Vulnerable People Live in the Worst Slums? A Spatial Analysis of Accra, Ghana

    PubMed Central

    Jankowska, Marta M.; Weeks, John R.; Engstrom, Ryan

    2011-01-01

    Slums are examples of localized communities within third world urban systems representing a range of vulnerabilities and adaptive capacities. This study examines vulnerability in relation to flooding, environmental degradation, social-status, demographics, and health in the slums of Accra, Ghana by utilizing a place-based approach informed by fieldwork, remote sensing, census data, and geographically weighted regression. The study objectives are threefold: (1) to move slums from a dichotomous into a continuous classification and examine the spatial patterns of the gradient, (2) develop measures of vulnerability for a developing world city and model the relationship between slums and vulnerability, and (3) to assess if the most vulnerable individuals live in the worst slums. A previously developed slum index is utilized, and four new measures of vulnerability are developed through principle components analysis, including a novel component of health vulnerability based on child mortality. Visualizations of the vulnerability measures assess spatial patterns of vulnerability in Accra. Ordinary least squares, spatial, and geographically weighted regression model the ability of the slum index to predict the four vulnerability measures. The slum index performs well for three of the four vulnerability measures, but is least able to predict health vulnerability underscoring the complex relationship between slums and child mortality in Accra. Finally, quintile analysis demonstrates the elevated prevalence of high vulnerability in places with high slum index scores. PMID:22379509

  15. Regional land salinization assessment and simulation through cellular automaton-Markov modeling and spatial pattern analysis.

    PubMed

    Zhou, De; Lin, Zhulu; Liu, Liming

    2012-11-15

    Land salinization and desalinization are complex processes affected by both biophysical and human-induced driving factors. Conventional approaches of land salinization assessment and simulation are either too time consuming or focus only on biophysical factors. The cellular automaton (CA)-Markov model, when coupled with spatial pattern analysis, is well suited for regional assessments and simulations of salt-affected landscapes since both biophysical and socioeconomic data can be efficiently incorporated into a geographic information system framework. Our hypothesis set forth that the CA-Markov model can serve as an alternative tool for regional assessment and simulation of land salinization or desalinization. Our results suggest that the CA-Markov model, when incorporating biophysical and human-induced factors, performs better than the model which did not account for these factors when simulating the salt-affected landscape of the Yinchuan Plain (China) in 2009. In general, the CA-Markov model is best suited for short-term simulations and the performance of the CA-Markov model is largely determined by the availability of high-quality, high-resolution socioeconomic data. The coupling of the CA-Markov model with spatial pattern analysis provides an improved understanding of spatial and temporal variations of salt-affected landscape changes and an option to test different soil management scenarios for salinity management. PMID:23085467

  16. Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis.

    PubMed

    Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Jiang, Baofa

    2016-04-01

    The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77-7.61), diarrhea (OR = 2.16, 95% CI = 1.24-3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04-35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region.

  17. Capturing multiple values of ecosystem services shaped by environmental worldviews: a spatial analysis.

    PubMed

    Van Riper, Carena J; Kyle, Gerard T

    2014-12-01

    Two related approaches to valuing nature have been advanced in past research including the study of ecosystem services and psychological investigations of the factors that shape behavior. Stronger integration of the insights that emerge from these two lines of enquiry can more effectively sustain ecosystems, economies, and human well-being. Drawing on survey data collected from outdoor recreationists on Santa Cruz Island within Channel Islands National Park, U.S., our study blends these two research approaches to examine a range of tangible and intangible values of ecosystem services provided to stakeholders with differing biocentric and anthropocentric worldviews. We used Public Participation Geographic Information System methods to collect survey data and a Social Values for Ecosystem Services mapping application to spatially analyze a range of values assigned to terrestrial and aquatic ecosystems in the park. Our results showed that preferences for the provision of biological diversity, recreation, and scientific-based values of ecosystem services varied across a spatial gradient. We also observed differences that emerged from a comparison between survey subgroups defined by their worldviews. The implications emanating from this investigation aim to support environmental management decision-making in the context of protected areas. PMID:25124790

