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.

  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. Spatially Resolved Elemental Analysis, Spectroscopy and Diffraction at the GSECARS Sector at the Advanced Photon Source

    SciTech Connect

    Sutton, Stephen R.; Lanzirotti, Antonio; Newville, Matthew; Rivers, Mark L.; Eng, Peter; Lefticariu, Liliana

    2017-01-01

    X-ray microprobes (XRM) coupled with high-brightness synchrotron X-ray facilities are powerful tools for environmental biogeochemistry research. One such instrument, the XRM at the Geo Soil Enviro Center for Advanced Radiation Sources Sector 13 at the Advanced Photon Source (APS; Argonne National Laboratory, Lemont, IL) was recently improved as part of a canted undulator geometry upgrade of the insertion device port, effectively doubling the available undulator beam time and extending the operating energy of the branch supporting the XRM down to the sulfur K edge (2.3 keV). Capabilities include rapid, high-resolution, elemental imaging including fluorescence microtomography, microscale X-ray absorption fine structure spectroscopy including sulfur K edge capability, and microscale X-ray diffraction. These capabilities are advantageous for (i) two-dimensional elemental mapping of relatively large samples at high resolution, with the dwell times typically limited only by the count times needed to obtain usable counting statistics for low concentration elements, (ii) three-dimensional imaging of internal elemental distributions in fragile hydrated specimens, such as biological tissues, avoiding the need for physical slicing, (iii) spatially resolved speciation determinations of contaminants in environmental materials, and (iv) identification of contaminant host phases. In this paper, we describe the XRM instrumentation, techniques, applications demonstrating these capabilities, and prospects for further improvements associated with the proposed upgrade of the APS.

  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.

  5. Spatial and Spatiotemporal Data Mining: Recent Advances

    SciTech Connect

    Shekhar, Shashi; Vatsavai, Raju; Celik, Mete

    2008-01-01

    Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this chapter we explore the emerging field of spatial data mining, focusing on four major topics: prediction and classification, outlier detection, co-location mining, and clustering. Spatiotemporal data mining is also briefly discussed.

  6. Spatial analysis of NDVI readings with difference sampling density

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Advanced remote sensing technologies provide research an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a complete understanding of the spatial complexity of a field and its crop. The objective of the study was...

  7. Spatial Data Analysis

    NASA Astrophysics Data System (ADS)

    Haining, Robert

    2003-06-01

    Are there geographic clusters of disease cases, or hotspots of crime? Can the geography of air quality be matched to where people hospitalized for respiratory complaints actually live? Spatial data is data about the world where the attribute of interest and its location on the earth's surface are recorded. This comprehensive overview of the subject shows how the above questions can be tackled. It is written for students and researchers in geography, economics, social science, the environmental sciences and statistics.

  8. Part 2 The Link between GIS and spatial analysis . GIS, spatial econometrics and social science research

    NASA Astrophysics Data System (ADS)

    Anselin, Luc

    Some ideas are formulated on the challenges presented to GIS, spatial analysis and spatial econometrics that result from recent trends in social science research. These new developments are characterized by a focus on the geography of phenomena. Particular emphasis is placed on the need to extend concepts of space, to broaden the analytical toolbox and to develop software and advance education.

  9. 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

  10. 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.

  11. Optical spatial solitons: historical overview and recent advances.

    PubMed

    Chen, Zhigang; Segev, Mordechai; Christodoulides, Demetrios N

    2012-08-01

    Solitons, nonlinear self-trapped wavepackets, have been extensively studied in many and diverse branches of physics such as optics, plasmas, condensed matter physics, fluid mechanics, particle physics and even astrophysics. Interestingly, over the past two decades, the field of solitons and related nonlinear phenomena has been substantially advanced and enriched by research and discoveries in nonlinear optics. While optical solitons have been vigorously investigated in both spatial and temporal domains, it is now fair to say that much soliton research has been mainly driven by the work on optical spatial solitons. This is partly due to the fact that although temporal solitons as realized in fiber optic systems are fundamentally one-dimensional entities, the high dimensionality associated with their spatial counterparts has opened up altogether new scientific possibilities in soliton research. Another reason is related to the response time of the nonlinearity. Unlike temporal optical solitons, spatial solitons have been realized by employing a variety of noninstantaneous nonlinearities, ranging from the nonlinearities in photorefractive materials and liquid crystals to the nonlinearities mediated by the thermal effect, thermophoresis and the gradient force in colloidal suspensions. Such a diversity of nonlinear effects has given rise to numerous soliton phenomena that could otherwise not be envisioned, because for decades scientists were of the mindset that solitons must strictly be the exact solutions of the cubic nonlinear Schrödinger equation as established for ideal Kerr nonlinear media. As such, the discoveries of optical spatial solitons in different systems and associated new phenomena have stimulated broad interest in soliton research. In particular, the study of incoherent solitons and discrete spatial solitons in optical periodic media not only led to advances in our understanding of fundamental processes in nonlinear optics and photonics, but also had a

  12. Advances in spatial epidemiology and geographic information systems.

    PubMed

    Kirby, Russell S; Delmelle, Eric; Eberth, Jan M

    2017-01-01

    The field of spatial epidemiology has evolved rapidly in the past 2 decades. This study serves as a brief introduction to spatial epidemiology and the use of geographic information systems in applied research in epidemiology. We highlight technical developments and highlight opportunities to apply spatial analytic methods in epidemiologic research, focusing on methodologies involving geocoding, distance estimation, residential mobility, record linkage and data integration, spatial and spatio-temporal clustering, small area estimation, and Bayesian applications to disease mapping. The articles included in this issue incorporate many of these methods into their study designs and analytical frameworks. It is our hope that these studies will spur further development and utilization of spatial analysis and geographic information systems in epidemiologic research.

  13. Forest Resources Study in Mongolia Using Advanced Spatial Technologies

    NASA Astrophysics Data System (ADS)

    Amarsaikhan, D.; Saandar, M.; Battsengel, V.; Amarjargal, Sh.

    2012-08-01

    The aim of this study is to conduct a forest resources study using optical and synthetic aperture radar (SAR) satellite images. For this purpose, a forest-dominated site around the Lake Khuvsgul located in northern Mongolia is selected. As remote sensing (RS) data sources, panchromatic and multispectral Landsat 7 images as well as ALOS PALSAR L-band HH polarization data are used. To produce a reliable land cover map from the multisensor images, a novel refined maximum likelihood classification based on the spectral and spatial thresholds are applied and for the accuracy assessment an overall accuracy is used. Overall, the research demonstrates that advanced spatial technologies based on optical and microwave RS are reliable tools for different forest studies.

  14. Advances in sequence analysis.

    PubMed

    Califano, A

    2001-06-01

    In its early days, the entire field of computational biology revolved almost entirely around biological sequence analysis. Over the past few years, however, a number of new non-sequence-based areas of investigation have become mainstream, from the analysis of gene expression data from microarrays, to whole-genome association discovery, and to the reverse engineering of gene regulatory pathways. Nonetheless, with the completion of private and public efforts to map the human genome, as well as those of other organisms, sequence data continue to be a veritable mother lode of valuable biological information that can be mined in a variety of contexts. Furthermore, the integration of sequence data with a variety of alternative information is providing valuable and fundamentally new insight into biological processes, as well as an array of new computational methodologies for the analysis of biological data.

  15. 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.

  16. 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.

  17. Advances in total scattering analysis

    SciTech Connect

    Proffen, Thomas E; Kim, Hyunjeong

    2008-01-01

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  18. 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

  19. 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).

  20. 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.

  1. Spatial Feature Evaluation for Aerial Scene Analysis

    SciTech Connect

    Swearingen, Thomas S; Cheriyadat, Anil M

    2013-01-01

    High-resolution aerial images are becoming more readily available, which drives the demand for robust, intelligent and efficient systems to process increasingly large amounts of image data. However, automated image interpretation still remains a challenging problem. Robust techniques to extract and represent features to uniquely characterize various aerial scene categories is key for automated image analysis. In this paper we examined the role of spatial features to uniquely characterize various aerial scene categories. We studied low-level features such as colors, edge orientations, and textures, and examined their local spatial arrangements. We computed correlograms representing the spatial correlation of features at various distances, then measured the distance between correlograms to identify similar scenes. We evaluated the proposed technique on several aerial image databases containing challenging aerial scene categories. We report detailed evaluation of various low-level features by quantitatively measuring accuracy and parameter sensitivity. To demonstrate the feature performance, we present a simple query-based aerial scene retrieval system.

  2. Spatial analysis using unsupervised neural networks

    NASA Astrophysics Data System (ADS)

    Murnion, Shane D.

    1996-11-01

    Site selection case studies are often used in training exercises or demonstrations to illustrate the advantages of using a geographical information system (GIS). A typical site selection case study might answer the question "where should I locate a new convenience store?" Current GIS can solve spatial analysis problems that are well defined efficiently. Unfortunately many "real world" problems are poorly defined, for example combinatorial spatial optimisation problems. In these problems the value of any solution depends on a number of factors, each of which must be changed and tested to generate an optimum solution. The large number of possible combinations that must be examined can render such problems insoluble using conventional analysis techniques. In this paper an example of a combinatorial spatial optimisation problem, which is nonpolynomial complete in nature, is examined. The problem can be defined as finding the optimum location for multiple retail sites, where the chosen retail sites will compete with each other for customers. It is shown that a solution can be determined using a relatively unsophisticated unsupervised Hopfield neural network algorithm. The neural network solution is generated within an efficient time-frame and it is shown that counter-intuitively, the algorithm becomes more efficient as the complexity of the problem increases.

  3. 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.

  4. 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

  5. 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.

  6. [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

  7. 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.

  8. High-speed multilevel phase/amplitude spatial light modulator advances

    NASA Astrophysics Data System (ADS)

    Bauchert, Kipp A.; Serati, Steven A.

    1999-03-01

    Recent and near-term advancements in our multi-level (analog) phase/amplitude liquid crystal spatial light modulators will be presented. These advancements include higher resolution, smaller pixel pitch, planarized pixel pads, and higher speed modulation for phase-only, amplitude-only, and phase- amplitude-coupled modulation. These devices have applications in optical processing, optical storage, holographic display, and beam steering. Design criteria and experimental data will be presented.

  9. LHC Olympics: Advanced Analysis Techniques

    NASA Astrophysics Data System (ADS)

    Armour, Kyle; Larkoski, Andrew; Gray, Amanda; Ventura, Dan; Walsh, Jon; Schabinger, Rob

    2006-05-01

    The LHC Olympics is a series of workshop aimed at encouraging theorists and experimentalists to prepare for the soon-to-be-online Large Hadron Collider in Geneva, Switzerland. One aspect of the LHC Olympics program consists of the study of simulated data sets which represent various possible new physics signals as they would be seen in LHC detectors. Through this exercise, LHC Olympians learn the phenomenology of possible new physics models and gain experience in analyzing LHC data. Additionally, the LHC Olympics encourages discussion between theorists and experimentalists, and through this collaboration new techniques could be developed. The University of Washington LHC Olympics group consists of several first-year graduate and senior undergraduate students, in both theoretical and experimental particle physics. Presented here is a discussion of some of the more advanced techniques used and the recent results of one such LHC Olympics study.

  10. 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.

  11. Digital map and spatial database requirements for advanced traffic management systems

    SciTech Connect

    Lerner-Lam, E.; Smith, W.T.; Francisca, J.R.; Rathi, A.

    1993-12-31

    Advanced Traffic Management Systems (ATMS) depend on good-quality digital maps and spatial databases. Concerns over the availability of digital maps and spatial databases for ATMS`s in the United States were initially raised in early meetings of IVHS America ATMS committee. While there has been little argument regarding the important role of the private sector in providing ``value-added`` data for sale to public and private parties, the IVHS community has since been engaged in a lively debate over the appropriates roles of the public and private sectors in providing ``base data`` for the nation`s Intelligent Vehicle and Highway Systems. This paper summarizes the activities of the ATMS Committee over the past 1 1/2 years and offers recommendations for next steps to be taken toward laying the foundations for efficient and effective deployment of digital map and spatial database resources for use in advanced traffic management systems.

  12. 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.

  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. 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).

  15. Advances in Barkhausen noise analysis

    NASA Astrophysics Data System (ADS)

    Meyendorf, Norbert; Hillmann, Susanne; Cikalova, Ulana; Schreiber, Juergen

    2014-03-01

    The magnetic Barkhausen Noise technique is a well suited method for the characterization of ferromagnetic materials. The Barkhausen effect results in an interaction between the magnetic structure and the microstructure of materials, and is sensitive to the stresses and microstructure related mechanical properties. Barkhausen noise is a complex signal that provides a large amount of information, for example frequency spectrum, amplitude, RMS value, dependence of magnetic field strength, magnetization frequency and fractal behavior. Although this technique has a lot potentials, it is not commonly used in nondestructive material testing. Large sensors and complex calibration procedures made the method impractical for many applications. However, research has progressed in recent years; new sensor designs were developed and evaluated, new algorithms to simplify the calibration and measurement procedures were developed as well as analysis of additional material properties have been introduced.

  16. Spatial Fourier Transform Analysis of Polishing Pad Surface Topography

    NASA Astrophysics Data System (ADS)

    Khajornrungruang, Panart; Kimura, Keiichi; Okuzono, Takahisa; Suzuki, Keisuke; Kushida, Takashi

    2012-05-01

    The spatial Fourier transform analysis is proposed to quantitatively evaluate the irregular topography of the conditioned chemical mechanical polishing (CMP) pad surface. We discuss the power spectrum in the spatial wavelengths of the surface topographies corresponding to polishing time. We conclude that the spatial wavelength of less than 5 µm in the topography yielded high material removal rates.

  17. An Empirical Bayes Approach to Spatial Analysis

    NASA Technical Reports Server (NTRS)

    Morris, C. N.; Kostal, H.

    1983-01-01

    Multi-channel LANDSAT data are collected in several passes over agricultural areas during the growing season. How empirical Bayes modeling can be used to develop crop identification and discrimination techniques that account for spatial correlation in such data is considered. The approach models the unobservable parameters and the data separately, hoping to take advantage of the fact that the bulk of spatial correlation lies in the parameter process. The problem is then framed in terms of estimating posterior probabilities of crop types for each spatial area. Some empirical Bayes spatial estimation methods are used to estimate the logits of these probabilities.

  18. 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…

  19. 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

  20. Advanced techniques for the storage and use of very large, heterogeneous spatial databases

    NASA Technical Reports Server (NTRS)

    Peuquet, Donna J.

    1987-01-01

    Progress is reported in the development of a prototype knowledge-based geographic information system. The overall purpose of this project is to investigate and demonstrate the use of advanced methods in order to greatly improve the capabilities of geographic information system technology in the handling of large, multi-source collections of spatial data in an efficient manner, and to make these collections of data more accessible and usable for the Earth scientist.

  1. 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

    2015-01-06

    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.

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

    USGS Publications Warehouse

    Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; 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.

  3. 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

  4. 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.

  5. Classification of Sulfides, Arsenides and Tellurides from the Sudbury Igneous Complex (SIC) Using Feature Analysis and Spectrum Imaging with Advanced EDS

    NASA Astrophysics Data System (ADS)

    Salge, T.; Hecht, L.; Hansen, B.; Patzschke, M.

    2013-08-01

    Developments in energy dispersive X-ray spectrometry offer advanced element analysis at high spatial resolution. Technological advances are demonstrated in representative samples for quantitative mineralogy and ore characterization.

  6. Recent Advances in Morphological Cell Image Analysis

    PubMed Central

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  7. Advanced Climate Analysis and Long Range Forecasting

    DTIC Science & Technology

    2014-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Advanced Climate Analysis and Long Range Forecasting...project is to improve the long range and climate support provided by the U.S. Naval Oceanography Enterprise (NOe) for planning, conducting, and...months, several seasons, several years). The primary transition focus is on improving the long range and climate support capabilities of the Fleet

  8. 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.

  9. Exploiting spatial descriptions in visual scene analysis.

    PubMed

    Ziegler, Leon; Johannsen, Katrin; Swadzba, Agnes; De Ruiter, Jan P; Wachsmuth, Sven

    2012-08-01

    The reliable automatic visual recognition of indoor scenes with complex object constellations using only sensor data is a nontrivial problem. In order to improve the construction of an accurate semantic 3D model of an indoor scene, we exploit human-produced verbal descriptions of the relative location of pairs of objects. This requires the ability to deal with different spatial reference frames (RF) that humans use interchangeably. In German, both the intrinsic and relative RF are used frequently, which often leads to ambiguities in referential communication. We assume that there are certain regularities that help in specific contexts. In a first experiment, we investigated how speakers of German describe spatial relationships between different pieces of furniture. This gave us important information about the distribution of the RFs used for furniture-predicate combinations, and by implication also about the preferred spatial predicate. The results of this experiment are compiled into a computational model that extracts partial orderings of spatial arrangements between furniture items from verbal descriptions. In the implemented system, the visual scene is initially scanned by a 3D camera system. From the 3D point cloud, we extract point clusters that suggest the presence of certain furniture objects. We then integrate the partial orderings extracted from the verbal utterances incrementally and cumulatively with the estimated probabilities about the identity and location of objects in the scene, and also estimate the probable orientation of the objects. This allows the system to significantly improve both the accuracy and richness of its visual scene representation.

  10. 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.

  11. Leak Location in Plates Using Spatial Fourier Transform Based Analysis

    NASA Astrophysics Data System (ADS)

    Roberts, R.; Holland, S.; Strei, M.; Song, J.; Chimenti, D. E.

    2005-04-01

    The location of air leaks in plate-like structures is examined using a spatial Fourier transform based analysis. Noise data is collected over 2-D spatial arrays at sensor locations, from which mean cross-correlations are compiled. Propagation properties, transit times, and energy distribution among modes are extracted through spatial Fourier transformation of these data. A simple algorithm to determine source location using a reduced set of transform data is demonstrated experimentally, based upon extraction of energy propagation direction.

  12. Spatial analysis of hemorrhagic fever with renal syndrome in China

    PubMed Central

    Fang, Liqun; Yan, Lei; Liang, Song; de Vlas, Sake J; Feng, Dan; Han, Xiaona; Zhao, Wenjuan; Xu, Bing; Bian, Ling; Yang, Hong; Gong, Peng; Richardus, Jan Hendrik; Cao, Wuchun

    2006-01-01

    Background Hemorrhagic fever with renal syndrome (HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Methods Annualized average incidence at a county level was calculated using HFRS cases reported during 1994–1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Results Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's I = 0.5044 (p = 0.001). Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p < 0.01) with maximum spatial cluster sizes of ≤ 20% and ≤ 10% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS. PMID:16638156

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  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. 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.

  19. The role of the society of Latin American specialists on remote sensing (SELPER) in the analysis and actions related to the main advances and needs of spatial remote sensing for Latin America

    NASA Astrophysics Data System (ADS)

    Araya, Mauricio F.

    The existence of SELPER (Sociedad de Especialistas Latinoamericanos en Percepción Remota / Society of Latinamerican Specialists on Remote Sensing) has filled a great gap among latinamerican countries. SELPER was formed in 1980 and several important activities, having international support, have been performed and are planned in the near future. SELPER consolidation will help develop several important regional cooperation programs and the next years look very promisory in this sense. Different steps are planned but the most important is related with the formation of such a Latin American Council on Remote Sensing, having official support from different countries of the region; SELPER can help this important objective. Main advances and needs are summarized in this paper and it is possible to conclude that SELPER will be important for regional and inter-regional scientific and technical cooperation on remote sensing.

  20. Spatial Analysis Methods for Health Promotion and Education.

    PubMed

    Chaney, Robert A; Rojas-Guyler, Liliana

    2016-05-01

    This article provides a review of spatial analysis methods for use in health promotion and education research and practice. Spatial analysis seeks to describe or make inference about variables with respect to the places they occur. This includes geographic differences, proximity issues, and access to resources. This is important for understanding how health outcomes differ from place to place; and in terms of understanding some of the environmental underpinnings of health outcomes data by placing it in context of geographic location. This article seeks to promote spatial analysis as a viable tool for health promotion and education research and practice. Four more commonly used spatial analysis techniques are described in-text. An illustrative example of motor vehicle collisions in a large metropolitan city is presented using these techniques. The techniques discussed are as follows: descriptive mapping, global spatial autocorrelation, cluster detection, and identification and spatial regression analysis. This article provides useful information for health promotion and education researchers and practitioners seeking to examine research questions from a spatial perspective.

  1. Holographic analogy of the spatial radial carrier analysis of interferograms

    NASA Astrophysics Data System (ADS)

    Garcia-Marquez, Jorge L.; Malacara-Hernandez, Daniel

    1996-07-01

    A holographic analogy ofthe analysis of thterferograms with a spatial radial carrier introduced by means of defocusing and its practical applications is describei Special emphasis is made ofthe conditions imposed on the Fourier spectra ofthe interferogram.

  2. 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...

  3. 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.

  4. Correction for spatial averaging in laser speckle contrast analysis

    PubMed Central

    Thompson, Oliver; Andrews, Michael; Hirst, Evan

    2011-01-01

    Practical laser speckle contrast analysis systems face a problem of spatial averaging of speckles, due to the pixel size in the cameras used. Existing practice is to use a system factor in speckle contrast analysis to account for spatial averaging. The linearity of the system factor correction has not previously been confirmed. The problem of spatial averaging is illustrated using computer simulation of time-integrated dynamic speckle, and the linearity of the correction confirmed using both computer simulation and experimental results. The valid linear correction allows various useful compromises in the system design. PMID:21483623

  5. A spatial-temporal covariance model for rainfall analysis

    NASA Astrophysics Data System (ADS)

    Li, Sha; Shu, Hong; Xu, Zhengquan

    2009-10-01

    Many environmental phenomena are regarded as realizations of random functions which possess both spatial and temporal characteristics. In particular, Geostatistics with an extension of the existing spatial techniques into the space-time domain offers some kinds of methods to model such processes. Although these methods for the analysis of spatial-temporal data are becoming more important for many areas of application, they are less developed than those for the analysis of purely spatial or purely temporal data. In this paper, two kinds of spatial-temporal stationary covariance models are introduced. And the differences between spatial domain and time domain are examined. A product-sum covariance model originally given by De Cesare is extended for spatial-temporal analysis on daily rainfall measurements in the three provinces of Northeast China. Remarkably, this generalized non-separable model does not correspond to the use of a metric one in space-time. The rainfall measurements used for this experiment are taken at 104 monitoring stations from January 2000 to December 2005. In the experiment, the product-sum variogram model is employed for developing ordinary kriging and its application to interpolation of the monthly rainfall data from January 2000 to December 2004 has been used to predict the monthly rainfall of 2005. The true values and the predicted ones are compared. The experimental results have shown that this product-sum covariance model is very effective for rainfall analysis.