  18. Capturing multiple values of ecosystem services shaped by environmental worldviews: a spatial analysis.

    PubMed

    Van Riper, Carena J; Kyle, Gerard T

    2014-12-01

    Two related approaches to valuing nature have been advanced in past research including the study of ecosystem services and psychological investigations of the factors that shape behavior. Stronger integration of the insights that emerge from these two lines of enquiry can more effectively sustain ecosystems, economies, and human well-being. Drawing on survey data collected from outdoor recreationists on Santa Cruz Island within Channel Islands National Park, U.S., our study blends these two research approaches to examine a range of tangible and intangible values of ecosystem services provided to stakeholders with differing biocentric and anthropocentric worldviews. We used Public Participation Geographic Information System methods to collect survey data and a Social Values for Ecosystem Services mapping application to spatially analyze a range of values assigned to terrestrial and aquatic ecosystems in the park. Our results showed that preferences for the provision of biological diversity, recreation, and scientific-based values of ecosystem services varied across a spatial gradient. We also observed differences that emerged from a comparison between survey subgroups defined by their worldviews. The implications emanating from this investigation aim to support environmental management decision-making in the context of protected areas.

  19. Time-resolved spatially offset Raman spectroscopy for depth analysis of diffusely scattering layers.

    PubMed

    Iping Petterson, Ingeborg E; Dvořák, Patrick; Buijs, Joost B; Gooijer, Cees; Ariese, Freek

    2010-12-01

    The objective of this study is to use time-resolved (TR) Raman spectroscopy, spatially offset Raman spectroscopy (SORS), and a combination of these approaches to obtain high quality Raman spectra from materials hidden underneath an opaque layer. Both TR Raman and SORS are advanced techniques that allow for an increased relative selectivity of photons from deeper layers within a sample. Time-resolved detection reduces fluorescence background, and the selectivity for the second layer is improved. By combining this with spatially offset excitation we additionally increased selectivity for deeper layers. Test samples were opaque white polymer blocks of several mm thicknesses. Excitation was carried out with a frequency-doubled Ti:sapphire laser at 460 nm, 3 ps pulse width and 76 MHz repetition rate. Detection was either with a continuous-wave CCD camera or in time-resolved mode using an intensified CCD camera with a 250 ps gate width. The Raman photons were collected in backscatter mode, with or without lateral offset. By measuring the delay of the Raman signal from the second layer (polyethylene terephthalate/PET/Arnite), the net photon migration speeds through Teflon, polythene, Delrin and Nylon were determined. Raman spectra could be obtained from a second layer of PET through Teflon layers up to 7 mm of thickness. The ability to obtain chemical information through layers of diffusely scattering materials has powerful potential for biomedical applications.

  20. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases.

    PubMed

    Hongoh, Valerie; Hoen, Anne Gatewood; Aenishaenslin, Cécile; Waaub, Jean-Philippe; Bélanger, Denise; Michel, Pascal

    2011-12-29

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.

  1. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    PubMed Central

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

  2. Advancing the retrievals of surface emissivity by modelling the spatial distribution of temperature in the thermal hyperspectral scene

    NASA Astrophysics Data System (ADS)

    Shimoni, M.; Haelterman, R.; Lodewyckx, P.

    2016-05-01

    Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are commonly retrieved from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. For assessing the influence of several spatial variances on the deviation of the temperature in the scene, a statistical model is created. The model was tested using several images from various times in the day and was validated using in-situ measurements. The results highlight the importance of the geometry of the scene and its setting relative to the position of the sun during day time. It also shows that when the position of the sun is in zenith, the main contribution to the thermal distribution in the scene is the thermal capacity of the landcover materials. In this paper we propose a new Temperature and Emissivity Separation (TES) method which integrates 3D surface and landcover information from LIDAR and VNIR hyperspectral imaging data in an attempt to improve the TES procedure for a thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.

  3. Analysis of PVA/AA based photopolymers at the zero spatial frequency limit using interferometric methods.

    PubMed

    Gallego, Sergi; Márquez, Andrés; Méndez, David; Ortuño, Manuel; Neipp, Cristian; Fernández, Elena; Pascual, Inmaculada; Beléndez, Augusto

    2008-05-10

    One of the problems associated with photopolymers as optical recording media is the thickness variation during the recording process. Different values of shrinkages or swelling are reported in the literature for photopolymers. Furthermore, these variations depend on the spatial frequencies of the gratings stored in the materials. Thickness variations can be measured using different methods: studying the deviation from the Bragg's angle for nonslanted gratings, using MicroXAM S/N 8038 interferometer, or by the thermomechanical analysis experiments. In a previous paper, we began the characterization of the properties of a polyvinyl alcohol/acrylamide based photopolymer at the lowest end of recorded spatial frequencies. In this work, we continue analyzing the thickness variations of these materials using a reflection interferometer. With this technique we are able to obtain the variations of the layers refractive index and, therefore, a direct estimation of the polymer refractive index.

  4. Calibration and analysis of spatially resolved x-ray absorption spectra from a nonuniform plasma

    SciTech Connect

    Knapp, P. F.; Hansen, S. B.; Pikuz, S. A.; Shelkovenko, T. A.; Hammer, D. A.

    2012-07-15

    We report here the calibration and analysis techniques used to obtain spatially resolved density and temperature measurements of a pair of imploding aluminum wires from x-ray absorption spectra. A step wedge is used to measure backlighter fluence at the film, allowing transmission through the sample to be measured with an accuracy of {+-}14% or better. A genetic algorithm is used to search the allowed plasma parameter space and fit synthetic spectra with 20 {mu}m spatial resolution to the measured spectra, taking into account that the object plasma nonuniformity must be physically reasonable. The inferred plasma conditions must be allowed to vary along the absorption path in order to obtain a fit to the spectral data. The temperature is estimated to be accurate to within {+-}25% and the density to within a factor of two. This information is used to construct two-dimensional maps of the density and temperature of the object plasma.

  5. Georeferenced data employed in the spatial analysis of neighborhood diversity and creative class share in Chicago

    PubMed Central

    Bereitschaft, Bradley; Cammack, Rex

    2015-01-01

    The dataset described in this article, and made available as an accompanying spreadsheet, was used in the study entitled, “Neighborhood diversity and the creative class in Chicago,” to assess the spatial associations between neighborhood diversity and the creative class at the neighborhood (i.e., census tract) scale in Chicago [1]. In this study, we found a significant positive association between the creative class and the proportion of gay households and income diversity, but not racial or linguistic diversity. However, a geographically-weighted regression (GWR) analysis demonstrated substantial spatial nonstationarity among these relationships. This article describes the creative class, diversity, and control variables, their sources, and the methods used to calculate them. *Correspondence to: Department of Geography/Geology, University of Nebraska at Omaha, 6001 Dodge Street, Durham Science Center 263, Omaha, NE 68182, USA. PMID:26322326

  6. A spatial analysis of private well water Escherichia coli contamination in southern Ontario.

    PubMed

    Krolik, Julia; Maier, Allison; Evans, Gerald; Belanger, Paul; Hall, Geoffrey; Joyce, Alan; Majury, Anna

    2013-11-01

    Research to date has provided limited insight into the complexity of water-borne pathogen transmission. Private well water supplies have been identified as a significant pathway in infectious disease transmission in both the industrialised and the developing world. Using over 90,000 private well water submission records representing approximately 30,000 unique well locations in south-eastern Ontario, Canada, a spatial analysis was performed in order to delineate clusters with elevated risk of E. coli contamination using 5 years of data (2008-2012). Analyses were performed for all years independently and subsequently compared to each other. Numerous statistically significant clusters were identified and both geographic stability and variation over time were examined. Through the identification of spatial and temporal patterns, this study provides the basis for future investigations into the underlying causes of bacterial groundwater contamination, while identifying geographic regions that merit particular attention to public health interventions and improvement of water quality.

  7. Dynamic extraction of visual evoked potentials through spatial analysis and dipole localization.

    PubMed

    Wang, Y; Yang, F

    1995-08-01

    The dynamic extraction of evoked potential is a problem of great interest in EEG signal processing. In this paper, a comprehensive method is presented which integrates spatial analysis and dipole localization to make full use of the spatial-temporal information contained in the multichannel stimulation records. A realistic double boundary head model is constructed through CT scans and a two-step method devised to overcome the ill-posed nature of the forward problem of EEG caused by the low conductivity of the skull. As a result, visual evoked potentials can be effectively extracted from only two consecutive records and the dynamic information of visual evoked potential thus procured. The efficiency of the presented method has been verified by means of computer simulation and a clinical experiment.

  8. Reliability modelling system for analysis of advanced battery technologies

    NASA Astrophysics Data System (ADS)

    Imhoff, C. H.; Hostick, C. J.; Nakaoka, R. K.

    1985-05-01

    Key considerations in evaluating the reliability of advanced battery technologies include the impact of cell failures on battery performance and cost. Pacific Northwest Laboratory developed interactive microcomputer based simulation models to help battery developers use cell reliability data to calculate the expected performance of new battery technologies. Key benefits of this model include its capability to estimate the effect of cell failures upon: (1) battery system discharge performance, (2) system cycle life, and (3) system economic performance (tradeoffs between capital investment and lifetime operating costs).