  6. 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.

  7. 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

  8. 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

  9. Application of Fourier analysis to multispectral/spatial recognition

    NASA Technical Reports Server (NTRS)

    Hornung, R. J.; Smith, J. A.

    1973-01-01

    One approach for investigating spectral response from materials is to consider spatial features of the response. This might be accomplished by considering the Fourier spectrum of the spatial response. The Fourier Transform may be used in a one-dimensional to multidimensional analysis of more than one channel of data. The two-dimensional transform represents the Fraunhofer diffraction pattern of the image in optics and has certain invariant features. Physically the diffraction pattern contains spatial features which are possibly unique to a given configuration or classification type. Different sampling strategies may be used to either enhance geometrical differences or extract additional features.

  10. An Analysis of Perturbed Quantization Steganography in the Spatial Domain

    DTIC Science & Technology

    2005-03-01

    steganography is also common with audio [KaP00]. Figure 1 depicts this form of steganography . Figure 1. Least Significant Bit Substitution 6...QUANTIZATION STEGANOGRAPHY IN THE SPATIAL DOMAIN THESIS Matthew D. Spisak AFIT/GIA/ENG/05-04DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY ORCE...ANALYSIS OF PERTURBED QUANTIZATION STEGANOGRAPHY IN THE SPATIAL DOMAIN THESIS Presented to the Faculty Department of Electrical and

  11. 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

  12. 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.

  13. 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

  14. Spatial cognition and crime: the study of mental models of spatial relations in crime analysis.

    PubMed

    Luini, Lorenzo P; Scorzelli, Marco; Mastroberardino, Serena; Marucci, Francesco S

    2012-08-01

    Several studies employed different algorithms in order to investigate criminal's spatial behaviour and to identify mental models and cognitive strategies related to it. So far, a number of geographic profiling (GP) software have been implemented to analyse mobility and its relation to the way criminals are using spatial environment when committing a crime. Since crimes are usually perpetrated in the offender's high-awareness areas, those cognitive maps can be employed to create a map of the criminal's operating area to help investigators to circumscribe search areas. The aim of the present study was to verify accuracy of simple statistical analysis in predicting spatial mobility of a group of 30 non-criminal subjects. Results showed that statistics such as Mean Centre and Standard Distance were accurate in elaborating a GP for each subject according to the mobility area provided. Future analysis will be implemented using mobility information of criminal subjects and location-based software to verify whether there is a cognitive spatial strategy employed by them when planning and committing a crime.

  15. 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).

  16. Geographic analysis of forest health indicators using spatial scan statistics.

    PubMed

    Coulston, John W; Riitters, Kurt H

    2003-06-01

    Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.

  17. Spatial independent component analysis of functional brain optical imaging

    NASA Astrophysics Data System (ADS)

    Li, Yong; Li, Pengcheng; Liu, Yadong; Luo, Weihua; Hu, Dewen; Luo, Qingming

    2003-12-01

    This paper introduces the algorithm and the basic theory of Independent Component Analysis (ICA), and discusses how to choose the proper ICA model of the data by the characteristics of the underlying signals to be estimated. The Spatial ICA (SICA) is applied to model and analysis of the data in the experiment when the signals and noises are spatially dependent. The data acquired from the intrinsic optical signals which are caused by electricity stimulation to sciatic nerve of rat are analyzed by SICA. In the result, the active-related component of the signals and its time course can be separate, and the signals of heartbeat and respiration also can be separated.

  18. Advanced techniques in current signature analysis

    NASA Astrophysics Data System (ADS)

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

    1992-02-01

    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 can 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 (greater than 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.

  19. 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

  20. Macroscopic spatial analysis of pedestrian and bicycle crashes.

    PubMed

    Siddiqui, Chowdhury; Abdel-Aty, Mohamed; Choi, Keechoo

    2012-03-01

    This study investigates the effect of spatial correlation using a Bayesian spatial framework to model pedestrian and bicycle crashes in Traffic Analysis Zones (TAZs). Aggregate models for pedestrian and bicycle crashes were estimated as a function of variables related to roadway characteristics, and various demographic and socio-economic factors. It was found that significant differences were present between the predictor sets for pedestrian and bicycle crashes. The Bayesian Poisson-lognormal model accounting for spatial correlation for pedestrian crashes in the TAZs of the study counties retained nine variables significantly different from zero at 95% Bayesian credible interval. These variables were - total roadway length with 35 mph posted speed limit, total number of intersections per TAZ, median household income, total number of dwelling units, log of population per square mile of a TAZ, percentage of households with non-retired workers but zero auto, percentage of households with non-retired workers and one auto, long term parking cost, and log of total number of employment in a TAZ. A separate distinct set of predictors were found for the bicycle crash model. In all cases the Bayesian models with spatial correlation performed better than the models that did not account for spatial correlation among TAZs. This finding implies that spatial correlation should be considered while modeling pedestrian and bicycle crashes at the aggregate or macro-level.

  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.

  2. 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…

  3. 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.

  4. 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.

  5. Random vectors and spatial analysis by geostatistics for geotechnical applications

    SciTech Connect

    Young, D.S.

    1987-08-01

    Geostatistics is extended to the spatial analysis of vector variables by defining the estimation variance and vector variogram in terms of the magnitude of difference vectors. Many random variables in geotechnology are in vectorial terms rather than scalars, and its structural analysis requires those sample variable interpolations to construct and characterize structural models. A better local estimator will result in greater quality of input models; geostatistics can provide such estimators; kriging estimators. The efficiency of geostatistics for vector variables is demonstrated in a case study of rock joint orientations in geological formations. The positive cross-validation encourages application of geostatistics to spatial analysis of random vectors in geoscience as well as various geotechnical fields including optimum site characterization, rock mechanics for mining and civil structures, cavability analysis of block cavings, petroleum engineering, and hydrologic and hydraulic modelings.

  6. 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.

  7. Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

    DTIC Science & Technology

    1987-04-01

    mumgs0.USmusa 7.AUWOJO 4. CIUTAC Rm6ANT Wuugme*j James V/. Mlahoney DACA? 6-85-C-00 10 NOQ 1 4-85-K-O 124 Artificial Inteligence Laboratory US USS 545...0197 672 IMAGE CHUWING: DEINING SPATIAL UILDING PLOCKS FOR 142 SCENE ANRLYSIS(U) MASSACHUSETTS INST OF TECH CAIIAIDGE ARTIFICIAL INTELLIGENCE LAO J...Technical Report 980 F-Image Chunking: Defining Spatial Building Blocks for Scene DTm -Analysis S ELECTED James V. Mahoney’ MIT Artificial Intelligence

  8. Spatial analysis of agro-ecological data: Detection of spatial patterns combining three different methodical approaches

    NASA Astrophysics Data System (ADS)

    Heuer, A.; Casper, M. C.; Vohland, M.

    2009-04-01

    Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to

  9. 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. ...

  10. 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

  11. 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.

  12. 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.

  13. 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).

  14. Spatial filtering efficiency of monostatic biaxial lidar: analysis and applications

    NASA Astrophysics Data System (ADS)

    Agishev, Ravil R.; Comeron, Adolfo

    2002-12-01

    Results of lidar modeling based on spatial-angular filtering efficiency criteria are presented. Their analysis shows that the low spatial-angular filtering efficiency of traditional visible and near-infrared systems is an important cause of low signal/background-radiation ratio (SBR) at the photodetector input. The low SBR may be responsible for considerable measurement errors and ensuing the low accuracy of the retrieval of atmospheric optical parameters. As shown, the most effective protection against sky background radiation for groundbased biaxial lidars is the modifying of their angular field according to a spatial-angular filtering efficiency criterion. Some effective approaches to achieve a high filtering efficiency for the receiving system optimization are discussed.

  15. Spatial filtering efficiency of monostatic biaxial lidar: analysis and applications.

    PubMed

    Agishev, Ravil R; Comeron, Adolfo

    2002-12-20

    Results of lidar modeling based on spatial-angular filtering efficiency criteria are presented. Their analysis shows that the low spatial-angular filtering efficiency of traditional visible and near-infrared systems is an important cause of low signal/background-radiation ratio (SBR) at the photodetector input The low SBR may be responsible for considerable measurement errors and ensuing the low accuracy of the retrieval of atmospheric optical parameters. As shown, the most effective protection against sky background radiation for groundbased biaxial lidars is the modifying of their angular field according to a spatial-angular filtering efficiency criterion. Some effective approaches to achieve a high filtering efficiency for the receiving system optimization are discussed.

  16. GIS application on spatial landslide analysis using statistical based models

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred F.

    2009-09-01

    This paper presents the assessment results of spatially based probabilistic three models using Geoinformation Techniques (GIT) for landslide susceptibility analysis at Penang Island in Malaysia. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and supported with field surveys. Maps of the topography, soil type, lineaments and land cover were constructed from the spatial data sets. There are ten landslide related factors were extracted from the spatial database and the frequency ratio, fuzzy logic, and bivariate logistic regression coefficients of each factor was computed. Finally, landslide susceptibility maps were drawn for study area using frequency ratios, fuzzy logic and bivariate logistic regression models. For verification, the results of the analyses were compared with actual landslide locations in study area. The verification results show that bivariate logistic regression model provides slightly higher prediction accuracy than the frequency ratio and fuzzy logic models.

  17. 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.

  18. Baseline Industry Analysis, Advance Ceramics Industry

    DTIC Science & Technology

    1993-04-01

    Commerce , Department of Defense, and the National Critical Technologies Panel. Advanced Ceramics, which include ceramic matrix composites, are found in...ceramics and materials industry being identified as a National Critical Technology, Commerce Emerging Technology, and Defense Critical Technology.’ There is...total procurement cost in advanced systems, and as much as ten percent of the electronics portion of those weapons. Ceramic capacitors are almost as

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach

    DTIC Science & Technology

    2012-05-10

    analysts. Many police departments aim to accomplish crime mitigation and crime prevention with very few resources. However, the growth in the size and...mining (SFPM) and defines the crime outbreak detection problem . Spatial frequent pattern mining (SFPM) is the process of discovering interesting...an analysis problem that may require a solution using SFPM . 2.1 Crime outbreak detection and Illustration In this section, we define crime outbreak

  4. Spatial Analysis of Maritime Traffic for Maritime Security

    DTIC Science & Technology

    2009-10-01

    Locations Spatial Pattern II Sample size NB NS Canoe 4 17 Kayak 8 21 Motorboat 15 10 Sailboat 5 47 Scope of Study Methodology Data Pre-cleaning Points on land...Attributes to Variates Speed Total distance Bounding Box Dedensified Trajectory Distance from shore Pattern Analysis Discrimination Classification Kayak ...Trajectories Pattern Classification Procedure Predicted: Kayak : T1,T5… Canoe: T3,T4… Sailboat: T6,… Motorboat: T2.. Actual: Kayak : T1,T5

  5. Terahertz grayscale imaging using spatial frequency domain analysis

    NASA Astrophysics Data System (ADS)

    Lv, Zhihui; Sun, Lin; Zhang, Dongwen; Yuan, Jianmin

    2011-11-01

    We reported a technology of gray-scale imaging using broadband terahertz pulse. Utilizing the spatial distribution of different frequency content, image information can be acquired from the terahertz frequency domain analysis. Unlike CCDs(charge-coupled devices) or spot scanning technology are used in conversional method, a single-pixels detector with single measurement can meet the demand of our scheme. And high SNR terahertz imaging with fast velocity is believed.

  6. Terahertz grayscale imaging using spatial frequency domain analysis

    NASA Astrophysics Data System (ADS)

    Lv, Zhihui; Sun, Lin; Zhang, Dongwen; Yuan, Jianmin

    2012-03-01

    We reported a technology of gray-scale imaging using broadband terahertz pulse. Utilizing the spatial distribution of different frequency content, image information can be acquired from the terahertz frequency domain analysis. Unlike CCDs(charge-coupled devices) or spot scanning technology are used in conversional method, a single-pixels detector with single measurement can meet the demand of our scheme. And high SNR terahertz imaging with fast velocity is believed.

  7. Gis-Based Spatial Statistical Analysis of College Graduates Employment

    NASA Astrophysics Data System (ADS)

    Tang, R.

    2012-07-01

    It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

  8. 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.

  9. 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.

  10. 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.

  11. Effects of sex and age on auditory spatial scene analysis.

    PubMed

    Lewald, Jörg; Hausmann, Markus

    2013-05-01

    Recently, it has been demonstrated that men outperform women in spatial analysis of complex auditory scenes (Zündorf et al., 2011). The present study investigated the relation between the effects of ageing and sex on the spatial segregation of concurrent sounds in younger and middle-aged adults. The experimental design allowed simultaneous presentation of target and distractor sound sources at different locations. The resulting spatial "pulling" effect (that is, the bias of target localization toward that of the distractor) was used as a measure of performance. The pulling effect was stronger in middle-aged than younger subjects, and female than male subjects. This indicates lower performance of the middle-aged women in the sensory and attentional mechanisms extracting spatial information about the acoustic event of interest from the auditory scene than both younger and male subjects. Moreover, age-specific differences were most prominent for conditions with targets in right hemispace and distractors in left hemispace, suggesting bilateral asymmetries underlying the effect of ageing.

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

    PubMed

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

    2016-08-30

    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. 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

  15. Proposed neutron activation analysis facilities in the Advanced Neutron Source

    SciTech Connect

    Robinson, L.; Dyer, F.F.; Emery, J.F.

    1990-01-01

    A number of analytical chemistry experimental facilities are being proposed for the Advanced Neutron Source. Experimental capabilities will include gamma-ray analysis and neutron depth profiling. This paper describes the various systems proposed and some of their important characteristics.

  16. 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.

  17. 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.

  18. Advanced Trending Analysis/EDS Data Program.

    DTIC Science & Technology

    1982-01-01

    Fault Detection and Isolation (TEFDI) Program, SCT was to use the Advanced Trend...detailed discussion of the algorithm and its underlying theory, the reader is directed to SCT’s Turbine Engine Fault Detection and Isolation (TEF!I) Program...SCT’s Turbine Engine Fault Detection and Isolation (TEFDI) Program Final Report scheduled for release in early 1982. 2. DISCUSSION OF RESULTS -

  19. ESTATE: Strategy for Exploring Labeled Spatial Datasets Using Association Analysis

    NASA Astrophysics Data System (ADS)

    Stepinski, Tomasz F.; Salazar, Josue; Ding, Wei; White, Denis

    We propose an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. Proposed strategy, ESTATE (Exploring Spatial daTa Association patTErns), inverts such classification by interpreting different classes found in the dataset in terms of sets of discriminative patterns of its attributes. It consists of several core steps including discriminative data mining, similarity between transactional patterns, and visualization. An algorithm for calculating similarity measure between patterns is the major original contribution that facilitates summarization of discovered information and makes the entire framework practical for real life applications. Detailed description of the ESTATE framework is followed by its application to the domain of ecology using a dataset that fuses the information on geographical distribution of biodiversity of bird species across the contiguous United States with distributions of 32 environmental variables across the same area.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Image analysis in medical imaging: recent advances in selected examples.

    PubMed

    Dougherty, G

    2010-01-01

    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments.

  5. Advanced Software Methods for Physics Analysis

    NASA Astrophysics Data System (ADS)

    Lista, L.

    2006-01-01

    Unprecedented data analysis complexity is experienced in modern High Energy Physics experiments. The complexity arises from the growing size of recorded data samples, the large number of data analyses performed by different users in each single experiment, and the level of complexity of each single analysis. For this reason, the requirements on software for data analysis impose a very high level of reliability. We present two concrete examples: the former from BaBar experience with the migration to a new Analysis Model with the definition of a new model for the Event Data Store, the latter about a toolkit for multivariate statistical and parametric Monte Carlo analysis developed using generic programming.

  6. Advanced Plasma Diagnostic Analysis using Neural Networks

    NASA Astrophysics Data System (ADS)

    Tritz, Kevin; Reinke, Matt

    2016-10-01

    Machine learning techniques, specifically neural networks (NN), are used with sufficient internal complexity to develop an empirically weighted relationship between a set of filtered X-ray emission measurements and the electron temperature (Te) profile for a specific class of discharges on NSTX. The NN response matrix is used to calculate the Te profile directly from the filtered X-ray diode measurements which extends the electron temperature time response from the 60Hz Thomson Scattering profile measurements to fast timescales (>10kHz) and greatly expands the applicability of Te profile information to fast plasma phenomena, such as ELM dynamics. This process can be improved by providing additional information which helps the neural network refine the relationship between Te and the corresponding X-ray emission. NN supplement limited measurements of a particular quantity using related measurements with higher time or spatial resolution. For example, the radiated power (Prad) determined using resistive foil bolometers is related to similar measurements using AXUV diode arrays through a complex and slowly time-evolving quantum efficiency curve in the VUV spectral region. Results from a NN trained using Alcator C-Mod resistive foil bolometry and AXUV diodes are presented, working towards hybrid Prad measurements with the quantitative accuracy of resistive foil bolometers and with the enhanced temporal and spatial resolution of the unfiltered AXUV diode arrays. Work supported by Department of Energy Grant #: DE-FG02-09ER55012.

  7. 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.

  8. 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.

  9. 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.

  10. Improved dependent component analysis for hyperspectral unmixing with spatial correlations

    NASA Astrophysics Data System (ADS)

    Tang, Yi; Wan, Jianwei; Huang, Bingchao; Lan, Tian

    2014-11-01

    In highly mixed hyerspectral datasets, dependent component analysis (DECA) has shown its superiority over other traditional geometric based algorithms. This paper proposes a new algorithm that incorporates DECA with the infinite hidden Markov random field (iHMRF) model, which can efficiently exploit spatial dependencies between image pixels and automatically determine the number of classes. Expectation Maximization algorithm is derived to infer the model parameters, including the endmembers, the abundances, the dirichlet distribution parameters of each class and the classification map. Experimental results based on synthetic and real hyperspectral data show the effectiveness of the proposed algorithm.

  11. 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

  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. 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).

  15. Spatial regression analysis on 32 years total column ozone data

    NASA Astrophysics Data System (ADS)

    Knibbe, J. S.; van der A, R. J.; de Laat, A. T. J.

    2014-02-01

    Multiple-regressions analysis have been performed on 32 years of total ozone column data that was spatially gridded with a 1° × 1.5° resolution. The total ozone data consists of the MSR (Multi Sensor Reanalysis; 1979-2008) and two years of assimilated SCIAMACHY ozone data (2009-2010). The two-dimensionality in this data-set allows us to perform the regressions locally and investigate spatial patterns of regression coefficients and their explanatory power. Seasonal dependencies of ozone on regressors are included in the analysis. A new physically oriented model is developed to parameterize stratospheric ozone. Ozone variations on non-seasonal timescales are parameterized by explanatory variables describing the solar cycle, stratospheric aerosols, the quasi-biennial oscillation (QBO), El Nino (ENSO) and stratospheric alternative halogens (EESC). For several explanatory variables, seasonally adjusted versions of these explanatory variables are constructed to account for the difference in their effect on ozone throughout the year. To account for seasonal variation in ozone, explanatory variables describing the polar vortex, geopotential height, potential vorticity and average day length are included. Results of this regression model are compared to that of similar analysis based on a more commonly applied statistically oriented model. The physically oriented model provides spatial patterns in the regression results for each explanatory variable. The EESC has a significant depleting effect on ozone at high and mid-latitudes, the solar cycle affects ozone positively mostly at the Southern Hemisphere, stratospheric aerosols affect ozone negatively at high Northern latitudes, the effect of QBO is positive and negative at the tropics and mid to high-latitudes respectively and ENSO affects ozone negatively between 30° N and 30° S, particularly at the Pacific. The contribution of explanatory variables describing seasonal ozone variation is generally large at mid to high

  16. 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

  17. Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

    PubMed Central

    Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

    2015-01-01

    Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

  18. 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).

  19. 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.

  20. Advances in microfluidics for environmental analysis.

    PubMed

    Jokerst, Jana C; Emory, Jason M; Henry, Charles S

    2012-01-07

    During the past few years, a growing number of groups have recognized the utility of microfluidic devices for environmental analysis. Microfluidic devices offer a number of advantages and in many respects are ideally suited to environmental analyses. Challenges faced in environmental monitoring, including the ability to handle complex and highly variable sample matrices, lead to continued growth and research. Additionally, the need to operate for days to months in the field requires further development of robust, integrated microfluidic systems. This review examines recently published literature on the applications of microfluidic systems for environmental analysis and provides insight in the future direction of the field.

  1. 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

  2. Advanced Durability Analysis. Volume 1. Analytical Methods

    DTIC Science & Technology

    1987-07-31

    for microstruc .- tural behavior . This approach for representing the IFQ, when properly used, can provide reasonable durability analysis rt,- sults for...equivalent initial flaw size distribution (EIFSD) function. Engineering principles rather than mechanistic-based theories for microstructural behavior are...accurate EIFS distribution and a service crack growth behavior . The determinations of EIFS distribution have been described in detail previously. In this

  3. 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.