  9. Analysis of an advanced ducted propeller subsonic inlet

    NASA Technical Reports Server (NTRS)

    Iek, Chanthy; Boldman, Donald R.; Ibrahim, Mounir

    1992-01-01

    It is shown that a time marching Navier-Stokes code called PARC can be utilized to provide a reasonable prediction of the flow field within an inlet for an advanced ducted propeller. The code validation was implemented for a nonseparated flow condition associated with the inlet functioning at angles-of-attack of zero and 25 deg. Comparison of the computational results with the test data shows that the PARC code with the propeller face fixed flow properties boundary conditions (BC) provided a better prediction of the inlet surface static pressures than the prediction when the mass flow BC was employed.

  10. Analysis of spatial flow patterns across the Indian subcontinent via multi-basin hydrological modelling

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, Ilias; Arheimer, Berit

    2016-04-01

    In here, we use examples from the recent HYPE hydrological model set-up across 6010 subbasins for the Indian subcontinent, named India-HYPE v1.0 (Pechlivanidis and Arheimer, 2015), and demonstrate the potential of multi-basin modelling for process understanding and comparative hydrology. We analyse the flow characteristics in all modelled 6010 subbasins and group them based on similarities in 12 flow signatures to gain insights in spatial patterns of flow generating processes. We applied a k-means clustering approach within the 12-dimensional space (consisting of the 12 calculated flow signatures) to categorise the subbasins based on their combined similarity in flow signatures. To highlight the hydrological insights gained during model identification, we conducted the clustering analysis on two different steps of the model calibration and explored the sensitivity of calibration on the spatial patterns of flow signatures. Analysis resulted into six different classes of varying size with different distribution in signatures. Although the classes are geographically distinct, their flow response is dependent on the physiographic and climatic characteristics at the regional scale. Factors including for instance the dominance of snow/ice processes, volume in precipitation and evaporation rates affect the catchment functioning and hence drive the clustering. Catchments in the Himalayan region and the Western Ghats respond similarly and are characterised by high mean annual specific runoff values and variable flow regime. Response of the catchments in the tropical zone is characterised by high peaks, while catchments in the dry regions show very strong flow variability and respond quickly to rainfall. Finally, model parameterisation can affect the spatial pattern of clusters in terms of catchment functioning. In particular, clusters after calibration seem to have a consistent spatial structure; this also justifies the validity of parameter regionalisation approaches based

  11. Relative Risk of Visceral Leishmaniasis in Brazil: A Spatial Analysis in Urban Area

    PubMed Central

    de Araújo, Valdelaine Etelvina Miranda; Pinheiro, Letícia Cavalari; Almeida, Maria Cristina de Mattos; de Menezes, Fernanda Carvalho; Morais, Maria Helena Franco; Reis, Ilka Afonso; Assunção, Renato Martins; Carneiro, Mariângela

    2013-01-01

    Background Visceral leishmaniasis (VL) is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission. Methodology This is an ecological study on the relative risk of human VL. Spatial units of analysis were the coverage areas of the Basic Health Units (146 small-areas) of Belo Horizonte, Minas Gerais State, Brazil. Human VL cases, from 2007 to 2009 (n = 412), were obtained in the Brazilian Reportable Disease Information System. Bayesian approach was used to model the relative risk of VL including potential risk factors involved in transmission (canine infection, socioeconomic and environmental features) and to identify the small-areas of greater risk to human VL. Principal Findings The relative risk of VL was shown to be correlated with income, education, and the number of infected dogs per inhabitants. The estimates of relative risk of VL were higher than 1.0 in 54% of the areas (79/146). The spatial modeling highlighted 14 areas with the highest relative risk of VL and 12 of them are concentrated in the northern region of the city. Conclusions The spatial analysis used in this study is useful for the identification of small-areas according to risk of human VL and presents operational applicability in control and surveillance program in an urban environment with an unequal spatial distribution of the disease. Thus the frequent monitoring of relative risk of human VL in small-areas is important to direct and prioritize the actions of the control program in urban environment, especially in big cities. PMID:24244776

  12. New image analysis method for the estimation of global and spatial changes in fruit microstructure

    NASA Astrophysics Data System (ADS)

    Pieczywek, Piotr M.; Cybulska, Justyna; Dyki, Barbara; Konopacka, Dorota; Mieszczakowska-Frąc, Monika; Zdunek, Artur

    2016-04-01

    A new image analysis method for the spatial characterization of microscopy images of fruit microstructure is proposed in order to analyse the heterogeneous microstructure of unprocessed fruit and the possible inhomogeneous effects of various technological treatments on this microstructure. The micro-structure of tissue samples was characterized using the global statistics of size and shape parameters calculated for all visible objects. Global analysis was supported by a novel algorithm that allowed for drawing of the maps of the cell wall fraction from microscopy images and for the analysis of both global and local compaction or loosening of tissue. The spatial distribution of the cell wall fraction was visualised in the convenient form of bivariate histograms. To test the developed image analysis protocols, structural changes resulting from ultrasonic and osmotic treatments of apple tissue samples were studied. Peeled and cored apples were submersed in a liquid medium (distilled water or 60 °Bx sucrose solution) for 45 and 90 min with and without ultrasonic treatment. After these treatment procedures, tissue samples were cut into slices, stained and imaged using a microscope. The proposed method allowed to characterise the effects of different sample treatments.

  13. Spatial analysis of electricity demand patterns in Greece: Application of a GIS-based methodological framework

    NASA Astrophysics Data System (ADS)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2016-04-01

    We investigate various uses of electricity demand in Greece (agricultural, commercial, domestic, industrial use as well as use for public and municipal authorities and street lightning) and we examine their relation with variables such as population, total area, population density and the Gross Domestic Product. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the level of prefecture. We both visualize the results of the analysis and we perform cluster and outlier analysis using the Anselin local Moran's I statistic as well as hot spot analysis using the Getis-Ord Gi* statistic. The definition of the spatial patterns and relationships of the aforementioned variables in a GIS environment provides meaningful insight and better understanding of the regional development model in Greece and justifies the basis for an energy demand forecasting methodology. Acknowledgement: This research has been partly financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II: Reinforcement of the interdisciplinary and/ or inter-institutional research and innovation (CRESSENDO project; grant number 5145).

  14. A Navigation Analysis Tool (NAT) to assess spatial behavior in open-field and structured mazes.

    PubMed

    Jarlier, Frédéric; Arleo, Angelo; Petit, Géraldine H; Lefort, Julie M; Fouquet, Céline; Burguière, Eric; Rondi-Reig, Laure

    2013-05-15

    Spatial navigation calls upon mnemonic capabilities (e.g. remembering the location of a rewarding site) as well as adaptive motor control (e.g. fine tuning of the trajectory according to the ongoing sensory context). To study this complex process by means of behavioral measurements it is necessary to quantify a large set of meaningful parameters on multiple time scales (from milliseconds to several minutes), and to compare them across different paradigms. Moreover, the issue of automating the behavioral analysis is critical to cope with the consequent computational load and the sophistication of the measurements. We developed a general purpose Navigation Analysis Tool (NAT) that provides an integrated architecture consisting of a data management system (implemented in MySQL), a core analysis toolbox (in MATLAB), and a graphical user interface (in JAVA). Its extensive characterization of trajectories over time, from exploratory behavior to goal-oriented navigation with decision points using a wide range of parameters, makes NAT a powerful analysis tool. In particular, NAT supplies a new set of specific measurements assessing performances in multiple intersection mazes and allowing navigation strategies to be discriminated (e.g. in the starmaze). Its user interface enables easy use while its modular organization provides many opportunities of extension and customization. Importantly, the portability of NAT to any type of maze and environment extends its exploitation far beyond the field of spatial navigation.

  15. Analysis of Spatial Variations and Sources of Heavy Metals in Farmland Soils of Beijing Suburbs

    PubMed Central

    Zou, Jianmei; Dai, Wei; Gong, Shengxuan; Ma, Zeyu

    2015-01-01

    To understand the effect of intense human activities in suburbs on environmental quality, we obtained 758 measurements of the heavy metals in certain farmland soils of the Beijing suburbs. Multivariate statistical analysis and geostatistical analysis were used to conduct a basic analysis of the heavy metal concentrations, the distribution characteristics and the sources of pollution of the farmland soils in these suburbs. The results showed the presence of eight heavy metals in the agricultural soils at levels exceeding the background values for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. In particular, all the measured Cr concentrations exceeded the background value, while As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were present at 1.13, 1.68, 1.95, 1.43, 1.63, 0.79, 0.92 and 1.36 times their background values, respectively. The results of correlation, factor and spatial structure analyses showed that Cd, Cu, Pb and Zn were strongly homologous, whereas Cr and Hg showed a degree of heterogeneity. The analysis further indicated that in addition to natural factors, Cd, Cu, Pb and Zn in the soil were mainly associated with distribution from road traffic and land use status. Different agricultural production measures in the various areas were also important factors that affected the spatial distribution of the soil Cr concentration. The major sources of Hg pollution were landfills for industrial waste and urban domestic garbage, while the spatial distribution of As was more likely to be a result of composite pollution. The regional distribution of the heavy metals indicated that except for Cr and Hg, the high heavy metal levels occurred in districts and counties with higher organic matter concentrations, such as the northwestern and southeastern suburbs of Beijing. There was no significant Ni pollution in the agricultural soils of the Beijing suburbs. PMID:25658749