  4. Map Analysis and Spatial Statistic: Assessment of Spatial Variability of Agriculture Land Conversion at Urban Fringe Area of Yogyakarta

    NASA Astrophysics Data System (ADS)

    Susilo, Bowo

    2016-11-01

    Urban development has brought various effects, one of which was the marginalization of the agricultural sector. Agricultural land is gradually converted to other type of land uses which considered more profitable. Conversion of agricultural land cannot be avoided but it should be controlled. Early identification on spatial distribution and intensity of agricultural land conversion as well as its related factor is necessary. Objective of the research were (1) to assess the spatial variability of agricultural land conversion, (2) to identify factors that affecting the spatial variability of agricultural land conversion. Research was conducted at urban fringe area of Yogyakarta. Spatial variability of agricultural land conversion was analysed using an index called Relative Conversion Index (RCI). Combined of map analysis and spatial statistical were used to determine the center of agricultural land conversion. Simple regression analysis was used to determine the factors associated with the conversion of agricultural land. The result shows that intensity of agricultural land conversion in the study area varies spatially as well as temporally. Intensity of agricultural land conversion in the period 1993-2000, involves three categories which are high, moderate and low. In the period of 2000-2007, the intensity of agricultural land conversion involves two categories which are high and low. Spatial variability of agricultural land conversion in the study area has a significant correlation with three factors: population growth, fragmentation of agricultural land and distance of agricultural land to the city

  5. The bivariate combined model for spatial data analysis.

    PubMed

    Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Faes, Christel

    2016-08-15

    To describe the spatial distribution of diseases, a number of methods have been proposed to model relative risks within areas. Most models use Bayesian hierarchical methods, in which one models both spatially structured and unstructured extra-Poisson variance present in the data. For modelling a single disease, the conditional autoregressive (CAR) convolution model has been very popular. More recently, a combined model was proposed that 'combines' ideas from the CAR convolution model and the well-known Poisson-gamma model. The combined model was shown to be a good alternative to the CAR convolution model when there was a large amount of uncorrelated extra-variance in the data. Less solutions exist for modelling two diseases simultaneously or modelling a disease in two sub-populations simultaneously. Furthermore, existing models are typically based on the CAR convolution model. In this paper, a bivariate version of the combined model is proposed in which the unstructured heterogeneity term is split up into terms that are shared and terms that are specific to the disease or subpopulation, while spatial dependency is introduced via a univariate or multivariate Markov random field. The proposed method is illustrated by analysis of disease data in Georgia (USA) and Limburg (Belgium) and in a simulation study. We conclude that the bivariate combined model constitutes an interesting model when two diseases are possibly correlated. As the choice of the preferred model differs between data sets, we suggest to use the new and existing modelling approaches together and to choose the best model via goodness-of-fit statistics. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Study of trabecular bone microstructure using spatial autocorrelation analysis

    NASA Astrophysics Data System (ADS)

    Wald, Michael J.; Vasilic, Branimir; Saha, Punam K.; Wehrli, Felix W.

    2005-04-01

    The spatial autocorrelation analysis method represents a powerful, new approach to quantitative characterization of structurally quasi-periodic anisotropic materials such as trabecular bone (TB). The method is applicable to grayscale images and thus does not require any preprocessing, such as segmentation which is difficult to achieve in the limited resolution regime of in vivo imaging. The 3D autocorrelation function (ACF) can be efficiently calculated using the Fourier transform. The resulting trabecular thickness and spacing measurements are robust to the presence of noise and produce values within the expected range as determined by other methods from μCT and μMRI datasets. TB features found from the ACF are shown to correlate well with those determined by the Fuzzy Distance transform (FDT) in the transverse plane, i.e. the plane orthogonal to bone"s major axis. The method is further shown to be applicable to in-vivo μMRI data. Using the ACF, we examine data acquired in a previous study aimed at evaluating the structural implications of male hypogonadism characterized by testosterone deficiency and reduced bone mass. Specifically, we consider the hypothesis that eugonadal and hypogonadal men differ in the anisotropy of their trabecular networks. The analysis indicates a significant difference in trabecular bone thickness and longitudinal spacing between the control group and the testosterone deficient group. We conclude that spatial autocorrelation analysis is able to characterize the 3D structure and anisotropy of trabecular bone and provides new insight into the structural changes associated with osteoporotic trabecular bone loss.

  7. 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.

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

    PubMed

    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.

  9. 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.

  10. 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.

  11. 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.

  12. 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 ...

  13. 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.

  14. 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

  15. Spatial-Decomposition Analysis of Energetics of Ionic Hydration.

    PubMed

    Mogami, George; Suzuki, Makoto; Matubayasi, Nobuyuki

    2016-03-03

    Hydration energetics is analyzed for a set of ions. The analysis is conducted on the basis of a spatial-decomposition formula for the excess partial molar energy of the solute that expresses the thermodynamic quantity as an integral over the whole space of the solute-solvent and solvent-solvent interactions conditioned by the solute-solvent distance. It is observed for all the ionic solutes treated in the present work that the ion-water interaction is favorable at the expense of the water-water interaction and that the variations of the ion-water and water-water interactions with the ion-water distance compensate against each other beyond the contact distance. The extent of spatial localization of the excess partial molar energy is then assessed by introducing a cutoff into the integral expression and examining the convergence with respect to the change in the cutoff. It is found that the excess energy is not quantitatively localized within the first and second hydration layers, while its correlations over the variation of ions are good against the first-layer contribution.

  16. Analysis of cholera epidemics with bacterial growth and spatial movement.

    PubMed

    Wang, Xueying; Wang, Jin

    2015-01-01

    In this work, we propose novel epidemic models (named, susceptible-infected-recovered-susceptible-bacteria) for cholera dynamics by incorporating a general formulation of bacteria growth and spatial variation. In the first part, a generalized ordinary differential equation (ODE) model is presented and it is found that bacterial growth contributes to the increase in the basic reproduction number, [Formula: see text]. With the derived basic reproduction number, we analyse the local and global dynamics of the model. Particularly, we give a rigorous proof on the endemic global stability by employing the geometric approach. In the second part, we extend the ODE model to a partial differential equation (PDE) model with the inclusion of diffusion to capture the movement of human hosts and bacteria in a heterogeneous environment. The disease threshold of this PDE model is studied again by using the basic reproduction number. The results on the threshold dynamics of the ODE and PDE models are compared, and verified through numerical simulation. Additionally, our analysis shows that incorporating diffusive spatial spread does not produce a Turing instability when [Formula: see text] associated with the ODE model is less than the unity.

  17. [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.

  18. Spatial Hierarchical Bayesian Analysis of the Historical Extreme Streamflow

    NASA Astrophysics Data System (ADS)

    Najafi, M. R.; Moradkhani, H.

    2012-04-01

    Analysis of the climate change impact on extreme hydro-climatic events is crucial for future hydrologic/hydraulic designs and water resources decision making. The purpose of this study is to investigate the changes of the extreme value distribution parameters with respect to time to reflect upon the impact of climate change. We develop a statistical model using the observed streamflow data of the Columbia River Basin in USA to estimate the changes of high flows as a function of time as well as other variables. Generalized Pareto Distribution (GPD) is used to model the upper 95% flows during December through March for 31 gauge stations. In the process layer of the model the covariates including time, latitude, longitude, elevation and basin area are considered to assess the sensitivity of the model to each variable. Markov Chain Monte Carlo (MCMC) method is used to estimate the parameters. The Spatial Hierarchical Bayesian technique models the GPD parameters spatially and borrows strength from other locations by pooling data together, while providing an explicit estimation of the uncertainties in all stages of modeling.

  19. Advanced Risk Analysis for High-Performing Organizations

    DTIC Science & Technology

    2006-01-01

    using traditional risk analysis techniques. Mission Assurance Analysis Protocol (MAAP) is one technique that high performers can use to identify and mitigate the risks arising from operational complexity....The operational environment for many types of organizations is changing. Changes in operational environments are driving the need for advanced risk ... analysis techniques. Many types of risk prevalent in today’s operational environments (e.g., event risks, inherited risk) are not readily identified

  20. Metabolic systems analysis to advance algal biotechnology.

    PubMed

    Schmidt, Brian J; Lin-Schmidt, Xiefan; Chamberlin, Austin; Salehi-Ashtiani, Kourosh; Papin, Jason A

    2010-07-01

    Algal fuel sources promise unsurpassed yields in a carbon neutral manner that minimizes resource competition between agriculture and fuel crops. Many challenges must be addressed before algal biofuels can be accepted as a component of the fossil fuel replacement strategy. One significant challenge is that the cost of algal fuel production must become competitive with existing fuel alternatives. Algal biofuel production presents the opportunity to fine-tune microbial metabolic machinery for an optimal blend of biomass constituents and desired fuel molecules. Genome-scale model-driven algal metabolic design promises to facilitate both goals by directing the utilization of metabolites in the complex, interconnected metabolic networks to optimize production of the compounds of interest. Network analysis can direct microbial development efforts towards successful strategies and enable quantitative fine-tuning of the network for optimal product yields while maintaining the robustness of the production microbe. Metabolic modeling yields insights into microbial function, guides experiments by generating testable hypotheses, and enables the refinement of knowledge on the specific organism. While the application of such analytical approaches to algal systems is limited to date, metabolic network analysis can improve understanding of algal metabolic systems and play an important role in expediting the adoption of new biofuel technologies.

  1. Advances in Mössbauer data analysis

    NASA Astrophysics Data System (ADS)

    de Souza, Paulo A.

    1998-08-01

    The whole Mössbauer community generates a huge amount of data in several fields of human knowledge since the first publication of Rudolf Mössbauer. Interlaboratory measurements of the same substance may result in minor differences in the Mössbauer Parameters (MP) of isomer shift, quadrupole splitting and internal magnetic field. Therefore, a conventional data bank of published MP will be of limited help in identification of substances. Data bank search for exact information became incapable to differentiate the values of Mössbauer parameters within the experimental errors (e.g., IS = 0.22 mm/s from IS = 0.23 mm/s), but physically both values may be considered the same. An artificial neural network (ANN) is able to identify a substance and its crystalline structure from measured MP, and its slight variations do not represent an obstacle for the ANN identification. A barrier to the popularization of Mössbauer spectroscopy as an analytical technique is the absence of a full automated equipment, since the analysis of a Mössbauer spectrum normally is time-consuming and requires a specialist. In this work, the fitting process of a Mössbauer spectrum was completely automated through the use of genetic algorithms and fuzzy logic. Both software and hardware systems were implemented turning out to be a fully automated Mössbauer data analysis system. The developed system will be presented.

  2. 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

  3. 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

  4. 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.

  5. Performance analysis of advanced spacecraft TPS

    NASA Technical Reports Server (NTRS)

    Pitts, William C.

    1987-01-01

    The analysis on the feasibility for using metal hydrides in the thermal protection system of cryogenic tanks in space was based on the heat capacity of ice as the phase change material (PCM). It was found that with ice the thermal protection system weight could be reduced by, at most, about 20 percent over an all LI-900 insulation. For this concept to be viable, a metal hydride with considerably more capacity than water would be required. None were found. Special metal hydrides were developed for hydrogen fuel storage applications and it may be possible to do so for the current application. Until this appears promising further effort on this feasibility study does not seem warranted.

  6. The spatial and temporal analysis of forest resources and institutions

    NASA Astrophysics Data System (ADS)

    Schweik, Charles M.

    This study addresses a central puzzle facing the Human Dimensions of Global Change research community: How can we understand the influence of environmental policies on human behavior when little or no information is available on the condition of forest resources? This dissertation capitalizes on new research tools, methods and approaches to overcome the "no information about the resource" problem. Specifically, I combine (1) forest mensuration techniques, (2) Global Positioning Systems, (3) Geographic Information Systems (GIS), (4) spatial statistics, (5) remote sensing, and (6) institutional analysis to analyze forest vegetation patterns. I provide explanation of these patterns by considering the incentive structures driving human decision-making and activity and do this through two studies in very different empirical settings. Both studies apply applicable theory related to human behavior and action. Both examine the incentive structures individuals face as they undertake daily activities related to forest resources. The first study, set in East Chitwan, Nepal, identifies spatial patterns in georeferenced forest inventory data and links these to patterns predicted by optimal foraging subject to institutional constraints. The second study compares forest management in one state and one national forest in Indiana, U.S.A. In this effort, I identify spatio-temporal patterns in the forest vegetation captured by a time series of Landsat multispectral images. The combination of natural forest regrowth and property manager actions in response to incentives and constraints explain these patterns. Substantively, both studies identify change in forest resources associated with combinations of the physical, human community and institutional "landscapes" in their regions. In both cases, geographic attributes of institutions (e.g., laws, rules) are found to influence the type and location of human actions. Methodologically, the two studies provide examples of how to control

  7. 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.

  8. 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.

  9. 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.

  10. Advances in the environmental analysis of polychlorinated naphthalenes and toxaphene.

    PubMed

    Kucklick, John R; Helm, Paul A

    2006-10-01

    Recent advances in the analysis of the chlorinated environmental pollutants polychlorinated naphthalenes (PCNs) and toxaphene are highlighted in this review. Method improvements have been realized for PCNs over the past decade in isomer-specific quantification, peak resolution, and the availability of mass-labeled standards. Toxaphene method advancements include the application of new capillary gas chromatographic (GC) stationary phases, mass spectrometry (MS), especially ion trap MS, and the availability of Standard Reference Materials that are value-assigned for total toxaphene and selected congener concentrations. An area of promise for the separation of complex mixtures such as PCNs and toxaphene is the development of multidimensional GC techniques. The need for continued advancements and efficiencies in the analysis of contaminants such as PCNs and toxaphene remains as monitoring requirements for these compound classes are established under international agreements.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Assessing the context of health care utilization in Ecuador: A spatial and multilevel analysis

    PubMed Central

    2010-01-01

    Background There are few studies that have analyzed the context of health care utilization, particularly in Latin America. This study examines the context of utilization of health services in Ecuador; focusing on the relationship between provision of services and use of both preventive and curative services. Methods This study is cross-sectional and analyzes data from the 2004 National Demographic and Maternal & Child Health dataset. Provider variables come from the Ecuadorian System of Social Indicators (SIISE). Global Moran's I statistic is used to assess spatial autocorrelation of the provider variables. Multilevel modeling is used for the simultaneous analysis of provision of services at the province-level with use of services at the individual level. Results Spatial analysis indicates no significant differences in the density of health care providers among Ecuadorian provinces. After adjusting for various predisposing, enabling, need factors and interaction terms, density of public practice health personnel was positively associated with use of preventive care, particularly among rural households. On the other hand, density of private practice physicians was positively associated with use of curative care, particularly among urban households. Conclusions There are significant public/private, urban/rural gaps in provision of services in Ecuador; which in turn affect people's use of services. It is necessary to strengthen the public health care delivery system (which includes addressing distribution of health workers) and national health information systems. These efforts could improve access to health care, and inform the civil society and policymakers on the advances of health care reform. PMID:20222988

  16. Bistatic Radar Configuration for Soil Moisture Retrieval: Analysis of the Spatial Coverage

    PubMed Central

    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. PMID:22399996

  17. 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…

  18. 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…

  19. Advances in NMR-based biofluid analysis and metabolite profiling.

    PubMed

    Zhang, Shucha; Nagana Gowda, G A; Ye, Tao; Raftery, Daniel

    2010-07-01

    Significant improvements in NMR technology and methods have propelled NMR studies to play an important role in a rapidly expanding number of applications involving the profiling of metabolites in biofluids. This review discusses recent technical advances in NMR spectroscopy based metabolite profiling methods, data processing and analysis over the last three years.

  20. 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...

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  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 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.

  8. 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.

  9. 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.

  10. Safety analysis of the advanced thermionic initiative reactor

    NASA Astrophysics Data System (ADS)

    Lee, Hsing H.; Klein, Andrew C.

    1995-01-01

    Previously, detailed analysis was conducted to assess the technology developed for the Advanced Thermionic Initiative reactor. This analysis included the development of an overall system design code capability and the improvement of analytical models necessary for the assessment of the use of single cell thermionic fuel elements in a low power space nuclear reactor. The present analysis extends this effort to assess the nuclear criticality safety of the ATI reactor for various different scenarios. The analysis discusses the efficacy of different methods of reactor control such as control rods, and control drums.

  11. 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

  12. 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 ...

  13. 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…

  14. 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.

  15. "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

  16. 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

  17. 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…

  18. 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.

  19. 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.

  20. Spatial Stratification of Order As Used in Failure Analysis

    NASA Astrophysics Data System (ADS)

    Leonard, Robert H.; Bachlechner, Martina E.

    2007-03-01

    Silicon nitride deposited on silicon substrates has application in dielectric layers for microelectronics as well as in photovoltaics. During production and operation of components involving silicon/silicon nitride interfaces, stresses and strains can build up at various temperatures resulting in component failure. Using molecular dynamics simulations the influence of temperature and rate of externally applied strain on silicon/silicon nitride interfaces has been analyzed. The primary purpose of this research is to understand the mechanisms leading to the failure of these films. Analyses involving bond lengths and angles have been developed to gain insight into these mechanisms. Methods for stratifying bond lengths and bond angles into unique sub-populations on the basis of spatial orientation have been developed, and have given much insight to how the material behaves, particularly with regards to the Poisson effect. Possible extensions of this stratification method to primitive rings will also be examined. In combination with experimental observations, this analysis will deepen our understanding of the structural properties of silicon/silicon nitride interfaces.

  1. 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.

  2. Consanguinity and late fertility: spatial analysis reveals positive association patterns.

    PubMed

    Lisa, Antonella; Astolfi, Paola; Zei, Gianna; Tentoni, Stefania

    2015-01-01

    The role of consanguinity on human complex traits is an important and controversial issue. In this work we focused on the Sardinian population and examined the effect of consanguineous unions on late female fertility. During the last century the island has been characterized by a high incidence of marriages between relatives, favoured by socio economic conditions and geographical isolation, and by high fertility despite a widespread tendency to delay reproduction. Through spatial analysis techniques, we explored the geographical heterogeneity of consanguinity and late fertility, and identified in Central-Eastern Sardinia a common area with an excess of both traits, where the traits are positively associated. We found that their association did not significantly affect women's fertility in the area, despite the expected negative role of both traits. Intriguingly, this critical zone corresponds well to areas reported by previous studies as being peculiar for a high frequency of centenarians and for lower risk in pregnancy outcome. The proposed approach can be generally exploited to identify target populations on which socioeconomic, biodemographic and genetic data can be collected at the individual level, and deeper analyses carried out to disentangle the determinants of complex biological traits and to investigate their association.

  3. 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…

  4. 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

  5. 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.

  6. Spatial analysis on China's regional air pollutants and CO2 emissions: emission pattern and regional disparity

    NASA Astrophysics Data System (ADS)

    Dong, Liang; Liang, Hanwei

    2014-08-01

    China has suffered from serious air pollution and CO2 emission. Challenges of emission reduction policy not only come from technology advancement, but also generate from the fact that, China has pronounced disparity between regions, in geographical and socioeconomic. How to deal with regional disparity is important to achieve the reduction target effectively and efficiently. This research conducts a spatial analysis on the emission patterns of three air pollutants named SO2, NOx and PM2.5, and CO2, in China's 30 provinces, applied with spatial auto-correlation and multi regression modeling. We further analyze the regional disparity and inequity issues with the approach of Lorenz curve and Gini coefficient. Results highlight that: there is evident cluster effect for the regional air pollutants and CO2 emissions. While emission amount increases from western regions to eastern regions, the emission per GDP is in inverse trend. The Lorenz curve shows an even larger unequal distribution of GDP/emissions than GDP/capita in 30 regions. Certain middle and western regions suffers from a higher emission with lower GDP, which reveal the critical issue of emission leakage. Future policy making to address such regional disparity is critical so as to promote the emission control policy under the “equity and efficiency” principle.

  7. 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.

  8. [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.

  9. Analysis of spatial inhomogeneities in cumulus clouds using high spatial resolution Landsat data

    NASA Technical Reports Server (NTRS)

    Parker, Lindsay; Welch, R. M.; Musil, D. J.

    1986-01-01

    Aircraft observations and high resolution Landsat MSS digital data are used to determine the sizes of spatial inhomogeneities ('holes') in cumulus clouds. The majority of holes are found near cloud edges, but the larger holes tend to be found in cloud interiors. Aircraft measurements show these cloud spatial inhomogeneities in the range of 100 to 500 m, while Landsat data show them in the range of 100 m to 3 km. The number of holes per cloud decreases exponentially with increasing hole diameter. Small clouds not only have smaller holes, but also fewer holes than large clouds. Large clouds have large holes in them, as well as large numbers of the smaller holes. The total cloud area occupied by holes increases with increasing cloud size.

  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. Advanced three-dimensional dynamic analysis by boundary element methods

    NASA Technical Reports Server (NTRS)

    Banerjee, P. K.; Ahma, S.

    1985-01-01

    Advanced formulations of boundary element method for periodic, transient transform domain and transient time domain solution of three-dimensional solids have been implemented using a family of isoparametric boundary elements. The necessary numerical integration techniques as well as the various solution algorithms are described. The developed analysis has been incorporated in a fully general purpose computer program BEST3D which can handle up to 10 subregions. A number of numerical examples are presented to demonstrate the accuracy of the dynamic analyses.

  12. 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.

  13. Spatial analysis of fractured rock around fault zones based on photogrammetric data

    NASA Astrophysics Data System (ADS)

    Deckert, H.; Gessner, K.; Drews, M.; Wellmann, J. F.

    2009-04-01

    The location of hydrocarbon, geothermal or hydrothermal fluids is often bound to fault zones. The fracture systems along these faults play an important role in providing pathways to fluids in the Earth's crust. Thus an evaluation of the change in permeability due to rock deformation is of particular interest in these zones. Recent advances in digital imaging using modern techniques like photogrammetry provide new opportunities to view, analyze and present high resolution geological data in three dimensions. Our method is an extension of the one-dimensional scan-line approach to quantify discontinuities in rock outcrops. It has the advantage to take into account a larger amount of spatial data than conventional manual measurement methods. It enables to recover the entity of spatial information of a 3D fracture pattern, i.e. position, orientation, extent and frequency of fractures. We present examples of outcrop scale datasets in granitic and sedimentary rocks and analyse changes in fracture patterns across fault zones from the host rock to the damage zone. We also present a method to generate discontinuity density maps from 3D surface models generated by digital photogrammetry methods. This methodology has potential for application in rock mass characterization, structural and tectonic studies, the formation of hydrothermal mineral deposits, oil and gas migration, and hydrogeology. Our analysis methods represent important steps towards developing a toolkit to automatically detect and interpret spatial rock characteristics, by taking advantage of the large amount of data that can be collected by photogrammetric methods. This acquisition of parameters defining a 3D fracture pattern allows the creation of synthetic fracture networks following these constraints. The mathematical description of such a synethtical network can be implemented into numerical simulation tools for modeling fluid flow in fracture media. We give an outline of current and future applications of

  14. 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.

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

    PubMed

    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.

  16. Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis

    PubMed Central

    2011-01-01

    -prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively. Conclusions This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The "novel" integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the "high impact" factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas. PMID:22093084

  17. 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.

  18. 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…

  19. [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.

  20. 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.

  1. Analysis of advanced solid rocket motor ignition phenomena

    NASA Astrophysics Data System (ADS)

    Foster, Winfred A., Jr.; Jenkins, Rhonald M.

    1995-07-01

    This report presents the results obtained from an experimental analysis of the flow field in the slots of the star grain section in the head-end of the advanced solid rocket motor during the ignition transient. This work represents an extension of the previous tests and analysis to include the effects of using a center port in conjunction with multiple canted igniter ports. The flow field measurements include oil smear data on the star slot walls, pressure and heat transfer coefficient measurements on the star slot walls and velocity measurements in the star slot.

  2. 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.

  3. Computational analysis of the spatial distribution of mitotic spindle angles in mouse developing airway

    NASA Astrophysics Data System (ADS)

    Tang, Nan; Marshall, Wallace F.

    2013-02-01

    Investigating the spatial information of cellular processes in tissues during mouse embryo development is one of the major technical challenges in development biology. Many imaging methods are still limited to the volumes of tissue due to tissue opacity, light scattering and the availability of advanced imaging tools. For analyzing the mitotic spindle angle distribution in developing mouse airway epithelium, we determined spindle angles in mitotic epithelial cells on serial sections of whole airway of mouse embryonic lungs. We then developed a computational image analysis to obtain spindle angle distribution in three dimensional airway reconstructed from the data obtained from all serial sections. From this study, we were able to understand how mitotic spindle angles are distributed in a whole airway tube. This analysis provides a potentially fast, simple and inexpensive alternative method to quantitatively analyze cellular process at subcellular resolution. Furthermore, this analysis is not limited to the size of tissues, which allows to obtain three dimensional and high resolution information of cellular processes in cell populations deeper inside intact organs.

  4. 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

  5. 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.

  6. 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.

  7. Nano risk analysis: advancing the science for nanomaterials risk management.

    PubMed

    Shatkin, Jo Anne; Abbott, Linda Carolyn; Bradley, Ann E; Canady, Richard Alan; Guidotti, Tee; Kulinowski, Kristen M; Löfstedt, Ragnar E; Louis, Garrick; MacDonell, Margaret; Macdonell, Margaret; Maynard, Andrew D; Paoli, Greg; Sheremeta, Lorraine; Walker, Nigel; White, Ronald; Williams, Richard

    2010-11-01

    Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.

  8. Advanced hydrogen/oxygen thrust chamber design analysis

    NASA Technical Reports Server (NTRS)

    Shoji, J. M.

    1973-01-01

    The results are reported of the advanced hydrogen/oxygen thrust chamber design analysis program. The primary objectives of this program were to: (1) provide an in-depth analytical investigation to develop thrust chamber cooling and fatigue life limitations of an advanced, high pressure, high performance H2/O2 engine design of 20,000-pounds (88960.0 N) thrust; and (2) integrate the existing heat transfer analysis, thermal fatigue and stress aspects for advanced chambers into a comprehensive computer program. Thrust chamber designs and analyses were performed to evaluate various combustor materials, coolant passage configurations (tubes and channels), and cooling circuits to define the nominal 1900 psia (1.31 x 10 to the 7th power N/sq m) chamber pressure, 300-cycle life thrust chamber. The cycle life capability of the selected configuration was then determined for three duty cycles. Also the influence of cycle life and chamber pressure on thrust chamber design was investigated by varying in cycle life requirements at the nominal chamber pressure and by varying the chamber pressure at the nominal cycle life requirement.

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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

    2016-08-18

    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.

  15. Impact of data assimilation on high-resolution rainfall forecasts: A spatial, seasonal, and category analysis

    NASA Astrophysics Data System (ADS)

    V, Rakesh; Goswami, Prashant

    2015-01-01

    a limited area model (LAM), the impact of data assimilation is likely to depend on the background state through lateral boundary forcing; this may introduce certain seasonality in the impact of data assimilation on rainfall forecasting. It is also likely that the impact of data assimilation on forecasts will have certain spatial variability. Finally, owing to the convective nature of rainfall and the roles of parameterization scheme, the impact of data assimilation may depend on the category (intensity) of rainfall. Here these aspects for rainfall forecasts at high resolution were examined. Using a LAM (An advanced version of Weather Research and Forecasting Model), we have carried out twin simulations with and without data assimilation; the simulations without data assimilation are used as the benchmark for assessing the impact of data assimilation. Analysis of simulations for 40 sample days distributed over the years 2012-2014 over Karnataka (southern state in India) is carried out to estimate impact of data assimilation. Various statistical measures show that data assimilation improved the rainfall prediction in most cases; however, there is also strong seasonality and location dependence in impact of data assimilation. Our results also show that improvement due to data assimilation is higher/lower for lower/higher rainfall categories. Analysis shows that the cases where the initial states with data assimilation depart strongly from the first guess generally result in less or even negative impact. It is pointed out that the results have important implications in design of observation system and assessment of impact of forecasts.

  16. 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…

  17. 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.

  18. 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.

  19. Chesapeake Bay Analysis using Time and Spatial Generalized Eigenfunctions

    DTIC Science & Technology

    2007-10-01

    unit of calculation used throughout this pa- per is the normal mode. Like the modes of a guitar string or an organ pipe, systems obeying the Helmholtz...spatial and temporal boundary conditions may reveal a different approach. Consider a guitar string of length, L. Held at both ends, clearly a Dirichlet

  20. Rockfall hazard analysis using LiDAR and spatial modeling

    NASA Astrophysics Data System (ADS)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  1. 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

  2. Spatial Analysis of Childhood Cancer: A Case/Control Study

    PubMed Central

    Ramis, Rebeca; Gómez-Barroso, Diana; Tamayo, Ibon; García-Pérez, Javier; Morales, Antonio; Pardo Romaguera, Elena; López-Abente, Gonzalo

    2015-01-01

    Background Childhood cancer was the leading cause of death among children aged 1-14 years for 2012 in Spain. Leukemia has the highest incidence, followed by tumors of the central nervous system (CNS) and lymphomas (Hodgkin lymphoma, HL, and Non-Hodgkin’s lymphoma, NHL). Spatial distribution of childhood cancer cases has been under concern with the aim of identifying potential risk factors. Objective The two objectives are to study overall spatial clustering and cluster detection of cases of the three main childhood cancer causes, looking to increase etiological knowledge. Methods We ran a case-control study. The cases were children aged 0 to 14 diagnosed with leukemia, lymphomas (HL and NHL) or CNS neoplasm in five Spanish regions for the period 1996-2011. As a control group, we used a sample from the Birth Registry matching every case by year of birth, autonomous region of residence and sex with six controls. We geocoded and validated the address of the cases and controls. For our two objectives we used two different methodologies. For the first, for overall spatial clustering detection, we used the differences of K functions from the spatial point patterns perspective proposed by Diggle and Chetwynd and the second, for cluster detection, we used the spatial scan statistic proposed by Kulldorff with a level for statistical significance of 0.05. Results We had 1062 cases of leukemia, 714 cases of CNS, 92 of HL and 246 of NHL. Accordingly we had 6 times the number of controls, 6372 controls for leukemia, 4284 controls for CNS, 552 controls for HL and 1476 controls for NHL. We found variations in the estimated empirical D(s) for the different regions and cancers, including some overall spatial clustering for specific regions and distances. We did not find statistically significant clusters. Conclusions The variations in the estimated empirical D(s) for the different regions and cancers could be partially explained by the differences in the spatial distribution of

  3. Distributed multi-criteria model evaluation and spatial association analysis

    NASA Astrophysics Data System (ADS)

    Scherer, Laura; Pfister, Stephan

    2015-04-01

    Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the

  4. A sensitivity analysis using different spatial resolution terrain models and flood inundation models

    NASA Astrophysics Data System (ADS)

    Papaioannou, George; Aronica, Giuseppe T.; Loukas, Athanasios; Vasiliades, Lampros

    2014-05-01

    The impact of terrain spatial resolution and accuracy on the hydraulic flood modeling can pervade the water depth and the flood extent accuracy. Another significant factor that can affect the hydraulic flood modeling outputs is the selection of the hydrodynamic models (1D,2D,1D/2D). Human mortality, ravaged infrastructures and other damages can be derived by extreme flash flood events that can be prevailed in lowlands at suburban and urban areas. These incidents make the necessity of a detailed description of the terrain and the use of advanced hydraulic models essential for the accurate spatial distribution of the flooded areas. In this study, a sensitivity analysis undertaken using different spatial resolution of Digital Elevation Models (DEMs) and several hydraulic modeling approaches (1D, 2D, 1D/2D) including their effect on the results of river flow modeling and mapping of floodplain. Three digital terrain models (DTMs) were generated from the different elevation variation sources: Terrestrial Laser Scanning (TLS) point cloud data, classic land surveying and digitization of elevation contours from 1:5000 scale topographic maps. HEC-RAS and MIKE 11 are the 1-dimensional hydraulic models that are used. MLFP-2D (Aronica et al., 1998) and MIKE 21 are the 2-dimensional hydraulic models. The last case consist of the integration of MIKE 11/MIKE 21 where 1D-MIKE 11 and 2D-MIKE 21 hydraulic models are coupled through the MIKE FLOOD platform. The validation process of water depths and flood extent is achieved through historical flood records. Observed flood inundation areas in terms of simulated maximum water depth and flood extent were used for the validity of each application result. The methodology has been applied in the suburban section of Xerias river at Volos-Greece. Each dataset has been used to create a flood inundation map for different cross-section configurations using different hydraulic models. The comparison of resulting flood inundation maps indicates

  5. 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

  6. 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.

  7. 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.

  8. ADVISOR: a systems analysis tool for advanced vehicle modeling

    NASA Astrophysics Data System (ADS)

    Markel, T.; Brooker, A.; Hendricks, T.; Johnson, V.; Kelly, K.; Kramer, B.; O'Keefe, M.; Sprik, S.; Wipke, K.

    This paper provides an overview of Advanced Vehicle Simulator (ADVISOR)—the US Department of Energy's (DOE's) ADVISOR written in the MATLAB/Simulink environment and developed by the National Renewable Energy Laboratory. ADVISOR provides the vehicle engineering community with an easy-to-use, flexible, yet robust and supported analysis package for advanced vehicle modeling. It is primarily used to quantify the fuel economy, the performance, and the emissions of vehicles that use alternative technologies including fuel cells, batteries, electric motors, and internal combustion engines in hybrid (i.e. multiple power sources) configurations. It excels at quantifying the relative change that can be expected due to the implementation of technology compared to a baseline scenario. ADVISOR's capabilities and limitations are presented and the power source models that are included in ADVISOR are discussed. Finally, several applications of the tool are presented to highlight ADVISOR's functionality. The content of this paper is based on a presentation made at the 'Development of Advanced Battery Engineering Models' workshop held in Crystal City, Virginia in August 2001.

  9. 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.

  10. 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.

  11. Creep analysis of fuel plates for the Advanced Neutron Source

    SciTech Connect

    Swinson, W.F.; Yahr, G.T.

    1994-11-01

    The reactor for the planned Advanced Neutron Source will use closely spaced arrays of fuel plates. The plates are thin and will have a core containing enriched uranium silicide fuel clad in aluminum. The heat load caused by the nuclear reactions within the fuel plates will be removed by flowing high-velocity heavy water through narrow channels between the plates. However, the plates will still be at elevated temperatures while in service, and the potential for excessive plate deformation because of creep must be considered. An analysis to include creep for deformation and stresses because of temperature over a given time span has been performed and is reported herein.

  12. Design, analysis and test verification of advanced encapsulation systems

    NASA Technical Reports Server (NTRS)

    Garcia, A., III

    1982-01-01

    An analytical methodology for advanced encapsulation designs was developed. From these methods design sensitivities are established for the development of photovoltaic module criteria and the definition of needed research tasks. Analytical models were developed to perform optical, thermal, electrical and analyses on candidate encapsulation systems. From these analyses several candidate systems were selected for qualification testing. Additionally, test specimens of various types are constructed and tested to determine the validity of the analysis methodology developed. Identified deficiencies and/or discrepancies between analytical models and relevant test data are corrected. Prediction capability of analytical models is improved. Encapsulation engineering generalities, principles, and design aids for photovoltaic module designers is generated.

  13. 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

  14. 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.

  15. 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.

  16. Geographic boundary analysis in spatial and spatio-temporal epidemiology: Perspective and prospects

    PubMed Central

    Jacquez, Geoffrey M.

    2010-01-01

    Geographic boundary analysis is a relatively new approach that is just beginning to be applied in spatial and spatio-temporal epidemiology to quantify spatial variation in health outcomes, predictors and correlates; generate and test epidemiologic hypotheses; to evaluate health-environment relationships; and to guide sampling design. Geographic boundaries are zones of rapid change in the value of a spatially distributed variable, and mathematically may be defined as those locations with a large second derivative of the spatial response surface. Here we introduce a pattern analysis framework based on Value, Change and Association questions, and boundary analysis is shown to fit logically into Change and Association paradigms. This article addresses fundamental questions regarding what boundary analysis can tell us in public health and epidemiology. It explains why boundaries are of interest, illustrates analysis approaches and limitations, and concludes with prospects and future research directions. PMID:21218153

  17. 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…

  18. 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.

  19. 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.

  20. Spatial analysis of mass wasting and topography in coastal British Columbia

    NASA Astrophysics Data System (ADS)

    Martin, Y.; Sjogren, D.

    2003-04-01

    The large inventory of mass wasting data collected by Gimbarzevsky (1988) for the Queen Charlotte Islands, British Columbia is an exceptional data base. The archipelago is located approximately 80 km off the coast of British Columbia and is seismically active, having the potential for earthquakes of large magnitude. The climate is mild, wet (1300 to 3600 mm/yr) and very windy. These factors together contribute to a high frequency of landsliding. The inventory consists of 8328 debris slides, debris avalanches, debris flows and debris torrents. Identification and characterization of events were based on 1:50 000 panchromatic aerial photographs and 1:50 000 map sheets. UTM grid cells of area 1 km^2 were used to classify landslide attributes, such as gradient and aspect. Since the original analysis was undertaken, significant advances have been made in the availability of topographic data and techniques to assess the spatial distribution of mass wasting events and associated landscape attributes. The mass wasting events, originally plotted on 1:50 000 NTS map sheets, are digitized and transferred to the 25-m DEM available for the Queen Charlotte Islands. This format allows for improved analysis of the original data base and, in particular, landscape attributes which may affect mass wasting frequency. Sensitivity analysis is undertaken to explore the effects of improved topographic resolution on results. In addition, the GIS format allows us to extend the original analysis using the sophisticated analytical techniques now available. Gimbarzevsky, P. (1988) Mass Wasting on the Queen Charlotte Islands: A Regional Inventory, BC Ministry of Forests and Lands, Land Management Report, 29, 96 pp.

  1. 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/

  2. 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

  3. 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

  4. 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.

  5. Advanced Video Analysis Needs for Human Performance Evaluation

    NASA Technical Reports Server (NTRS)

    Campbell, Paul D.

    1994-01-01

    Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

  6. 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

  7. 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.

  8. Variogram Analysis of the Spatial Genetic Structure of Continuous Populations Using Multilocus Microsatellite Data

    PubMed Central

    Wagner, Helene H.; Holderegger, Rolf; Werth, Silke; Gugerli, Felix; Hoebee, Susan E.; Scheidegger, Christoph

    2005-01-01

    A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation. PMID:15654102

  9. 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.

  10. Advanced stoichiometric analysis of metabolic networks of mammalian systems.

    PubMed

    Orman, Mehmet A; Berthiaume, Francois; Androulakis, Ioannis P; Ierapetritou, Marianthi G

    2011-01-01

    Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

  11. Advanced analysis and event reconstruction for the CTA Observatory

    NASA Astrophysics Data System (ADS)

    Becherini, Y.; Khélifi, B.; Pita, S.; Punch, M.; CTA Consortium

    2012-12-01

    The planned Cherenkov Telescope Array (CTA) is a future observatory for very-high-energy (VHE) gamma-ray astronomy composed of one site per hemisphere [1]. It aims at 10 times better sensitivity, a better angular resolution and wider energy coverage than current installations such as H.E.S.S., MAGIC and VERITAS. In order to achieve this level of performance, both the design of the telescopes and the analysis algorithms are being studied and optimized within the CTA Monte-Carlo working group. Here, we present ongoing work on the data analysis for both the event reconstruction (energy, direction) and gamma/hadron separation, carried out within the HAP (H.E.S.S. Analysis Package) software framework of the H.E.S.S. collaboration, for this initial study. The event reconstruction uses both Hillas-parameter-based algorithms and an improved version of the 3D-Model algorithm [2]. For the gamma/hadron discrimination, original and robust discriminant variables are used and treated with Boosted Decision Trees (BDTs) in the TMVA [3] (Toolkit for Multivariate Data Analysis) framework. With this advanced analysis, known as Paris-MVA [4], the sensitivity is improved by a factor of ~ 2 in the core range of CTA relative to the standard analyses. Here we present the algorithms used for the reconstruction and discrimination, together with the resulting performance characteristics, with good confidence, since the method has been successfully applied for H.E.S.S.

  12. 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

  13. Spatial behavior analysis at the global level using fractal geometry.

    PubMed

    Sambrook, Roger C

    2008-01-01

    Previous work has suggested that an estimate of fractal dimension can provide a useful metric for quantifying settlement patterns. This study uses fractal methods to investigate settlement patterns at a global scale showing that the scaling behavior of the pattern of the world's largest cities corresponds to that typically observed for coastlines and rivers. This serves to validate the use of fractal dimension as a scale-independent measure of settlement patterns which can be correlated with other physical features. Such a measure may be a useful validation criterion for models of human settlement and spatial behavior.

  14. 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.

  15. 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.

  16. Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

    DTIC Science & Technology

    2010-01-25

    consists of a heating element and thermocouple emplaced in epoxy in a hypodermic needle , which is encased in a porous ceramic matrix. This sensor is...Sensors 2010, 10, 913-932; doi:10.3390/s100100913 sensors ISSN 1424-8220 www.mdpi.com/journal/sensors Article Analysis of Large Scale Spatial...in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to

  17. 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.

  18. 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.

  19. Spatial and Angular Moment Analysis of Continuous and Discretized Particle Transport Problems

    NASA Astrophysics Data System (ADS)

    Brantley, Patrick Shawn

    1998-08-01

    A spatial and angular moment analysis of the linear Boltzmann transport equation is used to compute exact flux-weighted average spatial quantities such as the 'center of mass' and 'radius of gyration' of the flux distribution. This moment analysis is valid for multidimensional general-geometry analytic transport problems, posed in an infinite homogeneous medium, with multiple energy groups and anisotropic scattering. The results from the analysis are used in this thesis to assess how accurately approximations to the transport equation compute these flux-weighted average spatial quantities. The first part of this thesis addresses the theoretical analysis of spatial differencing schemes used to discretize the discrete ordinates approximation of the linear Boltzmann transport equation. Discrete ordinates methods have been utilized for many years to obtain numerical solutions of neutron transport problems in which the optical width of the spatial cells is small. The traditional truncation analysis can be used to assess the accuracy of spatial differencing schemes for these problems. The same discrete ordinates methods have in recent years been utilized for radiative transfer problems characterized by optically thick spatial cells and scattering ratios near unity. In this case, an asymptotic diffusion limit analysis has been applied to discretized transport problems in order to assess the accuracy of spatial differencing schemes. At present, theoretical methods for analyzing discretized transport problems with optically intermediate and thick spatial cells and arbitrary scattering ratios are not available. We develop a moment analysis method for theoretically analyzing discrete ordinates spatial differencing schemes that makes no assumptions on the optical thickness of the spatial cells or on the value of the scattering ratio. The second part of this thesis concerns the Simplified PN (SPN) approximation, a multidimensional generalization of the one-dimensional planar

  20. Sensitivity analyses of spatial population viability analysis models for species at risk and habitat conservation planning.

    PubMed

    Naujokaitis-Lewis, Ilona R; Curtis, Janelle M R; Arcese, Peter; Rosenfeld, Jordan

    2009-02-01

    Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. Spatial correlation analysis of cascading failures: Congestions and Blackouts

    PubMed Central

    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

  9. Spatial correlation analysis of cascading failures: Congestions and Blackouts

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

    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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Recent trends in the advanced analysis of bioactive fatty acids.

    PubMed

    Ruiz-Rodriguez, Alejandro; Reglero, Guillermo; Ibañez, Elena

    2010-01-20

    The consumption of dietary fats have been long associated to chronic diseases such as obesity, diabetes, cancer, arthritis, asthma, and cardiovascular disease; although some controversy still exists in the role of dietary fats in human health, certain fats have demonstrated their positive effect in the modulation of abnormal fatty acid and eicosanoid metabolism, both of them associated to chronic diseases. Among the different fats, some fatty acids can be used as functional ingredients such as alpha-linolenic acid (ALA), arachidonic acid (AA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), gamma-linolenic acid (GLA), stearidonic acid (STA) and conjugated linoleic acid (CLA), among others. The present review is focused on recent developments in FAs analysis, covering sample preparation methods such as extraction, fractionation and derivatization as well as new advances in chromatographic methods such as GC and HPLC. Special attention is paid to trans fatty acids due its increasing interest for the food industry.

  17. Analysis of biofluids by paper spray MS: advances and challenges.

    PubMed

    Manicke, Nicholas E; Bills, Brandon J; Zhang, Chengsen

    2016-03-01

    Paper spray MS is part of a cohort of ambient ionization or direct analysis methods that seek to analyze complex samples without prior sample preparation. Extraction and electrospray ionization occur directly from the paper substrate upon which a dried matrix spot is stored. Paper spray MS is capable of detecting drugs directly from dried blood, plasma and urine spots at the low ng/ml to pg/ml levels without sample preparation. No front end separation is performed, so MS/MS or high-resolution MS is required. Here, we discuss paper spray methodology, give a comprehensive literature review of the use of paper spray MS for bioanalysis, discuss technological advancements and variations on this technique and discuss some of its limitations.

  18. Stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization.

    PubMed

    Veeraraghavan, Rengasayee; Gourdie, Robert G

    2016-11-07

    The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins.

  19. Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization

    PubMed Central

    Veeraraghavan, Rengasayee; Gourdie, Robert G.

    2016-01-01

    The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200–300 nm of each other in the xy-plane and within 500–700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. PMID:27307586

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. A comprehensive analysis of a 3-P (Pa) S spatial parallel manipulator

    NASA Astrophysics Data System (ADS)

    Liu, Yuzhe; Wang, Liping; Wu, Jun; Wang, Jinsong

    2015-03-01

    In this paper, a novel 3-degree of freedom (3-DOF) spatial parallel kinematic machine (PKM) is analyzed. The manipulator owns three main motions (two rotations and one translation) and three concomitant motions (one rotation and two translations). At first, the structure of this spatial PKM is simplified according to the characteristic of each limb. Secondly, the kinematics model of this spatial PKM is set up. In addition, the relationship between the main motions and concomitant motions is studied. The workspaces respectively based on the outputs and inputs are derived and analyzed. Furthermore, the velocity model is put forward. Two indexes based on the velocity model are employed to investigate the performance of this spatial PKM. At last, the output error model can be obtained and simulated. The comprehensive kinematics analysis in this paper is greatly useful for the future applications of this spatial PKM.

  6. Application of standard and advanced open source GIS software functionality for analysis of coordinates obtained by GNSS measurements

    NASA Astrophysics Data System (ADS)

    Ilieva, Tamara

    2016-04-01

    Currently there is wide variety of GNSS measurements used in the geodetic practice. The coordinates obtained by static, kinematic or precise point positioning GNSS measurements could be analyzed by using the standard functionality of any GIS software, but the open source ones give to the users an opportunity to make themselves advanced functionality. There is an option the coordinates obtained by measurements to be stored in spatial geodatabase and information for the precision and time of measurement to be added. The data could be visualized in different coordinate systems and projections and analyzed by applying different types of spatial analysis. The process also could be automated in high degree. An example with test data is prepared. It includes automated loading of files with coordinates obtained by GNSS measurements and additional information for the precision and the time of measurements. Standard and advanced open source GIS software functionality is used for automation of the analysis process. Also, graph theory is implemented for making time series of the data stored in the spatial geodatabase.

  7. Spatial Analysis of Crime Incidence and Adolescent Physical Activity

    PubMed Central

    Robinson, Alyssa I.; Carnes, Fei

    2016-01-01

    Adolescents do not achieve recommended levels of physical activity. Crime is believed to be a barrier to physical activity among youth, but findings are inconsistent. This study compares the spatial distribution of crime incidences and moderate-to-vigorous physical activity (MVPA) among adolescents in Massachusetts between 2011 and 2012, and examines the correlation between crime and MVPA. Eighty adolescents provided objective physical activity (accelerometer) and location (Global Positioning Systems) data. Crime report data were obtained from the city police department. Data were mapped using geographic information systems, and crime and MVPA densities were calculated using kernel density estimations. Spearman’s correlation tested for associations between crime and MVPA. Overall, 1,694 reported crimes and 16,702 minutes of MVPA were included in analyses. A strong positive correlation was present between crime and adolescent MVPA (ρ=0.72, p<0.0001). Crime remained positively associated with MVPA in locations falling within the lowest quartile (ρ=0.43, p<0.0001) and highest quartile (ρ=0.32, p<0.0001) of crime density. This study found a strong positive association between crime and adolescent MVPA, despite research suggesting the opposite relationship. This counterintuitive finding may be explained by the logic of a common destination: neighborhood spaces which are desirable destinations and promote physical activity may likewise attract crime. PMID:26820115

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

    PubMed

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

    2012-01-01

    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.

  9. 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.

  10. Procedures for analysis of spatial relationships among ship survey data and sea surface temperature

    NASA Technical Reports Server (NTRS)

    Berry, J. K.; Sailor, J. K.

    1981-01-01

    The establishment of a limited spatial data base for the U.S. eastern seaboard vicinity is discussed along with the demonstration of computer assisted analysis techniques for investigating spatial patterns and relationships among ship survey data and remotely sensed sea surface temperature. Ship survey variables included concentrations of two zooplankton, two icthyoplankton, and two fish species, in addition to physical data of depth to bottom and surface and bottom water temperatures. Continuous spatial distributions of these data were created by both weighted nearest neighbor and iterative smoothing interpolation techniques. Maps of surface water temperature were created by digitizing GOES satellite images. All mapped data were spatially registered by conversion of latitude and longitude coordinates to rotated Lambert conic conformal rectilinear coordinates and stored in grid format of approximately one hundred square kilometers per cell. The analysis of these data include the generation of statistical summaries and maps describing the joint occurrence among variables.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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

  17. Nuclear methods of analysis in the advanced neutron source

    SciTech Connect

    Robinson, L.; Dyer, F.F.

    1994-12-31

    The Advanced Neutron Source (ANS) research reactor is presently in the conceptual design phase. The thermal power of this heavy water cooled and moderated reactor will be about 350 megawatts. The core volume of 27 liter is designed to provide the optimum neutron fluence rate for the numerous experimental facilities. The peak thermal neutron fluence rate is expected to be slightly less than 10{sup 20} neutrons/m{sup 2}s. In addition to the more than 40 neutron scattering stations, there will be extensive facilities for isotope production, material irradiation and analytical chemistry including neutron activation analysis (NAA) and a slow positron source. The highlight of this reactor will be the capability that it will provide for conducting research using cold neutrons. Two cryostats containing helium-cooled liquid deuterium will be located in the heavy water reflector tank. Each cryostat will provide low-temperature neutrons to researchers via numerous guides. A hot source with two beam tubes and several thermal beam tubes will also be available. The NAA facilities in the ANS will consist of seven pneumatic tubes, one cold neutron guide for prompt gamma-ray neutron activation analysis (PGNAA), and one cold neutron slanted guide for neutron depth profiling (NDP). In addition to these neutron interrogation systems, a gamma-ray irradiation facility for materials testing will be housed in a spent fuel storage pool. This paper will provide detailed information regarding the design and use of these various experimental systems.

  18. Advancement in analysis of Salviae miltiorrhizae Radix et Rhizoma (Danshen).

    PubMed

    Li, Yong-Guo; Song, Long; Liu, Mei; Hu, Zhi-Bi; Wang, Zheng-Tao

    2009-03-13

    This review summarizes the recent advances in the chemical analysis of Danshen and its finished products, including the introduction of the identified bioactive components, analytical methods for quantitative determination of target analytes and fingerprinting authentication, quality criteria of Danshen crude herb and its preparations, as well as the pharmacokinetic and pharmacodynamic studies on the active components of Danshen and its finished products. Danshen contains mainly two types of constituents, the hydrophilic depsides and lipophilic diterpenoidal quinones and both of them are responsible for the pharmacological activities of Danshen. In order to monitor simultaneously both types of components which have different physicochemical properties, numerous analytical methods have been reported using various chromatographic and spectrophotometric technologies. In this review, 110 papers on analysis of Danshen are discussed, various analytical methods and their chromatographic conditions are briefly described and their advantages/disadvantages are compared. For obtaining a quick, accurate and applicable analytical approach for quality evaluation and establishing a harmonized criteria of Danshen and its finished products, the authors' suggestion and opinions are given, including the reasonable selection of marker compounds with high concentration and commercial availability, a simple sample preparation procedure with high recoveries of both the hydrophilic phenols and lipophilic tanshinones, and an optimized chromatographic condition with ideal resolutions of all the target components. The chemical degradation and transformation of the predominant constituent salvianolic acid B in Danshen during processing and manufacturing are also emphasized in order to assure the quality consistency of Danshen containing products.

  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. Boundaries, links and clusters: a new paradigm in spatial analysis?

    PubMed Central

    Jacquez, Geoff M.; Kaufmann, Andy; Goovaerts, Pierre

    2008-01-01

    comprehensive description of spatial pattern. PMID:19023453

  1. Boundaries, links and clusters: a new paradigm in spatial analysis?

    PubMed

    Jacquez, Geoff M; Kaufmann, Andy; Goovaerts, Pierre

    2008-12-01

    of spatial pattern.

  2. 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.

  3. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

    EPA Pesticide Factsheets

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  4. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

    EPA Pesticide Factsheets

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  5. 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…

  6. Arc_Mat: a Matlab-based spatial data analysis toolbox

    NASA Astrophysics Data System (ADS)

    Liu, Xingjian; Lesage, James

    2010-03-01

    This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. Spatial analysis of elderly access to primary care services

    PubMed Central

    Mobley, Lee R; Root, Elisabeth; Anselin, Luc; Lozano-Gracia, Nancy; Koschinsky, Julia

    2006-01-01

    Background Admissions for Ambulatory Care Sensitive Conditions (ACSCs) are considered preventable admissions, because they are unlikely to occur when good preventive health care is received. Thus, high rates of admissions for ACSCs among the elderly (persons aged 65 or above who qualify for Medicare health insurance) are signals of poor preventive care utilization. The relevant geographic market to use in studying these admission rates is the primary care physician market. Our conceptual model assumes that local market conditions serving as interventions along the pathways to preventive care services utilization can impact ACSC admission rates. Results We examine the relationships between market-level supply and demand factors on market-level rates of ACSC admissions among the elderly residing in the U.S. in the late 1990s. Using 6,475 natural markets in the mainland U.S. defined by The Health Resources and Services Administration's Primary Care Service Area Project, spatial regression is used to estimate the model, controlling for disease severity using detailed information from Medicare claims files. Our evidence suggests that elderly living in impoverished rural areas or in sprawling suburban places are about equally more likely to be admitted for ACSCs. Greater availability of physicians does not seem to matter, but greater prevalence of non-physician clinicians and international medical graduates, relative to U.S. medical graduates, does seem to reduce ACSC admissions, especially in poor rural areas. Conclusion The relative importance of non-physician clinicians and international medical graduates in providing primary care to the elderly in geographic areas of greatest need can inform the ongoing debate regarding whether there is an impending shortage of physicians in the United States. These findings support other authors who claim that the existing supply of physicians is perhaps adequate, however the distribution of them across the landscape may not be

  12. [Comparative analysis of spatial organization of myoglobins. II. Secondary structure].

    PubMed

    Korobov, V N; Nazarenko, V I; Radomskiĭ, N F; Starodub, N F

    1992-01-01

    An analysis of probability of distribution curves of alpha-helical sites and bends of polypeptide chains of myoglobins in half-water mammals (beaver, nutria, muskrat, otter) carried out in comparison with those of myoglobins of the horse and Sperm whale (X-ray diffraction analysis has revealed their tertiary structure) has revealed a coincidence of the secondary structure sites end bends of the chain in the studied respiratory hemoproteins of muscles. Despite a considerable number of amino acid substitutions the profiles of alpha-helicity and B-bends of the compared proteins are practically identical. This indicates to the "resistance" of the probability curves to amino acid substitutions and to retention of the tertiary structure of myoglobins in evolutionary remote species of the animals.

  13. Advancing sensitivity analysis to precisely characterize temporal parameter dominance

    NASA Astrophysics Data System (ADS)

    Guse, Björn; Pfannerstill, Matthias; Strauch, Michael; Reusser, Dominik; Lüdtke, Stefan; Volk, Martin; Gupta, Hoshin; Fohrer, Nicola

    2016-04-01

    Parameter sensitivity analysis is a strategy for detecting dominant model parameters. A temporal sensitivity analysis calculates daily sensitivities of model parameters. This allows a precise characterization of temporal patterns of parameter dominance and an identification of the related discharge conditions. To achieve this goal, the diagnostic information as derived from the temporal parameter sensitivity is advanced by including discharge information in three steps. In a first step, the temporal dynamics are analyzed by means of daily time series of parameter sensitivities. As sensitivity analysis method, we used the Fourier Amplitude Sensitivity Test (FAST) applied directly onto the modelled discharge. Next, the daily sensitivities are analyzed in combination with the flow duration curve (FDC). Through this step, we determine whether high sensitivities of model parameters are related to specific discharges. Finally, parameter sensitivities are separately analyzed for five segments of the FDC and presented as monthly averaged sensitivities. In this way, seasonal patterns of dominant model parameter are provided for each FDC segment. For this methodical approach, we used two contrasting catchments (upland and lowland catchment) to illustrate how parameter dominances change seasonally in different catchments. For all of the FDC segments, the groundwater parameters are dominant in the lowland catchment, while in the upland catchment the controlling parameters change seasonally between parameters from different runoff components. The three methodical steps lead to clear temporal patterns, which represent the typical characteristics of the study catchments. Our methodical approach thus provides a clear idea of how the hydrological dynamics are controlled by model parameters for certain discharge magnitudes during the year. Overall, these three methodical steps precisely characterize model parameters and improve the understanding of process dynamics in hydrological

  14. 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

  15. Advance in orientation microscopy: quantitative analysis of nanocrystalline structures.

    PubMed

    Seyring, Martin; Song, Xiaoyan; Rettenmayr, Markus

    2011-04-26

    The special properties of nanocrystalline materials are generally accepted to be a consequence of the high density of planar defects (grain and twin boundaries) and their characteristics. However, until now, nanograin structures have not been characterized with similar detail and statistical relevance as coarse-grained materials, due to the lack of an appropriate method. In the present paper, a novel method based on quantitative nanobeam diffraction in transmission electron microscopy (TEM) is presented to determine the misorientation of adjacent nanograins and subgrains. Spatial resolution of <5 nm can be achieved. This method is applicable to characterize orientation relationships in wire, film, and bulk materials with nanocrystalline structures. As a model material, nanocrystalline Cu is used. Several important features of the nanograin structure are discovered utilizing quantitative analysis: the fraction of twin boundaries is substantially higher than that observed in bright-field images in the TEM; small angle grain boundaries are prominent; there is an obvious dependence of the grain boundary characteristics on grain size distribution and mean grain size.

  16. 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.

  17. Analysis of the spatial variation of hospitalization admissions for hypertension disease in Shenzhen, China.

    PubMed

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

    2014-01-03

    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.

  18. 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

  19. 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.

  20. Advanced predoctoral implant program at UIC: description and qualitative analysis.

    PubMed

    Afshari, Fatemeh S; Yuan, Judy Chia-Chun; Quimby, Anastasiya; Harlow, Rand; Campbell, Stephen D; Sukotjo, Cortino

    2014-05-01

    Dental implant education has increasingly become an integral part of predoctoral dental curricula. However, the majority of implant education emphasizes the restorative aspect as opposed to the surgical. The University of Illinois at Chicago College of Dentistry has developed an Advanced Predoctoral Implant Program (APIP) that provides a select group of students the opportunity to place implants for single-tooth restorations and mandibular overdentures. This article describes the rationale, logistics, experiences, and perspectives of an innovative approach to provide additional learning experiences in the care of patients with partial and complete edentulism using implant-supported therapies. Student and faculty perspectives on the APIP were ascertained via focus group discussions and a student survey. The qualitative analysis of this study suggests that the select predoctoral dental students highly benefited from this experience and intend to increase their knowledge and skills in implant dentistry through formal education following graduation. Furthermore, the survey indicates that the APIP has had a positive influence on the students' interest in surgically placing implants in their future dental practice and their confidence level in restoring and surgically placing implants.

  1. XII Advanced Computing and Analysis Techniques in Physics Research

    NASA Astrophysics Data System (ADS)

    Speer, Thomas; Carminati, Federico; Werlen, Monique

    November 2008 will be a few months after the official start of LHC when the highest quantum energy ever produced by mankind will be observed by the most complex piece of scientific equipment ever built. LHC will open a new era in physics research and push further the frontier of Knowledge This achievement has been made possible by new technological developments in many fields, but computing is certainly the technology that has made possible this whole enterprise. Accelerator and detector design, construction management, data acquisition, detectors monitoring, data analysis, event simulation and theoretical interpretation are all computing based HEP activities but also occurring many other research fields. Computing is everywhere and forms the common link between all involved scientists and engineers. The ACAT workshop series, created back in 1990 as AIHENP (Artificial Intelligence in High Energy and Nuclear Research) has been covering the tremendous evolution of computing in its most advanced topics, trying to setup bridges between computer science, experimental and theoretical physics. Conference web-site: http://acat2008.cern.ch/ Programme and presentations: http://indico.cern.ch/conferenceDisplay.py?confId=34666

  2. 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.

  3. Advances in protein complex analysis using mass spectrometry

    PubMed Central

    Gingras, Anne-Claude; Aebersold, Ruedi; Raught, Brian

    2005-01-01

    Proteins often function as components of larger complexes to perform a specific function, and formation of these complexes may be regulated. For example, intracellular signalling events often require transient and/or regulated protein–protein interactions for propagation, and protein binding to a specific DNA sequence, RNA molecule or metabolite is often regulated to modulate a particular cellular function. Thus, characterizing protein complexes can offer important insights into protein function. This review describes recent important advances in mass spectrometry (MS)-based techniques for the analysis of protein complexes. Following brief descriptions of how proteins are identified using MS, and general protein complex purification approaches, we address two of the most important issues in these types of studies: specificity and background protein contaminants. Two basic strategies for increasing specificity and decreasing background are presented: whereas (1) tandem affinity purification (TAP) of tagged proteins of interest can dramatically improve the signal-to-noise ratio via the generation of cleaner samples, (2) stable isotopic labelling of proteins may be used to discriminate between contaminants and bona fide binding partners using quantitative MS techniques. Examples, as well as advantages and disadvantages of each approach, are presented. PMID:15611014

  4. Advances in the analysis of iminocyclitols: Methods, sources and bioavailability.

    PubMed

    Amézqueta, Susana; Torres, Josep Lluís

    2016-05-01

    Iminocyclitols are chemically and metabolically stable, naturally occurring sugar mimetics. Their biological activities make them interesting and extremely promising as both drug leads and functional food ingredients. The first iminocyclitols were discovered using preparative isolation and purification methods followed by chemical characterization using nuclear magnetic resonance spectroscopy. In addition to this classical approach, gas and liquid chromatography coupled to mass spectrometry are increasingly used; they are highly sensitive techniques capable of detecting minute amounts of analytes in a broad spectrum of sources after only minimal sample preparation. These techniques have been applied to identify new iminocyclitols in plants, microorganisms and synthetic mixtures. The separation of iminocyclitol mixtures by chromatography is particularly difficult however, as the most commonly used matrices have very low selectivity for these highly hydrophilic structurally similar molecules. This review critically summarizes recent advances in the analysis of iminocyclitols from plant sources and findings regarding their quantification in dietary supplements and foodstuffs, as well as in biological fluids and organs, from bioavailability studies.

  5. 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.

  6. Steady-State Analysis Model for Advanced Fuel Cycle Schemes.

    SciTech Connect

    SARTORI, ENRICO

    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 are 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.

  7. Steady-state Analysis Model for Advanced Fuelcycle Schemes

    SciTech Connect

    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 are 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).

  8. 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.

  9. 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.

  10. Spatial-temporal data model and fractal analysis of transportation network in GIS environment

    NASA Astrophysics Data System (ADS)

    Feng, Yongjiu; Tong, Xiaohua; Li, Yangdong

    2008-10-01

    How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

  11. The spatial relationship analysis of regional development potential and resource and environment carrying capacity in China

    NASA Astrophysics Data System (ADS)

    Zhang, Yan; Xu, Jianhua; Zeng, Gang; Shen, Qi; Hu, Qing

    2008-10-01

    The main goal in this study is to explore the spatial relationship of Chinese regional development potential (DP) and resource & environment carrying capacity (REC) in 2000 and 2006 by using meta-synthesis of spatial statistical analysis and GIS technique. The results show that: The spatial distribution trend of DP and REC are overall gradient descending from coastal to inland, then to the western provinces. They all demonstrate that spatial agglomeration with global significant, namely high-DP regions aggregated in the east, low-DP regions aggregated in the west. The high-REC of central, eastern and southern China are improved and aggregated, but the low-REC aggregated in northwest. Chinese regional DP and REC are divided into five different kinds of regions based on the results of k-means clustering analysis and spatial clustering, which demonstrate that each area's DP and REC's spatial association measure is not very obviously. Compared to the high-DP region, the low-DP region is more restricted to the REC.

  12. Flow blockage analysis for the advanced neutron source reactor

    SciTech Connect

    Stovall, T.K.; Crabtree, J.A.; Felde, D.K.; Park, J.E.

    1996-01-01

    The Advanced Neutron Source (ANS) reactor was designed to provide a research tool with capabilities beyond those of any existing reactors. One portion of its state-of-the-art design required high-speed fluid flow through narrow channels between the fuel plates in the core. Experience with previous reactors has shown that fuel plate damage can occur when debris becomes lodged at the entrance to these channels. Such debris disrupts the fluid flow to the plate surfaces and can prevent adequate cooling of the fuel. Preliminary ANS designs addressed this issue by providing an unheated entrance length for each fuel plate so that any flow disruption would recover, thus providing adequate heat removal from the downstream, heated portions of the fuel plates. As part of the safety analysis, the adequacy of this unheated entrance length was assessed using both analytical models and experimental measurements. The Flow Blockage Test Facility (FBTF) was designed and built to conduct experiments in an environment closely matching the ANS channel geometry. The FBTF permitted careful measurements of both heat transfer and hydraulic parameters. In addition to these experimental efforts, a thin, rectangular channel was modeled using the Fluent computational fluid dynamics computer code. The numerical results were compared with the experimental data to benchmark the hydrodynamics of the model. After this comparison, the model was extended to include those elements of the safety analysis that were difficult to measure experimentally. These elements included the high wall heat flux pattern and variable fluid properties. The results were used to determine the relationship between potential blockage sizes and the unheated entrance length required.

  13. Meta-Analysis and Advancement of Brucellosis Vaccinology

    PubMed Central

    Carvalho, Tatiane F.; Haddad, João Paulo A.; Paixão, Tatiane A.

    2016-01-01

    Background/Objectives In spite of all the research effort for developing new vaccines against brucellosis, it remains unclear whether these new vaccine technologies will in fact become widely used. The goal of this study was to perform a meta-analysis to identify parameters that influence vaccine efficacy as well as a descriptive analysis on how the field of Brucella vaccinology is advancing concerning type of vaccine, improvement of protection on animal models over time, and factors that may affect protection in the mouse model. Methods A total of 117 publications that met the criteria were selected for inclusion in this study, with a total of 782 individual experiments analyzed. Results Attenuated (n = 221), inactivated (n = 66) and mutant (n = 102) vaccines provided median protection index above 2, whereas subunit (n = 287), DNA (n = 68), and vectored (n = 38) vaccines provided protection indexes lower than 2. When all categories of experimental vaccines are analyzed together, the trend line clearly demonstrates that there was no improvement of the protection indexes over the past 30 years, with a low negative and non significant linear coefficient. A meta-regression model was developed including all vaccine categories (attenuated, DNA, inactivated, mutant, subunit, and vectored) considering the protection index as a dependent variable and the other parameters (mouse strain, route of vaccination, number of vaccinations, use of adjuvant, challenge Brucella species) as independent variables. Some of these variables influenced the expected protection index of experimental vaccines against Brucella spp. in the mouse model. Conclusion In spite of the large number of publication over the past 30 years, our results indicate that there is not clear trend to improve the protective potential of these experimental vaccines. PMID:27846274

  14. 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.

  15. An effect of spatial resolution of remotely sensed data for vegetation analysis over an arid zone

    NASA Astrophysics Data System (ADS)

    Oguro, Y.; Tsuchiya, K.; Setoguchi, R.

    1997-05-01

    One of the recent trends in the development of an optical sensor of earth observation satellite is a great importance of spatial resolution and the order of 1 - 2 meter resolution sensor is under development. To cope with this trend analyses are made on the effect of extremely fine spatial resolution of land cover classification accuracy utilizing spatial resolution of 20 cm and 1 meter aerial multi-sensor data of an arid reddish land where desertification is taking place in small spatial scale. Applied methods are supervised classification with combination of multi-level slice(pallarelpiped classification) and the Mahalanobis distance. The result of analysis indicates that the difference is within several percentage for 3 categories of bare land, vegetation and shadow. It was also found that small dried sparse grass land which can be recognized in 20 cm resolution image is difficult to extract in 1 meter resolution image.

  16. Spatial smoothing of canonical correlation analysis for steady state visual evoked potential based brain computer interfaces.

    PubMed

    Ryu, Shingo; Higashi, Hiroshi; Tanaka, Toshihisa; Nakauchi, Shigeki; Minami, Tetsuto

    2016-08-01

    Brain computer interface (BCI) is a system for communication between people and computers via brain activity. Steady-state visual evoked potentials (SSVEPs), a brain response observed in EEG, are evoked by flickering stimuli. SSVEP is one of the promising paradigms for BCI. Canonical correlation analysis (CCA) is widely used for EEG signal processing in SSVEP-based BCIs. However, the classification accuracy of CCA with short signal length is low. In order to solve the problem, we propose a regularization which works in such a way that the CCA spatial filter becomes spatially smooth to give robustness in short signal length condition. The spatial filter is designed in a parameter space spanned by a spatially smooth basis which are given by a graph Fourier transform of three dimensional electrode coordinates. We compared the classification accuracy of the proposed regularized CCA with the standard CCA. The result shows that the proposed CCA outperforms the standard CCA in short signal length condition.

  17. Analysis of the spatial correlation structure exhibited by daily rainfall in Southern Italy

    NASA Astrophysics Data System (ADS)

    Sirangelo, B.; Ferrari, E.

    2014-10-01

    The investigation of the spatial correlation structure exhibited by ground-based rainfall measurements can provide useful results for understanding, from a climatic point of view, the effects produced by the interaction between meteorological patterns and morphological features of a given territory. The central aspect of this study is the description of the spatial inhomogeneity and anisotropy that characterizes the correlation structure of daily rainfall. In the proposed approach, the analysis is developed by assuming that the correlation structure exhibited by the rainfall heights can be interpreted through a suitable deformation of the spatial coordinates providing a homogeneous and isotropic field. The technique has been applied to the daily rainfall recorded at the rain gauges network of the Crati River basin (Southern Italy). The results show that the elliptic deformations of the spatial structure exhibited by the correlation structure of the rain gauges are closely related to the physiographic features of the territory.

  18. 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.

  19. 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

  20. 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.

  1. Spatial temporal analysis of urban heat hazard in Tangerang City

    NASA Astrophysics Data System (ADS)

    Wibowo, Adi; Kuswantoro; Ardiansyah; Rustanto, Andry; Putut Ash Shidiq, Iqbal

    2016-11-01

    Urban heat is a natural phenomenon which might caused by human activities. The human activities were represented by various types of land-use such as urban and non-urban area. The aim of this study is to identify the urban heat behavior in Tangerang City as it might threats the urban environment. This study used three types of remote sensing data namely, Landsat TM, Landsat ETM+ and Landsat OLI-TIRS, to capture the urban heat behavior and to analysis the urban heat signature of Tangerang City in 2001, 2012, 2013, 2014, 2015 and 2016. The result showed that urban heat signature change dynamically each month based on the sun radiation. The urban heat island covered only small part of Tangerang City in 2001, but it was significantly increased and reached 50% of the area in 2012. Based on the result on urban heat signature, the threshold for threatening condition is 30 oC which recognized from land surface temperature (LST). The effective temperature (ET) index explains that condition as warm, uncomfortable, increase stress due to sweating and blood flow and may causing cardiovascular disorder.

  2. Weighting of spatial and spectro-temporal cues for auditory scene analysis by human listeners.

    PubMed

    Bremen, Peter; Middlebrooks, John C

    2013-01-01

    The auditory system creates a neuronal representation of the acoustic world based on spectral and temporal cues present at the listener's ears, including cues that potentially signal the locations of sounds. Discrimination of concurrent sounds from multiple sources is especially challenging. The current study is part of an effort to better understand the neuronal mechanisms governing this process, which has been termed "auditory scene analysis". In particular, we are interested in spatial release from masking by which spatial cues can segregate signals from other competing sounds, thereby overcoming the tendency of overlapping spectra and/or common temporal envelopes to fuse signals with maskers. We studied detection of pulsed tones in free-field conditions in the presence of concurrent multi-tone non-speech maskers. In "energetic" masking conditions, in which the frequencies of maskers fell within the ± 1/3-octave band containing the signal, spatial release from masking at low frequencies (~600 Hz) was found to be about 10 dB. In contrast, negligible spatial release from energetic masking was seen at high frequencies (~4000 Hz). We observed robust spatial release from masking in broadband "informational" masking conditions, in which listeners could confuse signal with masker even though there was no spectral overlap. Substantial spatial release was observed in conditions in which the onsets of the signal and all masker components were synchronized, and spatial release was even greater under asynchronous conditions. Spatial cues limited to high frequencies (>1500 Hz), which could have included interaural level differences and the better-ear effect, produced only limited improvement in signal detection. Substantially greater improvement was seen for low-frequency sounds, for which interaural time differences are the dominant spatial cue.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. Spatial analysis of water quality trends in the Han River basin, South Korea.

    PubMed

    Chang, Heejun

    2008-07-01

    Spatial patterns of water quality trends for 118 sites in the Han River basin of South Korea were examined for eight parameters-temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (TP), and total nitrogen (TN). A non-parametric seasonal Mann-Kendall's test determined the significance of trends for each parameter for each site between 1993 and 2002. There are no significant trends in temperature, but TN concentrations increased for the majority of the monitoring stations. DO, BOD, COD, pH, SS, and TP show increasing or decreasing trends with approximately half of the stations exhibiting no trends. Urban land cover is positively associated with increases in water pollution and included as an important explanatory variable for the variations in all water quality parameters except pH. Topography and soil factors further explain the spatial variations in pH, COD, BOD, and SS. BOD, COD, SS, and TP variations are consistently better explained by 100m buffer scale analysis, but DO are better explained by the whole basin scale analysis. Local water quality management or geology could further explain some variations of water quality. Non-point-source pollution exhibits strong positive spatial autocorrelation as measured by Moran's I, indicating that the incorporation of spatial dimensions into water quality assessment enhances our understanding of spatial patterns of water quality. The spatial regression models, compared to ordinary least square (OLS) models, always better explain the variations in water quality. This study suggests that spatial analysis of watershed data at different scales should be a vital part of identifying the fundamental spatio-temporal distribution of water quality.

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

    PubMed

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

    2017-04-01

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

  9. Spatial and dynamical handwriting analysis in mild cognitive impairment.

    PubMed

    Kawa, Jacek; Bednorz, Adam; Stępień, Paula; Derejczyk, Jarosław; Bugdol, Monika

    2017-03-01

    Background and Objectives Standard clinical procedure of Mild Cognitive Impairment (MCI) assessment employs time-consuming tests of psychological evaluation and requires the involvement of specialists. The employment of quantitative methods proves to be superior to clinical judgment, yet reliable, fast and inexpensive tests are not available. This study was conducted as a first step towards the development of a diagnostic tool based on handwriting. Methods In this paper the handwriting sample of a group of 37 patients with MCI (mean age 76.1±5.8) and 37 healthy controls (mean age 74.8±5.7) was collected using a Livescribe Echo Pen while completing three tasks: (1) regular writing, (2) all-capital-letters writing, and (3) single letter multiply repeated. Parameters differentiating both groups were selected in each task. Results Subjects with confirmed MCI needed more time to complete task one (median 119.5s, IQR - interquartile range - 38.1 vs. 95.1s, IQR 29.2 in control and MCI group, p-value <0.05) and two (median 84.2s, IQR 49.2 and 53.7s, IQR 30.5 in control and MCI group) as their writing was significantly slower. These results were associated with a longer time to complete a single stroke of written text. The written text was also noticeably larger in the MCI group in all three tasks (e.g. median height of the text block in task 2 being 22.3mm, IQR 12.9 in MCI and 20.2mm, IQR 8.7 in control group). Moreover, the MCI group showed more variation in the dynamics of writing: longer pause between strokes in task 1 and 2. The all-capital-letters task produced most of the discriminating features. Conclusion Proposed handwriting features are significant in distinguishing MCI patients. Inclusion of quantitative handwriting analysis in psychological assessment may be a step forward towards a fast MCI diagnosis.

  10. 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

  11. Numerical analysis of single pulse and differential pulse-width pair BOTDA systems in the high spatial resolution regime.

    PubMed

    Minardo, Aldo; Bernini, Romeo; Zeni, Luigi

    2011-09-26

    A numerical analysis of conventional and differential pulse-width pair Brillouin optical time domain analysis systems is reported. The tests are focused on determining the performance of these systems especially in terms of spatial resolution, as a function of the pulse characteristics. A new definition of spatial resolution is given, based on analysis of the shape of the Brillouin gain spectrum. The influence of the rise/fall time of the pulse light to the spatial resolution is also studied.

  12. Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

    NASA Astrophysics Data System (ADS)

    Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

    2016-04-01

    We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

  13. BATSE analysis techniques for probing the GRB spatial and luminosity distributions

    NASA Technical Reports Server (NTRS)

    Hakkila, Jon; Meegan, Charles A.

    1992-01-01

    The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

  14. 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

  15. Engineering design and analysis of advanced physical fine coal cleaning technologies

    SciTech Connect

    Not Available

    1992-01-20

    This project is sponsored by the United States Department of Energy (DOE) for the Engineering Design and Analysis of Advanced Physical Fine Coal Cleaning Technologies. The major goal is to provide the simulation tools for modeling both conventional and advanced coal cleaning technologies. This DOE project is part of a major research initiative by the Pittsburgh Energy Technology Center (PETC) aimed at advancing three advanced coal cleaning technologies-heavy-liquid cylconing, selective agglomeration, and advanced froth flotation through the proof-of-concept (POC) level.

  16. 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

  17. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes.

    PubMed

    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

    2016-04-12

    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.

  18. 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.

  19. 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

  20. Factorial Kriging Analysis as a tool for explaining the complex spatial distribution of metals in sediments.

    PubMed

    Alary, Claire; Demougeot-Renard, Hélène

    2010-01-15

    Rivers flowing through urbanized and industrial areas are usually greatly damaged by anthropogenic activities discharging contaminants. Characterizing the spatial distribution of pollutants in sediments is of high importance for selecting a suitable remediation operation, but is a complex task because this spatial variability is the result of various physical and chemical mechanisms occurring at different scales. Factorial Kriging Analysis (FKA) was applied on data collected in a canalized river (Scarpe, France) for that purpose, because this geostatistical technique allows to decompose a given variable into components of different spatial correlations and map them separately. This decomposition is meaningful provided that it can be related to physical phenomena occurring at the identified spatial scales. FKA applied to Cd and Zn concentrations in sediments of the Scarpe river proved to be effective, allowing their mapping to be decomposed in a first map related to a short-range spatial correlation corresponding to hot spots interpreted as the impact of industrial and urban inputs located along the canal, and a second map related to a long-range spatial variability associated with long pollutant plumes interpreted as the effect of one major upstream pollutant input.

  1. Advancing Risk Analysis for Nanoscale Materials: Report from an International Workshop on the Role of Alternative Testing Strategies for Advancement: Advancing Risk Analysis for Nanoscale Materials

    SciTech Connect

    Shatkin, J. A.; Ong, Kimberly J.; Beaudrie, Christian; Clippinger, Amy J.; Hendren, Christine Ogilvie; Haber, Lynne T.; Hill, Myriam; Holden, Patricia; Kennedy, Alan J.; Kim, Baram; MacDonell, Margaret; Powers, Christina M.; Sharma, Monita; Sheremeta, Lorraine; Stone, Vicki; Sultan, Yasir; Turley, Audrey; White, Ronald H.

    2016-08-01

    The Society for Risk Analysis (SRA) has a history of bringing thought leadership to topics of emerging risk. In September 2014, the SRA Emerging Nanoscale Materials Specialty Group convened an international workshop to examine the use of alternative testing strategies (ATS) for manufactured nanomaterials (NM) from a risk analysis perspective. Experts in NM environmental health and safety, human health, ecotoxicology, regulatory compliance, risk analysis, and ATS evaluated and discussed the state of the science for in vitro and other alternatives to traditional toxicology testing for NM. Based on this review, experts recommended immediate and near-term actions that would advance ATS use in NM risk assessment. Three focal areas-human health, ecological health, and exposure considerations-shaped deliberations about information needs, priorities, and the next steps required to increase confidence in and use of ATS in NM risk assessment. The deliberations revealed that ATS are now being used for screening, and that, in the near term, ATS could be developed for use in read-across or categorization decision making within certain regulatory frameworks. Participants recognized that leadership is required from within the scientific community to address basic challenges, including standardizing materials, protocols, techniques and reporting, and designing experiments relevant to real-world conditions, as well as coordination and sharing of large-scale collaborations and data. Experts agreed that it will be critical to include experimental parameters that can support the development of adverse outcome pathways. Numerous other insightful ideas for investment in ATS emerged throughout the discussions and are further highlighted in this article.

  2. 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.

  3. 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…

  4. 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.

  5. 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.

  6. Adaptive Spatial Filtering with Principal Component Analysis for Biomedical Photoacoustic Imaging

    NASA Astrophysics Data System (ADS)

    Nagaoka, Ryo; Yamazaki, Rena; Saijo, Yoshifumi

    Photoacoustic (PA) signal is very sensitive to noise generated by peripheral equipment such as power supply, stepping motor or semiconductor laser. Band-pass filter is not effective because the frequency bandwidth of the PA signal also covers the noise frequency. The objective of the present study is to reduce the noise by using an adaptive spatial filter with principal component analysis (PCA).

  7. 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…

  8. Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain.

    PubMed

    Chou, Shen-Ju; Wang, Chindi; Sintupisut, Nardnisa; Niou, Zhen-Xian; Lin, Chih-Hsu; Li, Ker-Chau; Yeang, Chen-Hsiang

    2016-01-20

    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.

  9. 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

  10. 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.

  11. 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

  12. A method for quantitative analysis of spatially variable physiological processes across leaf surfaces.

    PubMed

    Aldea, Mihai; Frank, Thomas D; DeLucia, Evan H

    2006-11-01

    Many physiological processes are spatially variable across leaf surfaces. While maps of photosynthesis, stomatal conductance, gene expression, water transport, and the production of reactive oxygen species (ROS) for individual leaves are readily obtained, analytical methods for quantifying spatial heterogeneity and combining information gathered from the same leaf but with different instruments are not widely used. We present a novel application of tools from the field of geographical imaging to the multivariate analysis of physiological images. Procedures for registration and resampling, cluster analysis, and classification provide a general framework for the analysis of spatially resolved physiological data. Two experiments were conducted to illustrate the utility of this approach. Quantitative analysis of images of chlorophyll fluorescence and the production of ROS following simultaneous exposure of soybean leaves to atmospheric O3 and soybean mosaic virus revealed that areas of the leaf where the operating quantum efficiency of PSII was depressed also experienced an accumulation of ROS. This correlation suggests a causal relationship between oxidative stress and inhibition of photosynthesis. Overlaying maps of leaf surface temperature and chlorophyll fluorescence following a photoinhibition treatment indicated that areas with low operating quantum efficiency of PSII also experienced reduced stomatal conductance (high temperature). While each of these experiments explored the covariance of two processes by overlaying independent images gathered with different instruments, the same procedures can be used to analyze the covariance of information from multiple images. The application of tools from geographic image analysis to physiological processes occurring over small spatial scales will help reveal the mechanisms generating spatial variation across leaves.

  13. Quantum diffraction and interference of spatially correlated photon pairs and its Fourier-optical analysis

    SciTech Connect

    Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

    2006-07-15

    We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns.

  14. 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

  15. NEIGHBOUR-IN: Image processing software for spatial analysis of animal grouping.

    PubMed

    Caubet, Yves; Richard, Freddie-Jeanne

    2015-01-01

    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.

  16. Spatial mapping of correlation profile in Brillouin optical correlation domain analysis

    NASA Astrophysics Data System (ADS)

    Somepalli, Bhargav; Venkitesh, Deepa; Srinivasan, Balaji

    2017-04-01

    We report an approach to spatially map the correlation profile along the sensing fiber in Brillouin optical correlation domain analysis by pulsing the pump radiation. Simulations are carried out to demonstrate the influence of frequency modulation parameters of a narrow linewidth source on the width of the correlation profile and its peak position. The simulation results are validated through controlled experiments. The correlation profile is mapped over 1 km long fiber with spatial resolution of 1 m, limited only by the finite lifetime of acoustic phonons in the silica fiber.

  17. 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

  18. A Spatial Cluster Analysis of Tractor Overturns in Kentucky from 1960 to 2002

    PubMed Central

    Saman, Daniel M.; Cole, Henry P.; Odoi, Agricola; Myers, Melvin L.; Carey, Daniel I.; Westneat, Susan 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. PMID:22291980

  19. 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.

  20. 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.

  1. 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.

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

    PubMed Central

    2012-01-01

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

  3. Spatial analysis of Tuberculosis in Rio de Janeiro in the period from 2005 to 2008 and associated socioeconomic factors using micro data and global spatial regression models.

    PubMed

    Magalhães, Monica de Avelar Figueiredo Mafra; Medronho, Roberto de Andrade

    2017-03-01

    The present study analyses the spatial pattern of tuberculosis (TB) from 2005 to 2008 by identifying relevant socioeconomic variables for the occurrence of the disease through spatial statistical models. This ecological study was performed in Rio de Janeiro using new cases. The census sector was used as the unit of analysis. Incidence rates were calculated, and the Local Empirical Bayesian method was used. The spatial autocorrelation was verified with Moran's Index and local indicators of spatial association (LISA). Using Spearman's test, variables with significant correlation at 5% were used in the models. In the classic multivariate regression model, the variables that fitted better to the model were proportion of head of family with an income between 1 and 2 minimum wages, proportion of illiterate people, proportion of households with people living alone and mean income of the head of family. These variables were inserted in the Spatial Lag and Spatial Error models, and the results were compared. The former exhibited the best parameters: R2 = 0.3215, Log-Likelihood = -9228, Akaike Information Criterion (AIC) = 18,468 and Schwarz Bayesian Criterion (SBC) = 18,512. The statistical methods were effective in the identification of spatial patterns and in the definition of determinants of the disease providing a view of the heterogeneity in space, allowing actions aimed more at specific populations.

  4. [Spatial variability and quantitative analysis of field factors based on GIS].

    PubMed

    Chen, Rongrong; Zhou, Zhiguo; Cao, Weixing; Dai, Tingbo

    2004-09-01

    The objective of this research was to investigate the variability and the quantitative relationships among soil nutrients and crop growth status and yield. All data were analyzed by both classical statistics and geostatistics based on GIS. Soil properties included soil pH, total N, organic matter, available P and available K, while crop growth status was indicated by SPAD, LAI and SPAD x LAI. All parameters except soil pH exhibited spatial correlation. Soil total N and organic matter, SPAD, LAI and SPAD x LAI were all correlated to rice yield. Kriged interpolation maps provided good indication of the spatial variability in crop yield and growth status. Spatial interpolation and correlation analysis proved that SPAD x LAI was more indicative of crop growth status than individual variables, and useful for implementing growth season and topdressing as needed.

  5. 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.

  6. 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.

  7. 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.

  8. Skunk and raccoon rabies in the eastern United States: temporal and spatial analysis.

    PubMed

    Guerra, Marta A; Curns, Aaron T; Rupprecht, Charles E; Hanlon, Cathleen A; Krebs, John W; Childs, James E

    2003-09-01

    Since 1981, an epizootic of raccoon rabies has spread throughout the eastern United States. A concomitant increase in reported rabies cases in skunks has raised concerns that an independent maintenance cycle of rabies virus in skunks could become established, affecting current strategies of wildlife rabies control programs. Rabies surveillance data from 1981 through 2000 obtained from the health departments of 11 eastern states were used to analyze temporal and spatial characteristics of rabies epizootics in each species. Spatial analysis indicated that epizootics in raccoons and skunks moved in a similar direction from 1990 to 2000. Temporal regression analysis showed that the number of rabid raccoons predicted the number of rabid skunks through time, with a 1-month lag. In areas where the raccoon rabies virus variant is enzootic, spatio-temporal analysis does not provide evidence that this rabies virus variant is currently cycling independently among skunks.

  9. Spatial error in geocoding physician location data from the AMA Physician Masterfile: implications for spatial accessibility analysis.

    PubMed

    McLafferty, Sara; Freeman, Vincent L; Barrett, Richard E; Luo, Lan; Shockley, Alisa

    2012-04-01

    The accuracy of geocoding hinges on the quality of address information that serves as input to the geocoding process; however errors associated with poor address quality are rarely studied. This paper examines spatial errors that arise due to incorrect address information with respect to physician location data in the United States. Studies of spatial accessibility to physicians in the U.S. typically rely on data from the American Medical Association's Physician Masterfile. These data are problematic because a substantial proportion of physicians only report a mailing address, which is often the physician's home (residential) location, rather than the address for the location where health care is provided. The incorrect geocoding of physicians' practice locations based on inappropriate address information results in a form of geocoding error that has not been widely analyzed. Using data for the Chicago metropolitan region, we analyze the extent and implications of geocoding error for measurement of spatial accessibility to primary care physicians. We geocode the locations of primary care physicians based on mailing addresses and office addresses. The spatial mismatch between the two is computed at the county, zip code and point location scales. Although mailing and office address locations are quite close for many physicians, they are far apart (>20 km) for a substantial minority. Kernel density estimation is used to characterize the spatial distribution of physicians based on office and mailing addresses and to identify areas of high spatial mismatch between the two. Errors are socially and geographically uneven, resulting in overestimation of physician supply in some high-income suburban communities, and underestimation in certain central city locations where health facilities are concentrated. The resulting errors affect local measures of spatial accessibility to primary care, biasing statistical analyses of the associations between spatial access to care and

  10. 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.

  11. A preliminary spatial analysis of diagnosed stroke disease in Osun state, Nigeria

    PubMed Central

    Adzandeh, Ayila Emmanuel; Awope, John; Oviasu, Osaretin Isoken

    2016-01-01

    Introduction There have been a number of clinical studies on diagnosed Stroke disease. However, there have been few studies on the geographical disparities for stroke. This study investigates the spatial pattern of stroke disease reflecting socio-demographic characteristics in the State. Methods Stroke patients' admissions for 22 years (from 1990 to 2012) were examined. Their socio-demographic characteristics were extracted from their health records and analyzed. The location of the stroke patients were categorized by Local Governments Areas (LGAs). Spatial maps were generated and produced in a Geographical Information System (GIS) environment. It involves the analysis of the distribution of stroke cases in relation to their underlying population to determine the areas of high and low density of diagnosed cases across the state. Results The result highlighted the spatial distribution of diagnosed stroke cases and also highlighted the areas of concern regarding their spatial distribution within the state. Social inequalities in stroke were persistent as incidence rates in urban areas (North) were around 3 times higher than in the rural areas (South). However, this could be due to better healthcare access in the urban areas than in the rural areas as there were disparities in the distribution of healthcare facilities involved in administering care to stroke patients in Osun State. Conclusion The outcome of this study appears to indicate that spatial inequalities in the access to Stroke healthcare is a concern that needs to be addressed in order to manage the disease adequately. PMID:28250887

  12. 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.

  13. 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.

  14. 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

  15. Effect of Major Royal Jelly Proteins on Spatial Memory in Aged Rats: Metabolomics Analysis in Urine.

    PubMed

    Chen, Di; Liu, Fang; Wan, Jian-Bo; Lai, Chao-Qiang; Shen, Li-Rong

    2017-04-10

    Royal jelly (RJ) produced by worker honeybees is the sole food for the queen bee throughout her life as well as the larvae of worker bees for the first 3 days after hatching. Supplementation of RJ in the diet has been shown to increase spatial memory in rodents. However, the key constituents in RJ responsible for improvement of cognitive function are unknown. Our objective was to determine if the major royal jelly proteins (MRJPs) extracted from RJ can improve the spatial memory of aged rats. The spatial memory assay using the Morris water maze test was administered once to rats after a 14-week feeding. Metabolomics analysis based on quadrupole time-of-flight mass spectrometry was conducted to examine the differences in compounds from urine. Aged male rats fed MRJPs showed improved spatial memory up to 48.5% when compared to the control male aged rats fed distilled water. The metabolite pattern of the MRJPs-fed aged rats was regressed to that of the young rats. Compounds altered by MRJPs were mapped to nicotinate and nicotinamide metabolism, cysteine taurine metabolism, and energy metabolism pathways. In summary, MRJPs may improve spatial memory and possess the potential for prevention of cognitive impairment via the cysteine and taurine metabolism and energy metabolism pathways in aged rats.

  16. 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.

  17. 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.

  18. 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.

  19. 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)

  20. Temporal and spatial gait parameters in patients dependent on walking assistance after stroke: reliability and agreement between simple and advanced methods of assessment.

    PubMed

    Høyer, Ellen; Opheim, Arve; Strand, Liv Inger; Moe-Nilssen, Rolf

    2014-01-01

    The aim of this study was to investigate the reliability of temporal and spatial gait parameters in patients dependent on walking assistance after severe stroke, and to examine agreement between simple and advanced methods. Twenty-one patients, admitted for in-patient multidisciplinary rehabilitation, were assessed repeatedly for walking function, both in a test corridor and a gait laboratory (3D camera system) before and after 11 weeks of rehabilitation. The test-retest reliability was examined using intraclass correlation (ICC1.1), and measurement error was reported by within-subject standard deviation (Sw). The agreement between different methods for assessing walking speed, cadence and step length was explored by Bland-Altman plots. High to excellent test-retest reliability was found between trials, both when assessed in the corridor (ICC: 0.93-0.99) and in the laboratory (ICC: 0.88-0.99). Agreement between methods was satisfactory at baseline and was higher after the rehabilitation period. Agreement was found to be slightly better at lower walking speeds and for shorter step lengths. The results implicate that temporal-spatial gait parameters may be measured reliably by both simple and advanced methods in dependent walkers after stroke. A high level of agreement was found between the two methods for walking speed, cadence and average step length at both test points.

  1. Advanced demodulation technique for the extraction of tissue optical properties and structural orientation contrast in the spatial frequency domain

    NASA Astrophysics Data System (ADS)

    Nadeau, Kyle P.; Durkin, Anthony J.; Tromberg, Bruce J.

    2014-05-01

    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.

  2. Time limits in testing: An analysis of eye movements and visual attention in spatial problem solving.

    PubMed

    Roach, Victoria A; Fraser, Graham M; Kryklywy, James H; Mitchell, Derek G V; Wilson, Timothy D

    2017-03-30

    Individuals with an aptitude for interpreting spatial information (high mental rotation ability: HMRA) typically master anatomy with more ease, and more quickly, than those with low mental rotation ability (LMRA). This article explores how visual attention differs with time limits on spatial reasoning tests. Participants were assorted to two groups based on their mental rotation ability scores and their eye movements were collected during these tests. Analysis of salience during testing revealed similarities between MRA groups in untimed conditions but significant differences between the groups in the timed one. Question-by-question analyses demonstrate that HMRA individuals were more consistent across the two timing conditions (κ = 0.25), than the LMRA (κ = 0.013). It is clear that the groups respond to time limits differently and their apprehension of images during spatial problem solving differs significantly. Without time restrictions, salience analysis suggests LMRA individuals attended to similar aspects of the images as HMRA and their test scores rose concomitantly. Under timed conditions however, LMRA diverge from HMRA attention patterns, adopting inflexible approaches to visual search and attaining lower test scores. With this in mind, anatomical educators may wish to revisit some evaluations and teaching approaches in their own practice. Although examinations need to evaluate understanding of anatomical relationships, the addition of time limits may induce an unforeseen interaction of spatial reasoning and anatomical knowledge. Anat Sci Educ. © 2017 American Association of Anatomists.

  3. 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.

  4. Where do Overweight Women in Ghana Live? Answers from Exploratory Spatial Data Analysis

    PubMed Central

    2012-01-01

    Contextual influence on health outcomes is increasingly becoming an important area of research. Analytical techniques such as spatial analysis help explain the variations and dynamics in health inequalities across different context and among different population groups. This paper explores spatial clustering in body mass index among Ghanaian women by analysing data from the 2008 Ghana Demographic and Health Survey using exploratory spatial data analysis techniques. Overweight was a more common occurrence in urban areas than in rural areas. Close to a quarter of the clusters in Ghana, mostly those in the southern sector contained women who were overweight. Women who lived in clusters where the women were overweight were more likely to live around other clusters where the women were also overweight. The results suggest that the urban environment could be a potential contributing factor to the high levels of obesity in urban areas of Ghana. There is the need for researchers to include a spatial dimension to obesity research in Ghana paying particular attention the urban environment.

  5. 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.

  6. 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.

  7. 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

  8. Genome Reshuffling for Advanced Intercross Permutation (GRAIP): Simulation and permutation for advanced intercross population analysis

    SciTech Connect

    Pierce, Jeremy; Broman, Karl; Lu, Lu; Chesler, Elissa J; Zhou, Guomin; Airey, David; Birmingham, Amanda; Williams, Robert

    2008-04-01

    Background: Advanced intercross lines (AIL) are segregating populations created using a multi-generation breeding protocol for fine mapping complex trait loci (QTL) in mice and other organisms. Applying QTL mapping methods for intercross and backcross populations, often followed by na ve permutation of individuals and phenotypes, does not account for the effect of AIL family structure in which final generations have been expanded and leads to inappropriately low significance thresholds. The critical problem with na ve mapping approaches in AIL populations is that the individual is not an exchangeable unit. Methodology/Principal Findings: The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also describe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. GRAIP permutes a more interchangeable unit in the final generation crosses - the parental genome - and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome-wide significance thresholds and locus-specific Pvalues for AILs and other populations with similar family structures. We contrast GRAIP with na ve permutation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses). A na ve permutation using coat color as a model phenotype demonstrates high false-positive locus identification and uncertain significance levels, which are corrected using GRAIP. GRAIP also detects an established hippocampus weight locus and a new locus, Hipp9a. Conclusions and Significance: GRAIP determines appropriate genome-wide significance thresholds and locus-specific Pvalues for AILs and other populations with similar family structures. The effect of

  9. Spatial-Temporal Analysis of Environmental Data of North Beijing District Using Hilbert-Huang Transform

    PubMed Central

    Wang, Wenyong; Moran, William

    2016-01-01

    Temperature, solar radiation and water are major important variables in ecosystem models which are measurable via wireless sensor networks (WSN). Effective data analysis is necessary to extract significant spatial and temporal information. In this work, information regarding the long term variation of seasonal field environment conditions is explored using Hilbert-Huang transform (HHT) based analysis on the wireless sensor network data collection. The data collection network, consisting of 36 wireless nodes, covers an area of 100 square kilometres in Yanqing, the northwest of Beijing CBD, in China and data collection involves environmental parameter observations taken over a period of three months in 2011. The analysis used the empirical mode decomposition (EMD/EEMD) to break a time sequence of data down to a finite set of intrinsic mode functions (IMFs). Both spatial and temporal properties of data explored by HHT analysis are demonstrated. Our research shows potential for better understanding the spatial-temporal relationships among environmental parameters using WSN and HHT. PMID:27936056

  10. 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

  11. 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.

  12. A Guide for Analysis Using Advanced Distributed Simulation (ADS)

    DTIC Science & Technology

    1997-01-01

    within a broader analysis strategy, experimental design, exercise preparation and management , and post-exercise analysis. Because it is impossible to...34* Decisionmakers, such as program managers , who need to determine how ADS might support their analysis needs and how to interpret ADS analysis products... Management and System Acquisition. Contents Preface ..................................................... iii Figures

  13. Spatial-Spectral EOF analysis of AIRS data: an exploratory study

    NASA Astrophysics Data System (ADS)

    Huang, X.; Yung, Y. L.; Lambrigtsen, B. H.

    2003-12-01

    We apply spatial-spectral EOF analysis to 14 days of AIRS (Atmospheric Infrared Sounder) calibrated radiance data collected over the tropics and subtropics (32S to 32N) from July 1 to July 14, 2003. We limit our analysis to the nadir-view (scan angle less than 5o) spectra only. After the quality control procedure, we have an average of 1400 spectra over this period for each 4o by 5o grid box. We obtain a 14-day averaged spectrum for each grid box and apply EOF analysis to these averaged spectra to obtain principal components in spectrally resolved radiance and associated spatial patterns. The first principal component (PC1) can explain more than 90% of the total variance. With the second principal component (PC2), these two leading principal components can explain more than 99% of the total variance. The PC1 spectral features are consistent with spectral features due to the change of surface (or cloud deck) emission temperature. A couple of features can be clearly seen in the PC1 spatial map: ITCZ due to the low emission temperature of optically-thick high cloud, Sahara due to the high surface emission temperature and the clear sky. The spatial map of PC1 closely resembles that of NCEP/NCAR reanalysis of outgoing longwave radiation over the same period. It is also highly correlated with the map of high cloud amount. Both the spectral features and spatial map indicate that the PC1 is mainly due to the spatial variation of cloud emission temperature (for grid boxes with the optically thick clouds) and surface temperature. The PC2 shows spectral features similar to those due to the change of the optical depth of low clouds. Moreover, the PC2 spatial map shows maxima near the coasts of Peru, Namibia and California, as well as over the southern ocean west of Australia. All these regions are known for high frequency of marine stratus. Unlike the traditional approach of observing low clouds from the visible reflectance, these results indicate that we can actually see

  14. Prospects for higher spatial resolution quantitative X-ray analysis using transition element L-lines

    NASA Astrophysics Data System (ADS)

    Statham, P.; Holland, J.

    2014-03-01

    Lowering electron beam kV reduces electron scattering and improves spatial resolution of X-ray analysis. However, a previous round robin analysis of steels at 5 - 6 kV using Lα-lines for the first row transition elements gave poor accuracies. Our experiments on SS63 steel using Lα-lines show similar biases in Cr and Ni that cannot be corrected with changes to self-absorption coefficients or carbon coating. The inaccuracy may be caused by different probabilities for emission and anomalous self-absorption for the La-line between specimen and pure element standard. Analysis using Ll(L3-M1)-lines gives more accurate results for SS63 plausibly because the M1-shell is not so vulnerable to the atomic environment as the unfilled M4,5-shell. However, Ll-intensities are very weak and WDS analysis may be impractical for some applications. EDS with large area SDD offers orders of magnitude faster analysis and achieves similar results to WDS analysis with Lα-lines but poorer energy resolution precludes the use of Ll-lines in most situations. EDS analysis of K-lines at low overvoltage is an alternative strategy for improving spatial resolution that could give higher accuracy. The trade-off between low kV versus low overvoltage is explored in terms of sensitivity for element detection for different elements.

  15. Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks

    NASA Astrophysics Data System (ADS)

    Zhang, Cheng; Bansal, Bhupesh; Branicio, Paulo S.; Kalia, Rajiv K.; Nakano, Aiichiro; Sharma, Ashish; Vashishta, Priya

    2006-09-01

    State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms such as K-ring analysis a challenge. This paper proposes an algorithm to improve the efficiency of ring analysis of large graphs, exploiting properties of K-rings and spatial correlations of vertices in the graph. The algorithm uses dual-tree expansion (DTE) and spatial hash-function tagging (SHAFT) to optimize computation and memory access. Numerical tests show nearly perfect linear scaling of the algorithm. Also a parallel implementation of the DTE + SHAFT algorithm achieves high scalability. The algorithm has been successfully employed to analyze large MD simulations involving up to 500 million atoms.

  16. 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.

  17. Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

    PubMed Central

    Gil, José F.; Nasser, Julio R.; Cajal, Silvana P.; Juarez, Marisa; Acosta, Norma; Cimino, Rubén O.; Diosque, Patricio; Krolewiecki, Alejandro J.

    2010-01-01

    We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina. PMID:20207869

  18. The emergence of spatial cyberinfrastructure

    PubMed Central

    Wright, Dawn J.; Wang, Shaowen

    2011-01-01

    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

  19. The emergence of spatial cyberinfrastructure.

    PubMed

    Wright, Dawn J; Wang, Shaowen

    2011-04-05

    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.

  20. Genome Reshuffling for Advanced Intercross Permutation (GRAIP): Simulation and permutation for advanced intercross population analysis

    SciTech Connect

    Pierce, Jeremy; Broman, Karl; Chesler, Elissa J; Zhou, Guomin; Airey, David; Birmingham, Amanda; Williams, Robert

    2008-01-01

    Abstract Background Advanced intercross lines (AIL) are segregating populations created using a multigeneration breeding protocol for fine mapping complex traits in mice and other organisms. Applying quantitative trait locus (QTL) mapping methods for intercross and backcross populations, often followed by na ve permutation of individuals and phenotypes, does not account for the effect of family structure in AIL populations in which final generations have been expanded and leads to inappropriately low significance thresholds. The critical problem with a na ve mapping approach in such AIL populations is that the individual is not an exchangeable unit given the family structure. Methodology/Principal Findings The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also describe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. RAIP permutes a more interchangeable unit in the final generation crosses - the parental genome - and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome- ide significance thresholds and locus-specific P-values for AILs and other populations with similar family structures. We contrast GRAIP with na ve permutation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses). A na ve permutation using coat color as a model phenotype demonstrates high false-positive locus identification and uncertain significance levels in our AIL population, which are corrected by use of GRAIP. We also show that GRAIP detects an established hippocampus weight locus and a new locus, Hipp9a. Conclusions and Significance GRAIP determines appropriate genome-wide significance thresholds

  1. Genotypic and Spatial Analysis of Mycobacterium tuberculosis Transmission in a High-Incidence Urban Setting

    PubMed Central

    Ribeiro, Fabíola Karla Correa; Pan, William; Bertolde, Adelmo; Vinhas, Solange Alves; Peres, Renata Lyrio; Riley, Lee; Palaci, Moisés; Maciel, Ethel Leonor

    2015-01-01

    Background. Genotyping Mycobacterium tuberculosis isolates allows study of dynamics of tuberculosis transmission, while geoprocessing allows spatial analysis of clinical and epidemiological data. Here, genotyping data and spatial analysis were combined to characterize tuberculosis transmission in Vitória, Brazil, to identify distinct neighborhoods and risk factors associated with recent tuberculosis transmission. Methods. From 2003 to 2007, 503 isolates were genotyped by IS6110 restriction fragment length polymorphism (RFLP) and spoligotyping. The analysis included kernel density estimation, K-function analysis, and a t test distance analysis. Mycobacterium tuberculosis isolates belonging to identical RFLP patterns (clusters) were considered to represent recent tuberculosis infection (cases). Results. Of 503 genotyped isolates, 242 (48%) were categorized into 70 distinct clusters belonging to 12 RFLP families. The proportion of recent transmission was 34.2%. Kernel density maps indicated 3 areas of intense concentration of cases. K-function analysis of the largest RFLP clusters and families showed they co-localized in space. The distance analysis confirmed these results and demonstrated that unique strain patterns (controls) randomly distributed in space. A logit model identified young age, positive smear test, and lower Index of Quality of Urban Municipality as risk factors for recent transmission. The predicted probabilities for each neighborhood were mapped and identified neighborhoods with high risk for recent transmission. Conclusions. Spatial and genotypic clustering of M. tuberculosis isolates revealed ongoing active transmission of tuberculosis caused by a small subset of strains in specific neighborhoods of the city. Such information provides an opportunity to target tuberculosis transmission control, such as through rigorous and more focused contact investigation programs. PMID:25948063

  2. 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.

  3. Wavelet analysis of location and intensity of spatial rhythms in hippocampus

    NASA Astrophysics Data System (ADS)

    Lavrova, Anastasia I.; Postnikov, Eugene B.

    2013-10-01

    Hippocampal formation is responsible for the memory processes and spatial navigation; however, underlaying mechanisms and firing location of specific neuronal cells are still poorly investigated. We propose the wavelet analysis for the description of generation of polyrhythmic signals in the human hippocampal system. We analyze experimental data obtained earlier in hippocampal shearers. This method allows comparing with the simple Fourier method to investigate firing patterns in details, namely, to characterize their location and firing intensity.

  4. 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.

  5. WE-EF-303-04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies

    SciTech Connect

    Rinaldi, I; Parodi, K; Krah, N

    2015-06-15

    Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 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 X-ray radiography convolved with a Gaussian kernel equal to the proton beam spot-size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set-up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non-optimized radiographies. These results represent a major step towards clinical

  6. 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.

  7. 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

  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.

  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. Spatial assessment of air quality patterns in Malaysia using multivariate analysis

    NASA Astrophysics Data System (ADS)

    Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

    2012-12-01

    This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

  11. Effects of spatial smoothing on inter-subject correlation based analysis of FMRI.

    PubMed

    Pajula, Juha; Tohka, Jussi

    2014-11-01

    This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively. In this study, ISC and GLM analyses were computed with two experimental and one simulated block-design datasets. The test statistics and the detected activation areas were compared numerically with correlation and Dice similarity measures, respectively. The study verified that (1) the choice of the filter substantially affected the activations detected by ISC analysis, (2) the detected activations according to ISC and GLM methods were highly similar regardless of the smoothing kernel and (3) the effect of spatial smoothing was mildly smaller on ISC than GLM analysis. Our results indicated that a good selection of the full width at half maximum of the Gaussian smoothing kernel for ISC was slightly larger than double the original voxel size.

  12. Advanced space system analysis software. Technical, user, and programmer guide

    NASA Technical Reports Server (NTRS)

    Farrell, C. E.; Zimbelman, H. F.

    1981-01-01

    The LASS computer program provides a tool for interactive preliminary and conceptual design of LSS. Eight program modules were developed, including four automated model geometry generators, an associated mass properties module, an appendage synthesizer module, an rf analysis module, and an orbital transfer analysis module. The existing rigid body controls analysis module was modified to permit analysis of effects of solar pressure on orbital performance. A description of each module, user instructions, and programmer information are included.

  13. 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

  14. A spatial and temporal analysis of child pedestrian crashes in Santiago, Chile.

    PubMed

    Blazquez, Carola A; Celis, Marcela S

    2013-01-01

    This paper presents a spatial and temporal analysis of child pedestrian crash data in Santiago, Chile during the period 2000-2008. First, this study identified seven critical areas with high child pedestrian crash risk employing kernel density estimation, and subsequently, statistically significant clusters of the main attributes associated to these crashes in each critical area were determined in a geographic information systems environment. Moran's I index test identified a positive spatial autocorrelation on crash contributing factors, time of day, straight road sections and intersections, and roads without traffic signs within the critical areas during the studied period, whereas a random spatial pattern was identified for crashes related to the age attribute. No statistical significance in the spatial relationship was obtained in child pedestrian crashes with respect to gender, weekday, and month of the year. The results from this research aid in determining the areas in which enhanced school-age child pedestrian safety is required by developing and implementing effective enforcement, educational, and engineering preventive measures.

  15. 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 (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.

  16. Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems.

    PubMed

    Wu, B M; van Bruggen, A H; Subbarao, K V; Pennings, G G

    2001-02-01

    ABSTRACT The epidemiology of lettuce downy mildew has been investigated extensively in coastal California. However, the spatial patterns of the disease and the distance that Bremia lactucae spores can be transported have not been determined. During 1995 to 1998, we conducted several field- and valley-scale surveys to determine spatial patterns of this disease in the Salinas valley. Geostatistical analyses of the survey data at both scales showed that the influence range of downy mildew incidence at one location on incidence at other locations was between 80 and 3,000 m. A linear relationship was detected between semivariance and lag distance at the field scale, although no single statistical model could fit the semi-variograms at the valley scale. Spatial interpolation by the inverse distance weighting method with a power of 2 resulted in plausible estimates of incidence throughout the valley. Cluster analysis in geographic information systems on the interpolated disease incidence from different dates demonstrated that the Salinas valley could be divided into two areas, north and south of Salinas City, with high and low disease pressure, respectively. Seasonal and spatial trends along the valley suggested that the distinction between the downy mildew conducive and nonconducive areas might be determined by environmental factors.

  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. Rural tourism spatial distribution based on multi-criteria decision analysis and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Hongxian; Yang, Qingsheng

    2008-10-01

    To study spatial distribution of rural tourism can provide scientific decision basis for developing rural economics. Traditional ways of tourism spatial distribution have some limitations in quantifying priority locations of tourism development on small units. They can only produce the overall tourism distribution locations and whether locations are suitable to tourism development simply while the tourism develop ranking with different decision objectives should be considered. This paper presents a way to find ranking of location of rural tourism development in spatial by integrating multi-criteria decision analysis (MCDA) and geography information system (GIS). In order to develop country economics with inconvenient transportation, undeveloped economy and better tourism resource, these locations should be firstly develop rural tourism. Based on this objective, the tourism develop priority utility of each town is calculated with MCDA and GIS. Towns which should be first develop rural tourism can be selected with higher tourism develop priority utility. The method is used to find ranking of location of rural tourism in Ningbo City successfully. The result shows that MCDA is an effective way for distribution rural tourism in spatial based on special decision objectives and rural tourism can promote economic development.

  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. Systems genetic analysis of hippocampal neuroanatomy and spatial learning in mice

    PubMed Central

    Delprato, Anna; Bonheur, Brice; Algéo, Marie-Paule; Rosay, Philippe; Lu, Lu; Williams, Robert W.

    2016-01-01

    Variation in hippocampal neuroanatomy correlates well with spatial learning ability in mice. Here we have studied both hippocampal neuroanatomy and behavior in 53 isogenic BXD recombinant strains derived from C57BL/6J and DBA/2J parents. A combination of experimental, neuroinformatic, and systems genetics methods were used to test the genetic bases of variation and covariation among traits. Data were collected on seven hippocampal subregions in CA3 and CA4 after testing spatial memory in an 8-arm radial maze task. Quantitative trait loci (QTLs) were identified for hippocampal structure, including the areas of the intra- and infrapyramidal mossy fibers, stratum radiatum, and stratum pyramidale, and for a spatial learning parameter, error rate. We identified multiple loci and gene variants linked to either structural differences or behavior. Gpc4 and Tenm2 are strong candidate genes that may modulate intra- and infrapyramidal mossy fiber areas. Analysis of gene-expression networks and trait correlations highlight several processes influencing morphometrical variation and spatial learning. PMID:26449520

  2. 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.

  3. Spatial and temporal analysis of DIII-D 3D magnetic diagnostic data.

    PubMed

    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.

  4. Spatial and temporal analysis of DIII-D 3D magnetic diagnostic data

    DOE PAGES

    Strait, E. J.; King, J. D.; Hanson, J. M.; ...

    2016-08-11

    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. Lastly, applications of the analysis include detection of non-rotating MHD instabilities, plasma control, and validation of MHD stability and 3D equilibrium models.

  5. Spatial Fourier Analysis of a Free-Free Beam for Structural Damage Detection

    NASA Astrophysics Data System (ADS)

    Bhagat, Mihir; Ganguli, Ranjan

    2014-07-01

    Free-free beams (FFB) are used to model many structures, such as missiles, rockets, MEMS (Micro Electro Mechanical Systems), etc. This paper aims to illustrate a novel structural health monitoring method-Fourier analysis of mode shapes of damaged beams-and extend it to the case of FFB. The damaged mode shapes of FFB are obtained by a finite element model and then studied using spatial Fourier analysis. The effect of noise in the mode shape data is considered and it is found that the Fourier coefficients provide a useful indication about the location and size of damage.

  6. Spatially Resolved Analysis of Amines Using a Fluorescence Molecular Probe: Molecular Analysis of IDPs

    NASA Technical Reports Server (NTRS)

    Clemett, S. J.; Messenger, S.; Thomas-Keprta, K. L.; Wentworth, S. J.; Robinson, G. A.; McKay, D. S.

    2002-01-01

    Some Interplanetary Dust Particles (IDPs) have large isotope anomalies in H and N. To address the nature of the carrier phase, we are developing a procedure to spatially resolve the distribution of organic species on IDP thin sections utilizing fluorescent molecular probes. Additional information is contained in the original extended abstract.

  7. 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...

  8. Advances in nanowire transistors for biological analysis and cellular investigation.

    PubMed

    Li, Bor-Ran; Chen, Chiao-Chen; Kumar, U Rajesh; Chen, Yit-Tsong

    2014-04-07

    Electrical biosensors based on silicon nanowire field-effect transistors (SiNW-FETs) have attracted enormous interest in the biosensing field. SiNW-FETs have proven to be significant and efficient in detecting diverse biomolecular species with the advantages of high probing sensitivity, target selectivity, real-time recording and label-free detection. In recent years, significant advances in biosensors have been achieved, particularly for cellular investigation and biomedical diagnosis. In this critical review, we will report on the latest developments in biosensing with SiNW-FETs and discuss recent advancements in the innovative designs of SiNW-FET devices. This critical review introduces the basic instrumental setup and working principle of SiNW-FETs. Technical approaches that attempted to enhance the detection sensitivity and target selectivity of SiNW-FET sensors are discussed. In terms of applications, we review the recent achievements with SiNW-FET biosensors for the investigations of protein-protein interaction, DNA/RNA/PNA hybridization, virus detection, cellular recording, biological kinetics, and clinical diagnosis. In addition, the novel architecture designs of the SiNW-FET devices are highlighted in studies of live neuron cells, electrophysiological measurements and other signal transduction pathways. Despite these remarkable achievements, certain improvements remain necessary in the device performance and clinical applications of FET-based biosensors; thus, several prospects about the future development of nanowire transistor-based instruments for biosensing employments are discussed at the end of this review.

  9. Design and analysis of advanced flight planning concepts

    NASA Technical Reports Server (NTRS)

    Sorensen, John A.

    1987-01-01

    The objectives of this continuing effort are to develop and evaluate new algorithms and advanced concepts for flight management and flight planning. This includes the minimization of fuel or direct operating costs, the integration of the airborne flight management and ground-based flight planning processes, and the enhancement of future traffic management systems design. Flight management (FMS) concepts are for on-board profile computation and steering of transport aircraft in the vertical plane between a city pair and along a given horizontal path. Flight planning (FPS) concepts are for the pre-flight ground based computation of the three-dimensional reference trajectory that connects the city pair and specifies the horizontal path, fuel load, and weather profiles for initializing the FMS. As part of these objectives, a new computer program called EFPLAN has been developed and utilized to study advanced flight planning concepts. EFPLAN represents an experimental version of an FPS. It has been developed to generate reference flight plans compatible as input to an FMS and to provide various options for flight planning research. This report describes EFPLAN and the associated research conducted in its development.

  10. Landscape object-based analysis of wetland plant functional types: the effects of spatial scale, vegetation classes and classifier methods

    NASA Astrophysics Data System (ADS)

    Dronova, I.; Gong, P.; Wang, L.; Clinton, N.; Fu, W.; Qi, S.

    2011-12-01

    Remote sensing-based vegetation classifications representing plant function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based image analysis (OBIA) and machine-learning algorithms offer new classification tools; however, few comparisons of different algorithms and spatial scales have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from 30-m Landsat TM scene at the peak of spring growing season. We targeted major PFTs (C3 grasses, C3 forbs and different types of C4 grasses and aquatic vegetation) that are both key players in system's biogeochemical cycles and critical providers of waterbird habitat. Classification results were compared among: a) several object segmentation scales (with average object sizes 900-9000 m2); b) several families of statistical classifiers (including Bayesian, Logistic, Neural Network, Decision Trees and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and more detailed 6-class set. We found that classification benefited from object-based approach which allowed including object shape, texture and context descriptors in classification. While a number of classifiers achieved high accuracy at the finest pixel-equivalent segmentation scale, the highest accuracies and best agreement among algorithms occurred at coarser object scales. No single classifier was consistently superior across all scales, although selected algorithms of Neural Network, Logistic and K-Nearest Neighbors families frequently provided the best discrimination of classes at different scales. The choice of vegetation categories also affected classification accuracy. The 6-class set allowed for higher individual class accuracies but lower overall accuracies than the 3-class set because

  11. 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.

  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. 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.

  14. Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis

    PubMed Central

    Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Jiang, Baofa

    2016-01-01

    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

  15. 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

  16. Advanced Polymer Composite Molding Through Intelligent Process Analysis and Control

    DTIC Science & Technology

    2004-11-30

    In this project. process analysis of Resin Transfer Molding (RTM) was carried out and adaptive process control models were developed. In addition, a...aforementioned work in three separate sections: (1) process analysis and adaptive control modeling, (2) manufacturing of non-invasive sensor, end (3) list of publications resulting from this project.

  17. Classroom Communication and Instructional Processes: Advances through Meta-Analysis

    ERIC Educational Resources Information Center

    Gayle, Barbara Mae, Ed.; Preiss, Raymond W., Ed.; Burrell, Nancy, Ed.; Allen, Mike, Ed.

    2006-01-01

    This volume offers a systematic review of the literature on communication education and instruction. Making meta-analysis findings accessible and relevant, the editors of this volume approach the topic from the perspective that meta-analysis serves as a useful tool for summarizing experiments and for determining how and why specific teaching and…

  18. Analysis of a spatially dispersive displacement sensor utilizing an AlGaInP chip.

    PubMed

    Horng, Ji-Bin; Liao, Jay; Tsai, Yao-Jun; Huang, Yen-Chen; Hu, Chieh; Tsau, Seth; Su, Yan-Kuin; Chou, Wei-Yang

    2007-08-20

    We present a demonstration and analysis of an industrialized design of a spatially dispersive displacement sensor, which is composed of an AlGaInP gain chip in visible range, optical assembly, and a spectrum analyzer. The sensor utilizes the spatial dispersion of focus from the optical assembly and wavelength spectrum's deviation induced by the displacement of the target. As a result, the sensor delivers a quick and simple way of measuring displacement. By adapting the magnification and resolution of the optical assembly, a displacement sensor with a middle measurement range, ~10 microm, was obtained. However, we should note that 25 nm resolution is limited by the bandwidth and temperature fluctuation of the gain chip.

  19. Fractal analysis and graph theory applied to the spatial and temporal variability of soil water content

    NASA Astrophysics Data System (ADS)

    Vieira, Sidney R.; Vidal Vázquez, Eva; Miranda, José G. V.; Paz Ferreiro, Jorge; Topp, George C.

    2010-05-01

    Spatial and temporal variability of soil moisture content has been frequently evaluated using statistical and geostatistical methods for several issues. For example, the statistical study of the temporal persistence or temporal stability in spatial patterns of soil moisture content has found interest to improve soil water monitoring strategies and to correct the average soil water content for missing data. Fractal analysis and graph theory are additional tools that can provide information and further insight to assess and to model indirect or hidden interactions in soil moisture content. In fractal analysis the fractal dimension (D) is an indicator of the pattern and extent of spatial and/or temporal variability. Large D values indicate the importance of short-range variation, while small D values reflect the importance of long-range variation when spatial and temporal data sets are analyzed. Moreover, for spatial and temporal variability, D can range from 1 to 2 for a profile and from 2 to 3 for a two dimensional network. Moreover, as the fractal dimension value increases the degree of roughness also increases. Graph theory tools take into account network structure by modelling pair wise relations between objects, which allow considering explicitly spatial-temporal connectivity of a given data set. The objective of this study was to use fractal analysis and graph theory to characterize the pattern of spatial and temporal variability of soil moisture content. The experimental field was located at Ottawa, Canada. Volumetric water content was monitored using Time Domain Reflectometry (TDR) during 34 dates at 164 locations per date. The depth of the TDR probes was 20 cm. The first and last measurements were 21 month apart and no data were taken in winter when the soil was covered by snow. The fractal dimension, D, was estimated from the slope of the regression line of log semivariogram versus distance for each of studied data sets. Using graph theory various

  20. Calibration and analysis of spatially resolved x-ray absorption spectra from a nonuniform plasma

    NASA Astrophysics Data System (ADS)

    Knapp, P. F.; Hansen, S. B.; Pikuz, S. A.; Shelkovenko, T. A.; Hammer, D. A.

    2012-07-01

    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 μm 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.

  1. [Spatial distribution pattern and fractal analysis of Larix chinensis populations in Qinling Mountain].

    PubMed

    Guo, Hua; Wang, Xiaoan; Xiao, Yaping

    2005-02-01

    In this paper, the fractal characters of Larix chinensis populations in Qinling Mountain were studied by contiguous grid quadrate sampling method and by boxing-counting dimension and information dimension. The results showed that the high boxing-counting dimension (1.8087) and information dimension (1.7931) reflected a higher spatial occupational degree of L. chinensis populations. Judged by the dispersal index and Morisita's pattern index, L. chinensis populations clumped at three different age stages (0-25, 25-50 and over 50 years). From Greig-Smiths' mean variance analysis, the figure of pattern scale showed that L. chinensis populations clumped in 128 m2 and 512 m2, and the different age groups clumped in different scales. The pattern intensities decreased with increasing age, and tended to reduce with increasing area when detected by Kershaw's PI index. The spatial pattern characters of L. chinensis populations may be their responses to environmental factors.

  2. 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.

  3. Advanced Technologies in Sialic Acid and Sialoglycoconjugate Analysis.

    PubMed

    Kitajima, Ken; Varki, Nissi; Sato, Chihiro

    2015-01-01

    Although the structural diversity of sialic acid (Sia) is rapidly expanding, understanding of its biological significance has lagged behind. Advanced technologies to detect and probe diverse structures of Sia are absolutely necessary not only to understand further biological significance but also to pursue medicinal and industrial applications. Here we describe analytical methods for detection of Sia that have recently been developed or improved, with a special focus on 9-O-acetylated N-acetylneuraminic acid (Neu5,9Ac), N-glycolylneuraminic acid (Neu5Gc), deaminoneuraminic acid (Kdn), O-sulfated Sia (SiaS), and di-, oligo-, and polysialic acid (diSia/oligoSia/polySia) in glycoproteins and glycolipids. Much more attention has been paid to these Sia and sialoglycoconjugates during the last decade, in terms of regulation of the immune system, neural development and function, tumorigenesis, and aging.

  4. Experimental and CFD Analysis of Advanced Convective Cooling Systems

    SciTech Connect

    Hassan, Yassin A; Ugaz, Victor M

    2012-06-27

    The objective of this project is to study the fundamental physical phenomena in the reactor cavity cooling system (RCCS) of very high-temperature reactors (VHTRs). One of the primary design objectives is to assure that RCCS acts as an ultimate heat sink capable of maintaining thermal integrity of the fuel, vessel, and equipment within the reactor cavity for the entire spectrum of postulated accident scenarios. Since construction of full-scale experimental test facilities to study these phenomena is impractical, it is logical to expect that computational fluid dynamics (CFD) simulations will play a key role in the RCCS design process. An important question then arises: To what extent are conventional CFD codes able to accurately capture the most important flow phenomena, and how can they be modified to improve their quantitative predictions? Researchers are working to tackle this problem in two ways. First, in the experimental phase, the research team plans to design and construct an innovative platform that will provide a standard test setting for validating CFD codes proposed for the RCCS design. This capability will significantly advance the state of knowledge in both liquid-cooled and gas-cooled (e.g., sodium fast reactor) reactor technology. This work will also extend flow measurements to micro-scale levels not obtainable in large-scale test facilities, thereby revealing previously undetectable phenomena that will complement the existing infrastructure. Second, in the computational phase of this work, numerical simulation of the flow and temperature profiles will be performed using advanced turbulence models to simulate the complex conditions of flows in critical zones of the cavity. These models will be validated and verified so that they can be implemented into commercially available CFD codes. Ultimately, the results of these validation studies can then be used to enable a more accurate design and safety evaluation of systems in actual nuclear power

  5. 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

  6. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

    SciTech Connect

    Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora; Kitzmiller, Joseph A.; Huang, Eric L.; Zink, Erika M.; Sontag, Ryan L.; Orton, Daniel J.; Moore, Ronald J.; Carson, James P.; Smith, Richard D.; Whitsett, Jeffrey A.; Corley, Richard A.; Ambalavanan, Namasivayam; Ansong, Charles

    2016-12-22

    Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow that with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and

  7. 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.

  8. Scanning photoelectron microscope for nanoscale three-dimensional spatial-resolved electron spectroscopy for chemical analysis

    NASA Astrophysics Data System (ADS)

    Horiba, K.; Nakamura, Y.; Nagamura, N.; Toyoda, S.; Kumigashira, H.; Oshima, M.; Amemiya, K.; Senba, Y.; Ohashi, H.

    2011-11-01

    In order to achieve nondestructive observation of the three-dimensional spatially resolved electronic structure of solids, we have developed a scanning photoelectron microscope system with the capability of depth profiling in electron spectroscopy for chemical analysis (ESCA). We call this system 3D nano-ESCA. For focusing the x-ray, a Fresnel zone plate with a diameter of 200 μm and an outermost zone width of 35 nm is used. In order to obtain the angular dependence of the photoelectron spectra for the depth-profile analysis without rotating the sample, we adopted a modified VG Scienta R3000 analyzer with an acceptance angle of 60° as a high-resolution angle-resolved electron spectrometer. The system has been installed at the University-of-Tokyo Materials Science Outstation beamline, BL07LSU, at SPring-8. From the results of the line-scan profiles of the poly-Si/high-k gate patterns, we achieved a total spatial resolution better than 70 nm. The capability of our system for pinpoint depth-profile analysis and high-resolution chemical state analysis is demonstrated.

  9. Scanning photoelectron microscope for nanoscale three-dimensional spatial-resolved electron spectroscopy for chemical analysis

    SciTech Connect

    Horiba, K.; Oshima, M.; Nakamura, Y.; Nagamura, N.; Toyoda, S.; Kumigashira, H.; Amemiya, K.; Senba, Y.; Ohashi, H.

    2011-11-15

    In order to achieve nondestructive observation of the three-dimensional spatially resolved electronic structure of solids, we have developed a scanning photoelectron microscope system with the capability of depth profiling in electron spectroscopy for chemical analysis (ESCA). We call this system 3D nano-ESCA. For focusing the x-ray, a Fresnel zone plate with a diameter of 200 {mu}m and an outermost zone width of 35 nm is used. In order to obtain the angular dependence of the photoelectron spectra for the depth-profile analysis without rotating the sample, we adopted a modified VG Scienta R3000 analyzer with an acceptance angle of 60 deg. as a high-resolution angle-resolved electron spectrometer. The system has been installed at the University-of-Tokyo Materials Science Outstation beamline, BL07LSU, at SPring-8. From the results of the line-scan profiles of the poly-Si/high-k gate patterns, we achieved a total spatial resolution better than 70 nm. The capability of our system for pinpoint depth-profile analysis and high-resolution chemical state analysis is demonstrated.

  10. 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).

  11. 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

  12. 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

  13. Web-based spatial analysis with the ILWIS open source GIS software and satellite images from GEONETCast

    NASA Astrophysics Data System (ADS)

    Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.

    2009-12-01

    This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the

  14. 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

  15. A common spatial factor analysis model for measured neighborhood-level characteristics: The Multi-Ethnic Study of Atherosclerosis.

    PubMed

    Nethery, Rachel C; Warren, Joshua L; Herring, Amy H; Moore, Kari A B; Evenson, Kelly R; Diez-Roux, Ana V

    2015-11-01

    The purpose of this study was to reduce the dimensionality of a set of neighborhood-level variables collected on participants in the Multi-Ethnic Study of Atherosclerosis (MESA) while appropriately accounting for the spatial structure of the data. A common spatial factor analysis model in the Bayesian setting was utilized in order to properly characterize dependencies in the data. Results suggest that use of the spatial factor model can result in more precise estimation of factor scores, improved insight into the spatial patterns in the data, and the ability to more accurately assess associations between the neighborhood environment and health outcomes.

  16. A Common Spatial Factor Analysis Model for Measured Neighborhood-Level Characteristics: The Multi-Ethnic Study of Atherosclerosis

    PubMed Central

    Nethery, Rachel C.; Warren, Joshua L.; Herring, Amy H.; Moore, Kari A.B.; Evenson, Kelly R.; Diez-Roux, Ana V.

    2015-01-01

    The purpose of this study was to reduce the dimensionality of a set of neighborhood-level variables collected on participants in the Multi-Ethnic Study of Atherosclerosis (MESA) while appropriately accounting for the spatial structure of the data. A common spatial factor analysis model in the Bayesian setting was utilized in order to properly characterize dependencies in the data. Results suggest that use of the spatial factor model can result in more precise estimation of factor scores, improved insight into the spatial patterns in the data, and the ability to more accurately assess associations between the neighborhood environment and health outcomes. PMID:26372887

  17. Advancing school-based interventions through economic analysis.

    PubMed

    Olsson, Tina M; Ferrer-Wreder, Laura; Eninger, Lilianne

    2014-01-01

    Commentators interested in school-based prevention programs point to the importance of economic issues for the future of prevention efforts. Many of the processes and aims of prevention science are dependent upon prevention resources. Although economic analysis is an essential tool for assessing resource use, the attention given economic analysis within school-based prevention remains cursory. Largely, economic analyses of school-based prevention efforts are undertaken as secondary research. This limits these efforts to data that have been collected previously as part of epidemiological and outcomes research. Therefore, economic analyses suffer from gaps in the knowledge generated by these studies. This chapter addresses the importance of economic analysis for the future of school-based substance abuse prevention programs and highlights the role of prevention research in the development of knowledge that can be used for economic analysis.

  18. 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

  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 d