  16. Development of spatial data guidelines and standards: spatial data set documentation to support hydrologic analysis in the U.S. Geological Survey

    USGS Publications Warehouse

    Fulton, James L.

    1992-01-01

    Spatial data analysis has become an integral component in many surface and sub-surface hydrologic investigations within the U.S. Geological Survey (USGS). Currently, one of the largest costs in applying spatial data analysis is the cost of developing the needed spatial data. Therefore, guidelines and standards are required for the development of spatial data in order to allow for data sharing and reuse; this eliminates costly redevelopment. In order to attain this goal, the USGS is expanding efforts to identify guidelines and standards for the development of spatial data for hydrologic analysis. Because of the variety of project and database needs, the USGS has concentrated on developing standards for documenting spatial sets to aid in the assessment of data set quality and compatibility of different data sets. An interim data set documentation standard (1990) has been developed that provides a mechanism for associating a wide variety of information with a data set, including data about source material, data automation and editing procedures used, projection parameters, data statistics, descriptions of features and feature attributes, information on organizational contacts lists of operations performed on the data, and free-form comments and notes about the data, made at various times in the evolution of the data set. The interim data set documentation standard has been automated using a commercial geographic information system (GIS) and data set documentation software developed by the USGS. Where possible, USGS developed software is used to enter data into the data set documentation file automatically. The GIS software closely associates a data set with its data set documentation file; the documentation file is retained with the data set whenever it is modified, copied, or transferred to another computer system. The Water Resources Division of the USGS is continuing to develop spatial data and data processing standards, with emphasis on standards needed to support

  17. Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer

    PubMed Central

    Boscoe, Francis P; Ward, Mary H; Reynolds, Peggy

    2004-01-01

    The use of spatially referenced data in cancer studies is gaining in prominence, fueled by the development and availability of spatial analytic tools and the broadening recognition of the linkages between geography and health. We provide an overview of some of the unique characteristics of spatial data, followed by an account of the major types and sources of data used in the spatial analysis of cancer, including data from cancer registries, population data, health surveys, environmental data, and remote sensing data. We cite numerous examples of recent studies that have used these data, with a focus on etiological research. PMID:15574197

  18. Using 2D Correlation Analysis to Enhance Spectral Information Available from Highly Spatially Resolved AFM-IR Spectra.

    PubMed

    Marcott, Curtis; Lo, Michael; Hu, Qichi; Kjoller, Kevin; Boskey, Adele; Noda, Isao

    2014-07-01

    The recent combination of atomic force microscopy and infrared spectroscopy (AFM-IR) has led to the ability to obtain IR spectra with nanoscale spatial resolution, nearly two orders-of-magnitude better than conventional Fourier transform infrared (FT-IR) microspectroscopy. This advanced methodology can lead to significantly sharper spectral features than are typically seen in conventional IR spectra of inhomogeneous materials, where a wider range of molecular environments are coaveraged by the larger sample cross section being probed. In this work, two-dimensional (2D) correlation analysis is used to examine position sensitive spectral variations in datasets of closely spaced AFM-IR spectra. This analysis can reveal new key insights, providing a better understanding of the new spectral information that was previously hidden under broader overlapped spectral features. Two examples of the utility of this new approach are presented. Two-dimensional correlation analysis of a set of AFM-IR spectra were collected at 200-nm increments along a line through a nucleation site generated by remelting a small spot on a thin film of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate). There are two different crystalline carbonyl band components near 1720 cm(-1) that sequentially disappear before a band at 1740 cm(-1) due to more disordered material appears. In the second example, 2D correlation analysis of a series of AFM-IR spectra spaced every 1 micrometer of a thin cross section of a bone sample measured outward from an osteon center of bone growth. There are many changes in the amide I and phosphate band contours, suggesting changes in the bone structure are occurring as the bone matures.

  19. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2003-12-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative

  20. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2004-01-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative