WorldWideScience

Sample records for spatial analysis techniques

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  3. Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

    Science.gov (United States)

    Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

    2018-02-01

    This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

  4. Progress in spatial analysis methods and applications

    CERN Document Server

    Páez, Antonio; Buliung, Ron N; Dall'erba, Sandy

    2010-01-01

    This book brings together developments in spatial analysis techniques, including spatial statistics, econometrics, and spatial visualization, and applications to fields such as regional studies, transportation and land use, population and health.

  5. Spatial analysis statistics, visualization, and computational methods

    CERN Document Server

    Oyana, Tonny J

    2015-01-01

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

  6. Measurement of spatial correlation functions using image processing techniques

    International Nuclear Information System (INIS)

    Berryman, J.G.

    1985-01-01

    A procedure for using digital image processing techniques to measure the spatial correlation functions of composite heterogeneous materials is presented. Methods for eliminating undesirable biases and warping in digitized photographs are discussed. Fourier transform methods and array processor techniques for calculating the spatial correlation functions are treated. By introducing a minimal set of lattice-commensurate triangles, a method of sorting and storing the values of three-point correlation functions in a compact one-dimensional array is developed. Examples are presented at each stage of the analysis using synthetic photographs of cross sections of a model random material (the penetrable sphere model) for which the analytical form of the spatial correlations functions is known. Although results depend somewhat on magnification and on relative volume fraction, it is found that photographs digitized with 512 x 512 pixels generally have sufficiently good statistics for most practical purposes. To illustrate the use of the correlation functions, bounds on conductivity for the penetrable sphere model are calculated with a general numerical scheme developed for treating the singular three-dimensional integrals which must be evaluated

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

    Science.gov (United States)

    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.

  8. Global sensitivity analysis for models with spatially dependent outputs

    International Nuclear Information System (INIS)

    Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

    2011-01-01

    The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

  9. Water quality, Multivariate statistical techniques, submarine out fall, spatial variation, temporal variation

    International Nuclear Information System (INIS)

    Garcia, Francisco; Palacio, Carlos; Garcia, Uriel

    2012-01-01

    Multivariate statistical techniques were used to investigate the temporal and spatial variations of water quality at the Santa Marta coastal area where a submarine out fall that discharges 1 m3/s of domestic wastewater is located. Two-way analysis of variance (ANOVA), cluster and principal component analysis and Krigging interpolation were considered for this report. Temporal variation showed two heterogeneous periods. From December to April, and July, where the concentration of the water quality parameters is higher; the rest of the year (May, June, August-November) were significantly lower. The spatial variation reported two areas where the water quality is different, this difference is related to the proximity to the submarine out fall discharge.

  10. BATMAN: Bayesian Technique for Multi-image Analysis

    Science.gov (United States)

    Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

    2017-04-01

    This paper describes the Bayesian Technique for Multi-image Analysis (BATMAN), a novel image-segmentation technique based on Bayesian statistics that characterizes any astronomical data set containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (I.e. identical signal within the errors). We illustrate its operation and performance with a set of test cases including both synthetic and real integral-field spectroscopic data. The output segmentations adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. The quality of the recovered signal represents an improvement with respect to the input, especially in regions with low signal-to-noise ratio. However, the algorithm may be sensitive to small-scale random fluctuations, and its performance in presence of spatial gradients is limited. Due to these effects, errors may be underestimated by as much as a factor of 2. Our analysis reveals that the algorithm prioritizes conservation of all the statistically significant information over noise reduction, and that the precise choice of the input data has a crucial impact on the results. Hence, the philosophy of BaTMAn is not to be used as a 'black box' to improve the signal-to-noise ratio, but as a new approach to characterize spatially resolved data prior to its analysis. The source code is publicly available at http://astro.ft.uam.es/SELGIFS/BaTMAn.

  11. Spatial and Angular Moment Analysis of Continuous and Discretized Transport Problems

    International Nuclear Information System (INIS)

    Brantley, Patrick S.; Larsen, Edward W.

    2000-01-01

    A new theoretical tool for analyzing continuous and discretized transport equations is presented. This technique is based on a spatial and angular moment analysis of the analytic transport equation, which yields exact expressions for the 'center of mass' and 'squared radius of gyration' of the particle distribution. Essentially the same moment analysis is applied to discretized particle transport problems to determine numerical expressions for the center of mass and squared radius of gyration. Because this technique makes no assumption about the optical thickness of the spatial cells or about the amount of absorption in the system, it is applicable to problems that cannot be analyzed by a truncation analysis or an asymptotic diffusion limit analysis. The spatial differencing schemes examined (weighted- diamond, lumped linear discontinuous, and multiple balance) yield a numerically consistent expression for computing the squared radius of gyration plus an error term that depends on the mesh spacing, quadrature constants, and material properties of the system. The numerical results presented suggest that the relative accuracy of spatial differencing schemes for different types of problems can be assessed by comparing the magnitudes of these error terms

  12. Visualization techniques for spatial probability density function data

    Directory of Open Access Journals (Sweden)

    Udeepta D Bordoloi

    2006-01-01

    Full Text Available Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data. The clustering methods are used on two datasets, and the results are discussed with the help of visualization techniques designed for the spatial probability data.

  13. Spatial Analysis Along Networks Statistical and Computational Methods

    CERN Document Server

    Okabe, Atsuyuki

    2012-01-01

    In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process

  14. Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

    Science.gov (United States)

    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.

  15. Spatially resolved δ13C analysis using laser ablation isotope ratio mass spectrometry

    Science.gov (United States)

    Moran, J.; Riha, K. M.; Nims, M. K.; Linley, T. J.; Hess, N. J.; Nico, P. S.

    2014-12-01

    Inherent geochemical, organic matter, and microbial heterogeneity over small spatial scales can complicate studies of carbon dynamics through soils. Stable isotope analysis has a strong history of helping track substrate turnover, delineate rhizosphere activity zones, and identifying transitions in vegetation cover, but most traditional isotope approaches are limited in spatial resolution by a combination of physical separation techniques (manual dissection) and IRMS instrument sensitivity. We coupled laser ablation sampling with isotope measurement via IRMS to enable spatially resolved analysis over solid surfaces. Once a targeted sample region is ablated the resulting particulates are entrained in a helium carrier gas and passed through a combustion reactor where carbon is converted to CO2. Cyrotrapping of the resulting CO2 enables a reduction in carrier gas flow which improves overall measurement sensitivity versus traditional, high flow sample introduction. Currently we are performing sample analysis at 50 μm resolution, require 65 ng C per analysis, and achieve measurement precision consistent with other continuous flow techniques. We will discuss applications of the laser ablation IRMS (LA-IRMS) system to microbial communities and fish ecology studies to demonstrate the merits of this technique and how similar analytical approaches can be transitioned to soil systems. Preliminary efforts at analyzing soil samples will be used to highlight strengths and limitations of the LA-IRMS approach, paying particular attention to sample preparation requirements, spatial resolution, sample analysis time, and the types of questions most conducive to analysis via LA-IRMS.

  16. Advanced spatial metrics analysis in cellular automata land use and cover change modeling

    International Nuclear Information System (INIS)

    Zamyatin, Alexander; Cabral, Pedro

    2011-01-01

    This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.

  17. Evaluating spatial- and temporal-oriented multi-dimensional visualization techniques

    Directory of Open Access Journals (Sweden)

    Chong Ho Yu

    2003-07-01

    Full Text Available Visualization tools are said to be helpful for researchers to unveil hidden patterns and..relationships among variables, and also for teachers to present abstract statistical concepts and..complicated data structures in a concrete manner. However, higher-dimension visualization..techniques can be confusing and even misleading, especially when human-instrument interface..and cognitive issues are under-applied. In this article, the efficacy of function-based, datadriven,..spatial-oriented, and temporal-oriented visualization techniques are discussed based..upon extensive review. Readers can find practical implications for both research and..instructional practices. For research purposes, the spatial-based graphs, such as Trellis displays..in S-Plus, are preferable over the temporal-based displays, such as the 3D animated plot in..SAS/Insight. For teaching purposes, the temporal-based displays, such as the 3D animation plot..in Maple, seem to have advantages over the spatial-based graphs, such as the 3D triangular..coordinate plot in SyStat.

  18. Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging.

    Science.gov (United States)

    Khairalseed, Mawia; Xiong, Fangyuan; Kim, Jung-Whan; Mattrey, Robert F; Parker, Kevin J; Hoyt, Kenneth

    2018-01-01

    H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

  19. Perspectives on spatial data analysis

    CERN Document Server

    Rey, Sergio

    2010-01-01

    This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading experts in the field. Four main aspects are highlighted, dealing with spatial analysis, pattern analysis, local statistics as well as illustrative empirical applications. Researchers and students will gain an appreciation of Getis' methodological contributions to spatial analysis and the broad impact of the methods he has helped pioneer on an impressively broad array of disciplines including spatial epidemiology, demography, economics, and ecology. The volume is a compilation of high impact original contributions, as evidenced by citations, and the latest thinking on the field by leading scholars. This makes the book ideal for advanced seminars and courses in spatial analysis as well as a key resource for researchers seeking a comprehensive overview of recent advances and future directions in the field.

  20. GeoXp : An R Package for Exploratory Spatial Data Analysis

    Directory of Open Access Journals (Sweden)

    Thibault Laurent

    2012-04-01

    Full Text Available We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analysis. We use a data set concerning public schools of the French MidiPyrenees region to illustrate the use of these exploratory techniques based on the coupling between a statistical graph and a map. Besides elementary plots like boxplots,histograms or simple scatterplots, GeoXp also couples maps with Moran scatterplots, variogram clouds, Lorenz curves and other graphical tools. In order to make the most of the multidimensionality of the data, GeoXp includes dimension reduction techniques such as principal components analysis and cluster analysis whose results are also linked to the map.

  1. MASTR: A Technique for Mosaic Mutant Analysis with Spatial and Temporal Control of Recombination Using Conditional Floxed Alleles in Mice

    Directory of Open Access Journals (Sweden)

    Zhimin Lao

    2012-08-01

    Full Text Available Mosaic mutant analysis, the study of cellular defects in scattered mutant cells in a wild-type environment, is a powerful approach for identifying critical functions of genes and has been applied extensively to invertebrate model organisms. A highly versatile technique has been developed in mouse: MASTR (mosaic mutant analysis with spatial and temporal control of recombination, which utilizes the increasing number of floxed alleles and simultaneously combines conditional gene mutagenesis and cell marking for fate analysis. A targeted allele (R26MASTR was engineered; the allele expresses a GFPcre fusion protein following FLP-mediated recombination, which serves the dual function of deleting floxed alleles and marking mutant cells with GFP. Within 24 hr of tamoxifen administration to R26MASTR mice carrying an inducible FlpoER transgene and a floxed allele, nearly all GFP-expressing cells have a mutant allele. The fate of single cells lacking FGF8 or SHH signaling in the developing hindbrain was analyzed using MASTR, and it was revealed that there is only a short time window when neural progenitors require FGFR1 for viability and that granule cell precursors differentiate rapidly when SMO is lost. MASTR is a powerful tool that provides cell-type-specific (spatial and temporal marking of mosaic mutant cells and is broadly applicable to developmental, cancer, and adult stem cell studies.

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

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2009-08-01

    Full Text Available 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.

  3. A GIS-based disaggregate spatial watershed analysis using RADAR data

    International Nuclear Information System (INIS)

    Al-Hamdan, M.

    2002-01-01

    Hydrology is the study of water in all its forms, origins, and destinations on the earth.This paper develops a novel modeling technique using a geographic information system (GIS) to facilitate watershed hydrological routing using RADAR data. The RADAR rainfall data, segmented to 4 km by 4 km blocks, divides the watershed into several sub basins which are modeled independently. A case study for the GIS-based disaggregate spatial watershed analysis using RADAR data is provided for South Fork Cowikee Creek near Batesville, Alabama. All the data necessary to complete the analysis is maintained in the ArcView GIS software. This paper concludes that the GIS-Based disaggregate spatial watershed analysis using RADAR data is a viable method to calculate hydrological routing for large watersheds. (author)

  4. Professional analysis in spatial planning

    Directory of Open Access Journals (Sweden)

    Andrej Černe

    2005-12-01

    Full Text Available Spatial analysis contributes to accomplishment of the three basic aims of spatial planning: it is basic element for setting spatial policies, concepts and strategies, gives basic information to inhabitants, land owners, investors, planners and helps in performing spatial policies, strategies, plans, programmes and projects. Analysis in planning are generally devoted to: understand current circumstances and emerging conditions within planning decisions; determine priorities of open questions and their solutions; formulate general principles for further development.

  5. Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA: Spatial Analysis Framework

    Directory of Open Access Journals (Sweden)

    Sina Tehranchi

    2017-03-01

    Full Text Available This research presents a Geographic Information Systems (GIS and spatial analysis approach based on the global spatial autocorrelation of road traffic injuries for identifying spatial patterns. A locational spatial autocorrelation was also used for identifying traffic injury at spatial level. Data for this research study were acquired from Canadian Institute for Health Information (CIHI based on 2004 and 2011. Moran’s I statistics were used to examine spatial patterns of road traffic injuries in the Greater Toronto Area (GTA. An assessment of Getis-Ord Gi* statistic was followed as to identify hot spots and cold spots within the study area. The results revealed that Peel and Durham have the highest collision rate for other motor vehicle with motor vehicle. Geographic weighted regression (GWR technique was conducted to test the relationships between the dependent variable, number of road traffic injury incidents and independent variables such as number of seniors, low education, unemployed, vulnerable groups, people smoking and drinking, urban density and average median income. The result of this model suggested that number of seniors and low education have a very strong correlation with the number of road traffic injury incidents.

  6. Where do overweight women in Ghana live? Answers from exploratory spatial data analysis

    Directory of Open Access Journals (Sweden)

    Fidelia A.A. Dake

    2012-03-01

    Full Text Available 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.

  7. ANÁLISE ESPACIAL DE DADOS GEOGRÁFICOS: A UTILIZAÇÃO DA EXPLORATORY SPATIAL DATA ANALYSIS - ESDA PARA IDENTIFICAÇÃO DE ÁREAS CRÍTICAS DE ACIDENTES DE TRÂNSITO NO MUNICÍPIO DE SÃO CARLOS (SP / Spatial analysis of Geographic Data: the use of the Exploratory Spatial Data Analysis - ESDA for identification of critical areas of traffic accidents in the São Carlos (SP

    Directory of Open Access Journals (Sweden)

    Msc. Luciano dos Santos

    2006-12-01

    Full Text Available The Spatial Analysis is one of the some forms of if understanding as some spatial events arerelationships. Currently, this technique to see being incorporated for diverse areas of the knowledgesuch as, the health areas, has carried and transit. This work has as objective to demonstrate theapplication of the Exploratory Spatial Data Analysis - ESDA, for the identification of criticalareas of traffic accidents in cities of average transport, having as study area the São Carlos - SP -Brazil. In this study it was possible to demonstrate to the viability of use of this technique, since itwas possible to incorporate new parameters of analysis of the accidents being provided new waysfor identification of problematic areas, facilitating its analysis.

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

    Directory of Open Access Journals (Sweden)

    Yang Hong

    2006-04-01

    Full Text Available Abstract 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 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.

  9. Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

    Science.gov (United States)

    Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

    2013-09-01

    The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

  10. Spatial data analysis and the use of maps in scientific health articles.

    Science.gov (United States)

    Nucci, Luciana Bertoldi; Souccar, Patrick Theodore; Castilho, Silvia Diez

    2016-07-01

    Despite the growing number of studies with a characteristic element of spatial analysis, the application of the techniques is not always clear and its continuity in epidemiological studies requires careful evaluation. To verify the spread and use of those processes in national and international scientific papers. An assessment was made of periodicals according to the impact index. Among 8,281 journals surveyed, four national and four international were selected, of which 1,274 articles were analyzed regarding the presence or absence of spatial analysis techniques. Just over 10% of articles published in 2011 in high impact journals, both national and international, showed some element of geographical location. Although these percentages vary greatly from one journal to another, denoting different publication profiles, we consider this percentage as an indication that location variables have become an important factor in studies of health.

  11. Spatial analysis and planning under imprecision

    CERN Document Server

    Leung, Y

    1988-01-01

    The book deals with complexity, imprecision, human valuation, and uncertainty in spatial analysis and planning, providing a systematic exposure of a new philosophical and theoretical foundation for spatial analysis and planning under imprecision. Regional concepts and regionalization, spatial preference-utility-choice structures, spatial optimization with single and multiple objectives, dynamic spatial systems and their controls are analyzed in sequence.The analytical framework is based on fuzzy set theory. Basic concepts of fuzzy set theory are first discussed. Many numerical examples and emp

  12. Analysis of thrips distribution: application of spatial statistics and Kriging

    Science.gov (United States)

    John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

    1991-01-01

    Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

  13. Residual analysis for spatial point processes

    DEFF Research Database (Denmark)

    Baddeley, A.; Turner, R.; Møller, Jesper

    We define residuals for point process models fitted to spatial point pattern data, and propose diagnostic plots based on these residuals. The techniques apply to any Gibbs point process model, which may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Ou...... or covariate effects. Q-Q plots of the residuals are effective in diagnosing interpoint interaction. Some existing ad hoc statistics of point patterns (quadrat counts, scan statistic, kernel smoothed intensity, Berman's diagnostic) are recovered as special cases....

  14. Spatial analysis methods and land-use planning models for rural areas

    Directory of Open Access Journals (Sweden)

    Patrizia Tassinari

    2009-10-01

    Full Text Available The work presents a brief report of the main results of a study carried out by the Spatial Engineering Division of the Department of Agricultural Economics and Engineering of the University of Bologna, within a broader PRIN 2005 research project concerning landscape and economic analysis, planning and programming. In particular, the study focuses on the design of spatial analysis methods aimed at building knowledge frameworks of the various natural and anthropic resources of rural areas. The goal is to increase the level of spatial and information detail of common databases, thus allowing higher accuracy and effectiveness of the analyses needed to achieve the goals of new generation spatial and agriculture planning. Specific in-depth analyses allowed to define techniques useful in order to reduce the increase in survey costs. Moreover, the work reports the main results regarding a multicriteria model for the analysis of the countryside defined by the research. Such model is aimed to assess the various agricultural, environmental and landscape features, vocations, expressions and attitudes, and support the definition and implementation of specific and targeted planning and programming policies.

  15. Spatial and temporal single-cell volume estimation by a fluorescence imaging technique with application to astrocytes in primary culture

    Science.gov (United States)

    Khatibi, Siamak; Allansson, Louise; Gustavsson, Tomas; Blomstrand, Fredrik; Hansson, Elisabeth; Olsson, Torsten

    1999-05-01

    Cell volume changes are often associated with important physiological and pathological processes in the cell. These changes may be the means by which the cell interacts with its surrounding. Astroglial cells change their volume and shape under several circumstances that affect the central nervous system. Following an incidence of brain damage, such as a stroke or a traumatic brain injury, one of the first events seen is swelling of the astroglial cells. In order to study this and other similar phenomena, it is desirable to develop technical instrumentation and analysis methods capable of detecting and characterizing dynamic cell shape changes in a quantitative and robust way. We have developed a technique to monitor and to quantify the spatial and temporal volume changes in a single cell in primary culture. The technique is based on two- and three-dimensional fluorescence imaging. The temporal information is obtained from a sequence of microscope images, which are analyzed in real time. The spatial data is collected in a sequence of images from the microscope, which is automatically focused up and down through the specimen. The analysis of spatial data is performed off-line and consists of photobleaching compensation, focus restoration, filtering, segmentation and spatial volume estimation.

  16. Recent developments in spatial analysis spatial statistics, behavioural modelling, and computational intelligence

    CERN Document Server

    Getis, Arthur

    1997-01-01

    In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.

  17. Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search.

    Science.gov (United States)

    Mena, Carlos; Sepúlveda, Cesar; Fuentes, Eduardo; Ormazábal, Yony; Palomo, Iván

    2018-05-07

    Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (e.g., rural, deprived neighbourhoods, etc.), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.

  18. Influence of Topographic and Hydrographic Factors on the Spatial Distribution of Leptospirosis Disease in São Paulo County, Brazil: An Approach Using Geospatial Techniques and GIS Analysis

    Science.gov (United States)

    Ferreira, M. C.; Ferreira, M. F. M.

    2016-06-01

    Leptospirosis is a zoonosis caused by Leptospira genus bacteria. Rodents, especially Rattus norvegicus, are the most frequent hosts of this microorganism in the cities. The human transmission occurs by contact with urine, blood or tissues of the rodent and contacting water or mud contaminated by rodent urine. Spatial patterns of concentration of leptospirosis are related to the multiple environmental and socioeconomic factors, like housing near flooding areas, domestic garbage disposal sites and high-density of peoples living in slums located near river channels. We used geospatial techniques and geographical information system (GIS) to analysing spatial relationship between the distribution of leptospirosis cases and distance from rivers, river density in the census sector and terrain slope factors, in Sao Paulo County, Brazil. To test this methodology we used a sample of 183 geocoded leptospirosis cases confirmed in 2007, ASTER GDEM2 data, hydrography and census sectors shapefiles. Our results showed that GIS and geospatial analysis techniques improved the mapping of the disease and permitted identify the spatial pattern of association between location of cases and spatial distribution of the environmental variables analyzed. This study showed also that leptospirosis cases might be more related to the census sectors located on higher river density areas and households situated at shorter distances from rivers. In the other hand, it was not possible to assert that slope terrain contributes significantly to the location of leptospirosis cases.

  19. Analysis of syntactic and semantic features for fine-grained event-spatial understanding in outbreak news reports

    Directory of Open Access Journals (Sweden)

    Chanlekha Hutchatai

    2010-03-01

    Full Text Available Abstract Background Previous studies have suggested that epidemiological reasoning needs a fine-grained modelling of events, especially their spatial and temporal attributes. While the temporal analysis of events has been intensively studied, far less attention has been paid to their spatial analysis. This article aims at filling the gap concerning automatic event-spatial attribute analysis in order to support health surveillance and epidemiological reasoning. Results In this work, we propose a methodology that provides a detailed analysis on each event reported in news articles to recover the most specific locations where it occurs. Various features for recognizing spatial attributes of the events were studied and incorporated into the models which were trained by several machine learning techniques. The best performance for spatial attribute recognition is very promising; 85.9% F-score (86.75% precision/85.1% recall. Conclusions We extended our work on event-spatial attribute recognition by focusing on machine learning techniques, which are CRF, SVM, and Decision tree. Our approach avoided the costly development of an external knowledge base by employing the feature sources that can be acquired locally from the analyzed document. The results showed that the CRF model performed the best. Our study indicated that the nearest location and previous event location are the most important features for the CRF and SVM model, while the location extracted from the verb's subject is the most important to the Decision tree model.

  20. Multiscale analysis of damage using dual and primal domain decomposition techniques

    NARCIS (Netherlands)

    Lloberas-Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.

    2014-01-01

    In this contribution, dual and primal domain decomposition techniques are studied for the multiscale analysis of failure in quasi-brittle materials. The multiscale strategy essentially consists in decomposing the structure into a number of nonoverlapping domains and considering a refined spatial

  1. Possibilities of LA-ICP-MS technique for the spatial elemental analysis of the recent fish scales: Line scan vs. depth profiling

    International Nuclear Information System (INIS)

    Hola, Marketa; Kalvoda, Jiri; Novakova, Hana; Skoda, Radek; Kanicky, Viktor

    2011-01-01

    LA-ICP-MS and solution based ICP-MS in combination with electron microprobe are presented as a method for the determination of the elemental spatial distribution in fish scales which represent an example of a heterogeneous layered bone structure. Two different LA-ICP-MS techniques were tested on recent common carp (Cyprinus carpio) scales: (a)A line scan through the whole fish scale perpendicular to the growth rings. The ablation crater of 55 μm width and 50 μm depth allowed analysis of the elemental distribution in the external layer. Suitable ablation conditions providing a deeper ablation crater gave average values from the external HAP layer and the collagen basal plate. (b)Depth profiling using spot analysis was tested in fish scales for the first time. Spot analysis allows information to be obtained about the depth profile of the elements at the selected position on the sample. The combination of all mentioned laser ablation techniques provides complete information about the elemental distribution in the fish scale samples. The results were compared with the solution based ICP-MS and EMP analyses. The fact that the results of depth profiling are in a good agreement both with EMP and PIXE results and, with the assumed ways of incorporation of the studied elements in the HAP structure, suggests a very good potential for this method.

  2. Possibilities of LA-ICP-MS technique for the spatial elemental analysis of the recent fish scales: Line scan vs. depth profiling

    Energy Technology Data Exchange (ETDEWEB)

    Hola, Marketa [Department of Chemistry, Masaryk University of Brno, Kamenice 5, 625 00 Brno (Czech Republic); Kalvoda, Jiri, E-mail: jkalvoda@centrum.cz [Department of Geological Sciences, Masaryk University of Brno, Kotlarska 2, 611 37 Brno (Czech Republic); Novakova, Hana [Department of Chemistry, Masaryk University of Brno, Kamenice 5, 625 00 Brno (Czech Republic); Skoda, Radek [Department of Geological Sciences, Masaryk University of Brno, Kotlarska 2, 611 37 Brno (Czech Republic); Kanicky, Viktor [Department of Chemistry, Masaryk University of Brno, Kamenice 5, 625 00 Brno (Czech Republic)

    2011-01-01

    LA-ICP-MS and solution based ICP-MS in combination with electron microprobe are presented as a method for the determination of the elemental spatial distribution in fish scales which represent an example of a heterogeneous layered bone structure. Two different LA-ICP-MS techniques were tested on recent common carp (Cyprinus carpio) scales: (a)A line scan through the whole fish scale perpendicular to the growth rings. The ablation crater of 55 {mu}m width and 50 {mu}m depth allowed analysis of the elemental distribution in the external layer. Suitable ablation conditions providing a deeper ablation crater gave average values from the external HAP layer and the collagen basal plate. (b)Depth profiling using spot analysis was tested in fish scales for the first time. Spot analysis allows information to be obtained about the depth profile of the elements at the selected position on the sample. The combination of all mentioned laser ablation techniques provides complete information about the elemental distribution in the fish scale samples. The results were compared with the solution based ICP-MS and EMP analyses. The fact that the results of depth profiling are in a good agreement both with EMP and PIXE results and, with the assumed ways of incorporation of the studied elements in the HAP structure, suggests a very good potential for this method.

  3. A new methodology of spatial cross-correlation analysis.

    Science.gov (United States)

    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.

  4. Spatial assessment and source identification of heavy metals pollution in surface water using several chemometric techniques.

    Science.gov (United States)

    Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Zain, Sharifuddin Md; Habir, Nur Liyana Abdul; Retnam, Ananthy; Kamaruddin, Mohd Khairul Amri; Umar, Roslan; Azid, Azman

    2016-05-15

    This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time. The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Components of spatial information management in wildlife ecology: Software for statistical and modeling analysis [Chapter 14

    Science.gov (United States)

    Hawthorne L. Beyer; Jeff Jenness; Samuel A. Cushman

    2010-01-01

    Spatial information systems (SIS) is a term that describes a wide diversity of concepts, techniques, and technologies related to the capture, management, display and analysis of spatial information. It encompasses technologies such as geographic information systems (GIS), global positioning systems (GPS), remote sensing, and relational database management systems (...

  6. Simulation techniques for spatially evolving instabilities in compressible flow over a flat plate

    NARCIS (Netherlands)

    Wasistho, B.; Geurts, Bernardus J.; Kuerten, Johannes G.M.

    1997-01-01

    In this paper we present numerical techniques suitable for a direct numerical simulation in the spatial setting. We demonstrate the application to the simulation of compressible flat plate flow instabilities. We compare second and fourth order accurate spatial discretization schemes in combination

  7. A New Methodology of Spatial Cross-Correlation Analysis

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

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

  8. Spatial Game Analytics and Visualization

    DEFF Research Database (Denmark)

    Drachen, Anders; Schubert, Matthias

    2013-01-01

    , techniques for spatial analysis had their share in these developments. However, the methods for analyzing and visualizing spatial and spatio-temporal patterns in player behavior being used by the game industry are not as diverse as the range of techniques utilized in game research, leaving room...... for a continuing development. This paper presents a review of current work on spatial and spatio-temporal game analytics across industry and research, describing and defining the key terminology, outlining current techniques and their application. We summarize the current problems and challenges in the field......The recently emerged field of game analytics and the development and adaptation of business intelligence techniques to support game design and development has given data-driven techniques a direct role in game development. Given that all digital games contain some sort of spatial operation...

  9. A comparison of spatial rainfall estimation techniques: A case study ...

    African Journals Online (AJOL)

    Two geostatistical interpolation techniques (kriging and cokriging) were evaluated against inverse distance weighted (IDW) and global polynomial interpolation (GPI). Of the four spatial interpolators, kriging and cokriging produced results with the least root mean square error (RMSE). A digital elevation model (DEM) was ...

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

    Science.gov (United States)

    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.

  11. Spatial analysis on human brucellosis incidence in mainland China: 2004–2010

    Science.gov (United States)

    Zhang, Junhui; Yin, Fei; Zhang, Tao; Yang, Chao; Zhang, Xingyu; Feng, Zijian; Li, Xiaosong

    2014-01-01

    Objectives China has experienced a sharply increasing rate of human brucellosis in recent years. Effective spatial monitoring of human brucellosis incidence is very important for successful implementation of control and prevention programmes. The purpose of this paper is to apply exploratory spatial data analysis (ESDA) methods and the empirical Bayes (EB) smoothing technique to monitor county-level incidence rates for human brucellosis in mainland China from 2004 to 2010 by examining spatial patterns. Methods ESDA methods were used to characterise spatial patterns of EB smoothed incidence rates for human brucellosis based on county-level data obtained from the China Information System for Disease Control and Prevention (CISDCP) in mainland China from 2004 to 2010. Results EB smoothed incidence rates for human brucellosis were spatially dependent during 2004–2010. The local Moran test identified significantly high-risk clusters of human brucellosis (all p values brucellosis incidence. PMID:24713215

  12. Colour and shape analysis techniques for weed detection in cereal fields

    DEFF Research Database (Denmark)

    Pérez, A.J; López, F; Benlloch, J.V.

    2000-01-01

    . The proposed methods use colour information to discriminate between vegetation and background, whilst shape analysis techniques are applied to distinguish between crop and weeds. The determination of crop row position helps to reduce the number of objects to which shape analysis techniques are applied....... The performance of algorithms was assessed by comparing the results with a human classification, providing an acceptable success rate. The study has shown that despite the difficulties in accurately determining the number of seedlings (as in visual surveys), it is feasible to use image processing techniques......Information on weed distribution within the field is necessary to implement spatially variable herbicide application. This paper deals with the development of near-ground image capture and processing techniques in order to detect broad-leaved weeds in cereal crops under actual field conditions...

  13. Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method

    Science.gov (United States)

    Cheng, Haiying; Yan, Yumei; Duong, Timothy Q.

    2009-02-01

    Noninvasive monitoring of blood flow in retinal circulation will reveal the progression and treatment of ocular disorders, such as diabetic retinopathy, age-related macular degeneration and glaucoma. A non-invasive and direct BF measurement technique with high spatial-temporal resolution is needed for retinal imaging. Laser speckle imaging (LSI) is such a method. Currently, there are two analysis methods for LSI: spatial statistics LSI (SS-LSI) and temporal statistical LSI (TS-LSI). Comparing these two analysis methods, SS-LSI has higher signal to noise ratio (SNR) and TSLSI is less susceptible to artifacts from stationary speckle. We proposed a hybrid temporal and spatial analysis method (HTS-LSI) to measure the retinal blood flow. Gas challenge experiment was performed and images were analyzed by HTS-LSI. Results showed that HTS-LSI can not only remove the stationary speckle but also increase the SNR. Under 100% O2, retinal BF decreased by 20-30%. This was consistent with the results observed with laser Doppler technique. As retinal blood flow is a critical physiological parameter and its perturbation has been implicated in the early stages of many retinal diseases, HTS-LSI will be an efficient method in early detection of retina diseases.

  14. Visualization and Analysis of Wireless Sensor Network Data for Smart Civil Structure Applications Based On Spatial Correlation Technique

    Science.gov (United States)

    Chowdhry, Bhawani Shankar; White, Neil M.; Jeswani, Jai Kumar; Dayo, Khalil; Rathi, Manorma

    2009-07-01

    Disasters affecting infrastructure, such as the 2001 earthquakes in India, 2005 in Pakistan, 2008 in China and the 2004 tsunami in Asia, provide a common need for intelligent buildings and smart civil structures. Now, imagine massive reductions in time to get the infrastructure working again, realtime information on damage to buildings, massive reductions in cost and time to certify that structures are undamaged and can still be operated, reductions in the number of structures to be rebuilt (if they are known not to be damaged). Achieving these ideas would lead to huge, quantifiable, long-term savings to government and industry. Wireless sensor networks (WSNs) can be deployed in buildings to make any civil structure both smart and intelligent. WSNs have recently gained much attention in both public and research communities because they are expected to bring a new paradigm to the interaction between humans, environment, and machines. This paper presents the deployment of WSN nodes in the Top Quality Centralized Instrumentation Centre (TQCIC). We created an ad hoc networking application to collect real-time data sensed from the nodes that were randomly distributed throughout the building. If the sensors are relocated, then the application automatically reconfigures itself in the light of the new routing topology. WSNs are event-based systems that rely on the collective effort of several micro-sensor nodes, which are continuously observing a physical phenomenon. WSN applications require spatially dense sensor deployment in order to achieve satisfactory coverage. The degree of spatial correlation increases with the decreasing inter-node separation. Energy consumption is reduced dramatically by having only those sensor nodes with unique readings transmit their data. We report on an algorithm based on a spatial correlation technique that assures high QoS (in terms of SNR) of the network as well as proper utilization of energy, by suppressing redundant data transmission

  15. Land Use Changes Analysis for Kelantan Basin Using Spatial Matrix Technique “Patch Analyst” in Relation to Flood Disaster

    Directory of Open Access Journals (Sweden)

    Tuan Pah Rokiah Syed Hussain

    2011-09-01

    Full Text Available In the recent decade, there are many government efforts to develop rural area as a step to curb vast economic discrepancy status within community in the nation. This effort is in line with National Development Policy promoted by government shifting from New Economic Policy. Therefore, this study area also has impact done by development activities. The enormous economic developments have encourage growth in urbanization, tourism and recreation, public facilities, housing and so on. Furthermore, the area of cultivation land uses and foliages are becoming shrinking due to development growth, which is development needs to shift land use pattern hence denotes that human beings infuriate the environment to meet the life needs. In response to that, this research delves into the level of land use changes using the Geographic Information System (GIS and Spatial Analyst to determine the actual area or vicinity and what is the type of rigorous changes in land use. This issue can be seen all the way through the study outcome via spatial analysis technique adapted from Patch Density & Size Metrics (Mean Patch Size, Edge Metrics (Total Edge (TE, Edge Density (ED, Mean Perimeter-Area Ratio (Mpar and Shannons Diversity Index (SHDI. Results of the study show that, land use changes have occurred significantly in the study area for the period of 20 years, wher, all types of analysis verify that there is an increase in patch for every statistical test. The increase in patch is a picture of current land use changes, land use edge density and land use area in study area. Moreover, this study investigates the relationship between land use with rising flood disaster frequency and intensity variable which has always happened lately in Kelantan River Basin.

  16. SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

    Science.gov (United States)

    Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan

    2017-09-01

    With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

    Science.gov (United States)

    ,

    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.

  18. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  19. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  20. Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013.

    Directory of Open Access Journals (Sweden)

    Yan-Yan Chen

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

  1. A Spatial Analysis of Tourism Activity in Romania

    Directory of Open Access Journals (Sweden)

    Daniela Luminita Constantin

    2018-02-01

    Full Text Available Location is a key concept in tourism sector analysis, given the dependence of this activity on the natural, built, cultural and social characteristics of a certain territory. As a result, the tourist zoning is an important instrument for delimiting tourist areas in accordance with multiple criteria, so as to lay the foundations for finding the most suitable solutions of turning to good account the resources in this field. The modern approaches proposed in this paper use a series of analytical tools that combine GIS and spatial agglomeration analysis based techniques. They can be also employed in order to examine and explain the differences between tourist zones (and sub-zones in terms of economic and social results and thus to suggest realistic ways to improve the efficiency and effectiveness of tourist activities in various geographical areas. In the described context this paper proposes an interdisciplinary perspective (spatial statistics and Geographical Information Systems for analysing the tourism activity in Romania, mainly aiming to identify the agglomerations of companies acting in this industry and assess their performance and contribution to the economic development of the corresponding regions. It also intends to contribute to a better understanding of the way in which tourism related business activities develop, in order to enhance appropriate support networks. Territorial and spatial statistics, as well as GIS based analyses are applied, using data about all companies acting in tourism industry in Romania provided by the National Authority for Tourism as well as data from the Environmental Systems Research Institute (ESRI.

  2. Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

    Science.gov (United States)

    Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

    2018-01-01

    Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

  3. [Applications of spectral analysis technique to monitoring grasshoppers].

    Science.gov (United States)

    Lu, Hui; Han, Jian-guo; Zhang, Lu-da

    2008-12-01

    Grasshopper monitoring is of great significance in protecting environment and reducing economic loss. However, how to predict grasshoppers accurately and effectively is a difficult problem for a long time. In the present paper, the importance of forecasting grasshoppers and its habitat is expounded, and the development in monitoring grasshopper populations and the common arithmetic of spectral analysis technique are illustrated. Meanwhile, the traditional methods are compared with the spectral technology. Remote sensing has been applied in monitoring the living, growing and breeding habitats of grasshopper population, and can be used to develop a forecast model combined with GIS. The NDVI values can be analyzed throughout the remote sensing data and be used in grasshopper forecasting. Hyper-spectra remote sensing technique which can be used to monitor grasshoppers more exactly has advantages in measuring the damage degree and classifying damage areas of grasshoppers, so it can be adopted to monitor the spatial distribution dynamic of rangeland grasshopper population. Differentialsmoothing can be used to reflect the relations between the characteristic parameters of hyper-spectra and leaf area index (LAI), and indicate the intensity of grasshopper damage. The technology of near infrared reflectance spectroscopy has been employed in judging grasshopper species, examining species occurrences and monitoring hatching places by measuring humidity and nutrient of soil, and can be used to investigate and observe grasshoppers in sample research. According to this paper, it is concluded that the spectral analysis technique could be used as a quick and exact tool in monitoring and forecasting the infestation of grasshoppers, and will become an important means in such kind of research for their advantages in determining spatial orientation, information extracting and processing. With the rapid development of spectral analysis methodology, the goal of sustainable monitoring

  4. Diffusion MRI of the neonate brain: acquisition, processing and analysis techniques

    Energy Technology Data Exchange (ETDEWEB)

    Pannek, Kerstin [University of Queensland, Centre for Clinical Research, Brisbane (Australia); University of Queensland, School of Medicine, Brisbane (Australia); University of Queensland, Centre for Advanced Imaging, Brisbane (Australia); Guzzetta, Andrea [IRCCS Stella Maris, Department of Developmental Neuroscience, Calambrone Pisa (Italy); Colditz, Paul B. [University of Queensland, Centre for Clinical Research, Brisbane (Australia); University of Queensland, Perinatal Research Centre, Brisbane (Australia); Rose, Stephen E. [University of Queensland, Centre for Clinical Research, Brisbane (Australia); University of Queensland, Centre for Advanced Imaging, Brisbane (Australia); University of Queensland Centre for Clinical Research, Royal Brisbane and Women' s Hospital, Brisbane (Australia)

    2012-10-15

    Diffusion MRI (dMRI) is a popular noninvasive imaging modality for the investigation of the neonate brain. It enables the assessment of white matter integrity, and is particularly suited for studying white matter maturation in the preterm and term neonate brain. Diffusion tractography allows the delineation of white matter pathways and assessment of connectivity in vivo. In this review, we address the challenges of performing and analysing neonate dMRI. Of particular importance in dMRI analysis is adequate data preprocessing to reduce image distortions inherent to the acquisition technique, as well as artefacts caused by head movement. We present a summary of techniques that should be used in the preprocessing of neonate dMRI data, and demonstrate the effect of these important correction steps. Furthermore, we give an overview of available analysis techniques, ranging from voxel-based analysis of anisotropy metrics including tract-based spatial statistics (TBSS) to recently developed methods of statistical analysis addressing issues of resolving complex white matter architecture. We highlight the importance of resolving crossing fibres for tractography and outline several tractography-based techniques, including connectivity-based segmentation, the connectome and tractography mapping. These techniques provide powerful tools for the investigation of brain development and maturation. (orig.)

  5. Nitrogen Oxide Emission, Economic Growth and Urbanization in China: a Spatial Econometric Analysis

    Science.gov (United States)

    Zhou, Zhimin; Zhou, Yanli; Ge, Xiangyu

    2018-01-01

    This research studies the nexus of nitrogen oxide emissions and economic development/urbanization. Under the environmental Kuznets curve (EKC) hypothesis, we apply the analysis technique of spatial panel data in the STIRPAT framework, and thus obtain the estimated impacts of income/urbanization on nitrogen oxide emission systematically. The empirical findings suggest that spatial dependence on nitrogen oxide emission distribution exist at provincial level, and the inverse N-shape EKC describes both income-nitrogen oxide and urbanization-nitrogen oxide nexuses. In addition, some well-directed policy advices are made to reduce the nitrogen oxide emission in future.

  6. SLR and GPS spatial techniques in ITRF. Argentine results.

    Science.gov (United States)

    Actis, Eloy Vicente; Huang, Dongping; Márquez, Raúl; Adarvez, Sonia; Flores, Matías; Brizuela, Diego; Nievas, Jesica; Podestá, Ricardo; Pacheco, Ana M.; Rojas, Hernán Alvis; Yin, Zhiqiang; Li, Jinzeng; Han, Yanben; Liu, Weidong; Wang, Rui

    2012-08-01

    Along the late 30 years spatial geodetic techniques enable us to measure horizontal and vertical deformations of the Earth’s surface with a very high precision. Performing this task we made Satellite Laser Ranging (SLR), and Global Positioning System (GPS) observations in South America ILRS 7406 Station placed at Observatorio Astronómico Félix Aguilar (OAFA) in San Juan, Argentina, accomplishing a Cooperation Agreement between CAS - NAOC and OAFA - UNSJ. Trough LAGEOS II Satellite observations we obtain rectangular coordinates of San Juan ILRS Station in the Terrestrial Reference Frame (ITR 2000), standing out that Argentine Station data were included in the late arrangements ITRF given by International Earth Rotation and Reference System Service (IERS). Spatial and temporary variations of the epoch 2010 - 2011 were evaluated finding out remarkable displacements, of about a half meter, related with seismic events on the region. We confirm these deformations by means of GP S determinations referred to Permanent GPS Station placed nearby the SLR Station.

  7. Linking Spatial Variations in Water Quality with Water and Land Management using Multivariate Techniques.

    Science.gov (United States)

    Wan, Yongshan; Qian, Yun; Migliaccio, Kati White; Li, Yuncong; Conrad, Cecilia

    2014-03-01

    Most studies using multivariate techniques for pollution source evaluation are conducted in free-flowing rivers with distinct point and nonpoint sources. This study expanded on previous research to a managed "canal" system discharging into the Indian River Lagoon, Florida, where water and land management is the single most important anthropogenic factor influencing water quality. Hydrometric and land use data of four drainage basins were uniquely integrated into the analysis of 25 yr of monthly water quality data collected at seven stations to determine the impact of water and land management on the spatial variability of water quality. Cluster analysis (CA) classified seven monitoring stations into four groups (CA groups). All water quality parameters identified by discriminant analysis showed distinct spatial patterns among the four CA groups. Two-step principal component analysis/factor analysis (PCA/FA) was conducted with (i) water quality data alone and (ii) water quality data in conjunction with rainfall, flow, and land use data. The results indicated that PCA/FA of water quality data alone was unable to identify factors associated with management activities. The addition of hydrometric and land use data into PCA/FA revealed close associations of nutrients and color with land management and storm-water retention in pasture and citrus lands; total suspended solids, turbidity, and NO + NO with flow and Lake Okeechobee releases; specific conductivity with supplemental irrigation supply; and dissolved O with wetland preservation. The practical implication emphasizes the importance of basin-specific land and water management for ongoing pollutant loading reduction and ecosystem restoration programs. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  8. A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

    Science.gov (United States)

    Mayer, J. M.; Stead, D.

    2017-04-01

    With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

  9. FIA data and species diversity—successes and failures using multivariate analysis techniques, spatial lag and error models and hot-spot analysis

    Science.gov (United States)

    Andrew J. Hartsell

    2015-01-01

    This study will investigate how global and local predictors differ with varying spatial scale in relation to species evenness and richness in the gulf coastal plain. Particularly, all-live trees >= one-inch d.b.h. Forest Inventory and Analysis (FIA) data was used as the basis for the study. Watersheds are defined by the USGS 12 digit hydrologic units. The...

  10. Spatial Econometric data analysis: moving beyond traditional models

    NARCIS (Netherlands)

    Florax, R.J.G.M.; Vlist, van der A.J.

    2003-01-01

    This article appraises recent advances in the spatial econometric literature. It serves as the introduction too collection of new papers on spatial econometric data analysis brought together in this special issue, dealing specifically with new extensions to the spatial econometric modeling

  11. A Spatial Analysis of the Potato Cyst Nematode Globodera pallida in Idaho.

    Science.gov (United States)

    Dandurand, Louise-Marie; Contina, Jean Bertrand; Knudsen, Guy R

    2018-03-13

    The potato cyst nematode (PCN), Globodera pallida, is a globally regulated and quarantine potato pest. It was detected for the first time in the U.S. in the state of Idaho in 2006. A spatial analysis was performed to: (i) understand the spatial arrangement of PCN infested fields in southern Idaho using spatial point pattern analysis; and (ii) evaluate the potential threat of PCN for entry to new areas using spatial interpolation techniques. Data point locations, cyst numbers and egg viability values for each infested field were collected by USDA-APHIS during 2006-2014. Results showed the presence of spatially clustered PCN infested fields (P = 0.003). We determined that the spread of PCN grew in diameter from the original center of infestation toward the southwest as an ellipsoidal-shaped cluster. Based on the aggregated spatial pattern of distribution and the low extent level of PCN infested fields in southern Idaho, we determined that PCN spread followed a contagion effect scenario, where nearby infested fields contributed to the infestation of new fields, probably through soil contaminated agricultural equipment or tubers. We determined that the recent PCN presence in southern Idaho is unlikely to be associated with new PCN entry from outside the state of Idaho. The relative aggregation of PCN infested fields, the low number of cysts recovered, and the low values in egg viability facilitate quarantine activities and confine this pest to a small area, which, in 2017, is estimated to be 1,233 hectares. The tools and methods provided in this study should facilitate comprehensive approaches to improve PCN control and eradication programs as well as to raise public awareness about this economically important potato pest.

  12. Spatial analysis of falls in an urban community of Hong Kong

    Directory of Open Access Journals (Sweden)

    Wong Wing C

    2009-03-01

    Full Text Available Abstract Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh and Standard Deviational Ellipse (SDE techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies.

  13. Spatial analysis of falls in an urban community of Hong Kong

    Science.gov (United States)

    Lai, Poh C; Low, Chien T; Wong, Martin; Wong, Wing C; Chan, Ming H

    2009-01-01

    Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh) and Standard Deviational Ellipse (SDE) techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies. PMID:19291326

  14. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    Science.gov (United States)

    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.

  15. Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Deutsch, Jared L., E-mail: jdeutsch@ualberta.ca [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Palmer, Kevin [Teck Resources Limited (Canada); Deutsch, Clayton V.; Szymanski, Jozef [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Etsell, Thomas H. [University of Alberta, Department of Chemical and Materials Engineering (Canada)

    2016-06-15

    High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.

  16. An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

    Science.gov (United States)

    Bhardwaj, Kaushal; Patra, Swarnajyoti

    2018-04-01

    Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

  17. Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

    Science.gov (United States)

    Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

    2015-05-01

    The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

  18. Spatially resolved chemical analysis of cicada wings using laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS).

    Science.gov (United States)

    Román, Jessica K; Walsh, Callee M; Oh, Junho; Dana, Catherine E; Hong, Sungmin; Jo, Kyoo D; Alleyne, Marianne; Miljkovic, Nenad; Cropek, Donald M

    2018-03-01

    Laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS) is an emerging bioanalytical tool for direct imaging and analysis of biological tissues. Performing ionization in an ambient environment, this technique requires little sample preparation and no additional matrix, and can be performed on natural, uneven surfaces. When combined with optical microscopy, the investigation of biological samples by LAESI allows for spatially resolved compositional analysis. We demonstrate here the applicability of LAESI-IMS for the chemical analysis of thin, desiccated biological samples, specifically Neotibicen pruinosus cicada wings. Positive-ion LAESI-IMS accurate ion-map data was acquired from several wing cells and superimposed onto optical images allowing for compositional comparisons across areas of the wing. Various putative chemical identifications were made indicating the presence of hydrocarbons, lipids/esters, amines/amides, and sulfonated/phosphorylated compounds. With the spatial resolution capability, surprising chemical distribution patterns were observed across the cicada wing, which may assist in correlating trends in surface properties with chemical distribution. Observed ions were either (1) equally dispersed across the wing, (2) more concentrated closer to the body of the insect (proximal end), or (3) more concentrated toward the tip of the wing (distal end). These findings demonstrate LAESI-IMS as a tool for the acquisition of spatially resolved chemical information from fragile, dried insect wings. This LAESI-IMS technique has important implications for the study of functional biomaterials, where understanding the correlation between chemical composition, physical structure, and biological function is critical. Graphical abstract Positive-ion laser-ablation electrospray ionization mass spectrometry coupled with optical imaging provides a powerful tool for the spatially resolved chemical analysis of cicada wings.

  19. A spatial compression technique for head-related transfer function interpolation and complexity estimation

    DEFF Research Database (Denmark)

    Shekarchi, Sayedali; Christensen-Dalsgaard, Jakob; Hallam, John

    2015-01-01

    A head-related transfer function (HRTF) model employing Legendre polynomials (LPs) is evaluated as an HRTF spatial complexity indicator and interpolation technique in the azimuth plane. LPs are a set of orthogonal functions derived on the sphere which can be used to compress an HRTF dataset...

  20. Reconstruction and analysis of temperature and density spatial profiles inertial confinement fusion implosion cores

    International Nuclear Information System (INIS)

    Mancini, R. C.

    2007-01-01

    We discuss several methods for the extraction of temperature and density spatial profiles in inertial confinement fusion implosion cores based on the analysis of the x-ray emission from spectroscopic tracers added to the deuterium fuel. The ideas rely on (1) detailed spectral models that take into account collisional-radiative atomic kinetics, Stark broadened line shapes, and radiation transport calculations, (2) the availability of narrow-band, gated pinhole and slit x-ray images, and space-resolved line spectra of the core, and (3) several data analysis and reconstruction methods that include a multi-objective search and optimization technique based on a novel application of Pareto genetic algorithms to plasma spectroscopy. The spectroscopic analysis yields the spatial profiles of temperature and density in the core at the collapse of the implosion, and also the extent of shell material mixing into the core. Results are illustrated with data recorded in implosion experiments driven by the OMEGA and Z facilities

  1. Modification in the assembly technique of histological sections for analysis of spatial distribution of boron by autoradiography

    International Nuclear Information System (INIS)

    Portu, A; Carpano, M; Dagrosa, A; Pozzi, E; Thorp, S; Curotto, P; Cabrini, R L; Saint Martin, G

    2012-01-01

    The Boron Neutron Capture Therapy (BNCT) is a modality for the treatment of cancer, based on the capture reaction 10 B(n,α) 7 Li. The emitted particles are highly transferred linear of energy and have a short range in tissue (10 μ). Therefore, if the boron is selectively accumulates in tumor cellulo, the damage will be limited to preserving normal cellulo. Thus, the knowledge of the location of 10 B in the different structures of biological tissues as tumor and surrounding tissue, is essential when considering BNCT treatment (Barth et al., 2005). Neutron autoradiography is one of the few methods that allow studying the distribution spatial of elements emitters in a material containing such. As part of BNCT, the first step in performing autoradiography involves placing a freeze tissue section on a nuclear track detector (SSNTD) (Wittig et al., 2008). For this purpose, tissue samples are fixed in N 2 (liq) when they are resected after infusion boronated compound. The sample-detector arrangement is irradiated with thermal neutrons and elements cast in the capture reaction zones produce latent damage SSNTD. Chemically attacking the detector, this latent trace level can be amplified by optical microscopy. Thus, the distribution of 10 B in biological samples can be evaluated, so that this technique is suitable for studying the uptake of boron compounds for the different histological structures. In our laboratory, we have developed neutron autoradiography and has been applied to the study of different biological models (Portu et al., 2011a). In particular, the study conducted by the micro-distribution 10 B in tumors from nude mice model of cutaneous melanomas injected with boronophenylalanine (BPA) (Carpano et al, 2010;. Portu et al, 2011b.). Still using means of support for the sample to be cut, as OCTTM, the lack of structure of necrotic areas of tumors such causes tearing of these regions in the cutting process, which prevents achieving adequate for analysis sections

  2. Spatial analysis of the electrical energy demand in Greece

    International Nuclear Information System (INIS)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2017-01-01

    The Electrical Energy Demand (EED) of the agricultural, commercial and industrial sector in Greece, as well as its use for domestic activities, public and municipal authorities and street lighting are analysed spatially using Geographical Information System and spatial statistical methods. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the NUTS (Nomenclature of Territorial Units for Statistics) level 3. The aim is to identify spatial patterns of the EED and its transformations such as the ratios of the EED to socioeconomic variables, i.e. the population, the total area, the population density and the Gross Domestic Product (GDP). Based on the analysis, Greece is divided in five regions, each one with a different development model, i.e. Attica and Thessaloniki which are two heavily populated major poles, Thessaly and Central Greece which form a connected geographical region with important agricultural and industrial sector, the islands and some coastal areas which are characterized by an important commercial sector and the rest Greek areas. The spatial patterns can provide additional information for policy decision about the electrical energy management and better representation of the regional socioeconomic conditions. - Highlights: • We visualize spatially the Electrical Energy Demand (EED) in Greece. • We apply spatial analysis methods to the EED data. • Spatial patterns of the EED are identified. • Greece is classified in five distinct groups, based on the analysis. • The results can be used for optimal planning of the electric system.

  3. Spatial statistical analysis of basal stem root disease under natural field epidemic of oil palm

    Science.gov (United States)

    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.

  4. Spatial analysis of weed patterns

    NARCIS (Netherlands)

    Heijting, S.

    2007-01-01

    Keywords: Spatial analysis, weed patterns, Mead’s test, space-time correlograms, 2-D correlograms, dispersal, Generalized Linear Models, heterogeneity, soil, Taylor’s power law. Weeds in agriculture occur in patches. This thesis is a contribution to the characterization of this patchiness, to its

  5. Spatial analysis of binary health indicators with local smoothing techniques The Viadana study.

    Science.gov (United States)

    Girardi, Paolo; Marcon, Alessandro; Rava, Marta; Pironi, Vanda; Ricci, Paolo; de Marco, Roberto

    2012-01-01

    When pollution data from a monitoring network is not available, mapping the spatial distribution of disease can be useful to identify populations at risk and to suggest a potential role for suspected emission sources. We aimed at obtaining a continuous spatial representation of the prevalence of symptoms that are potentially associated with the exposure to the pollutants emitted from the wood factories in the children who live in the district of Viadana (Northern Italy). In 2006, all the parents of the children aged 3-14 years residing in the Viadana district (n = 3854), filled in a questionnaire on respiratory symptoms, irritation symptoms of the eyes and skin, use of health services. The children's residential addresses were also collected and geocoded. Generalized additive models and local weighted regression (LOWESS) were used to estimate the distribution of the symptoms, to test for spatial trends of the symptoms' prevalence and to control for potential confounders. Permutation tests were used to identify the areas of significantly increased risk ("hot spots"). The prevalence of respiratory symptoms, eye symptoms and the use of health services showed a statistically significant spatial variation (p big chipboard industries were located. Hot spots were identified fairly near to one of the two chipboard industries in the district. The north-to-south trend in the prevalence of respiratory and eye symptoms, but not of skin symptoms, as well as the location of hot spots, are consistent with the potential exposure to air pollutants both emitted by the wood factories and related to traffic. In these "high risk areas" monitoring of pollution and preventive actions are clearly needed. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

  6. Spatial analysis of infection by the human immunodeficiency virus among pregnant women

    Directory of Open Access Journals (Sweden)

    Eliane Rolim de Holanda

    2015-06-01

    Full Text Available OBJECTIVES: to analyze the spatial distribution of reported cases of pregnant women infected by the human immunodeficiency virus and to identify the urban areas with greater social vulnerability to the infection among pregnant women.METHOD: ecological study, developed by means of spatial analysis techniques of area data. Secondary data were used from the Brazilian National Disease Notification System for the city of Recife, Pernambuco. Birth data were obtained from the Brazilian Information System on Live Births and socioeconomic data from the 2010 Demographic Census.RESULTS: the presence of spatial self-correlation was verified. Moran's Index was significant for the distribution. Clusters were identified, considered as high-risk areas, located in grouped neighborhoods, with equally high infection rates among pregnant women. A neighborhood located in the Northwest of the city was distinguished, considered in an epidemiological transition phase.CONCLUSION: precarious living conditions, as evidenced by the indicators illiteracy, absence of prenatal care and poverty, were relevant for the risk of vertical HIV transmission, converging to the grouping of cases among disadvantaged regions.

  7. TU-CD-304-08: Feasibility of a VMAT-Based Spatially Fractionated Grid Therapy Technique

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, B; Liu, M; Huang, Y; Kim, J; Brown, S; Siddiqui, F; Chetty, I; Wen, N [Henry Ford Health System, Detroit, MI (United States); Jin, J [Georgia Regents University, Augusta, GA (Georgia)

    2015-06-15

    Purpose: Grid therapy (GT) uses spatially modulated radiation doses to treat large tumors without significant toxicities. Incorporating 3D conformal-RT or IMRT improved single-field GT by reducing dose to normal tissues spatially through the use of multiple fields. The feasibility of a MLC-based, inverse-planned multi-field GT technique has been demonstrated. Volumetric modulated arc therapy (VMAT) provides conformal dose distributions with the additional potential advantage of reduced treatment times. In this study, we characterize a new VMAT-based GT (VMAT-GT) technique with respect to its deliverability and dosimetric accuracy. Methods: A lattice of 5mm-diameter spheres was created as the boost volume within a large treatment target. A simultaneous boost VMAT (RapidArc) plan with 8Gy to the target and 20Gy to the boost volume was generated using the Eclipse treatment planning system (AAA-v11). The linac utilized HD120 MLC and 6MV flattening-filter free beam. Four non-coplanar arcs, with couch angles at 0, 45, 90 and 317° were used. Collimator angles were at 45 and 315°. The plan was mapped to a phantom. Calibrated Gafchromic EBT3 films were used to measure the delivered dose. Results: The VMAT plan generated a highly spatially modulated dose distribution in the target. D95%, D50%, D5% for the spheres and the targets in Gy were 18.9, 20.6, 23 and 8.0, 9.6, 14.8, respectively. D50% for a 1cm ring 1cm outside the target was 3.0Gy. The peak-to-valley ratio of this technique is comparable to previously proposed techniques, but the MUs were reduced by almost 50%. Film dosimetry showed good agreement between calculated and delivered dose, with an overall gamma passing rate of >98% (3% and 1mm). The point dose differences at sphere centers varied from 2–8%. Conclusion: The deliverability and dose calculation accuracy of the proposed VMAT-GT technique demonstrates that ablative radiation doses are deliverable to large tumors safely and efficiently.

  8. Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

    Science.gov (United States)

    Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

    2017-12-01

    The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

  9. Crash rates analysis in China using a spatial panel model

    Directory of Open Access Journals (Sweden)

    Wonmongo Lacina Soro

    2017-10-01

    Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.

  10. Spatial Air Quality Modelling Using Chemometrics Techniques: A Case Study in Peninsular Malaysia

    International Nuclear Information System (INIS)

    Azman Azid; Hafizan Juahir; Mohammad Azizi Amran; Zarizal Suhaili; Mohamad Romizan Osman; Asyaari Muhamad; Asyaari Muhamad; Ismail Zainal Abidin; Nur Hishaam Sulaiman; Ahmad Shakir Mohd Saudi

    2015-01-01

    This study shows the effectiveness of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and multiple linear regressions (MLR) for assessment of air quality data and recognition of air pollution sources. 12 months data (January-December 2007) consisting of 14 stations in Peninsular Malaysia with 14 parameters were applied. Three significant clusters - low pollution source (LPS), moderate pollution source (MPS), and slightly high pollution source (SHPS) were generated via HACA. Forward stepwise of DA managed to discriminate eight variables, whereas backward stepwise of DA managed to discriminate nine variables out of fourteen variables. The PCA and FA results show the main contributor of air pollution in Peninsular Malaysia is the combustion of fossil fuel from industrial activities, transportation and agriculture systems. Four MLR models show that PM_1_0 account as the most and the highest pollution contributor to Malaysian air quality. From the study, it can be stipulated that the application of chemometrics techniques can disclose meaningful information on the spatial variability of a large and complex air quality data. A clearer review about the air quality and a novelty design of air quality monitoring network for better management of air pollution can be achieved via these methods. (author)

  11. Spatial analysis of NDVI readings with difference sampling density

    Science.gov (United States)

    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...

  12. Spatial Analysis Methods of Road Traffic Collisions

    DEFF Research Database (Denmark)

    Loo, Becky P. Y.; Anderson, Tessa Kate

    Spatial Analysis Methods of Road Traffic Collisions centers on the geographical nature of road crashes, and uses spatial methods to provide a greater understanding of the patterns and processes that cause them. Written by internationally known experts in the field of transport geography, the book...... outlines the key issues in identifying hazardous road locations (HRLs), considers current approaches used for reducing and preventing road traffic collisions, and outlines a strategy for improved road safety. The book covers spatial accuracy, validation, and other statistical issues, as well as link...

  13. Spatially adaptive mixture modeling for analysis of FMRI time series.

    Science.gov (United States)

    Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

    2010-04-01

    Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

  14. A matter of ephemerality: the study of Kel Tadrart Tuareg (southwest Libya campsites via quantitative spatial analysis

    Directory of Open Access Journals (Sweden)

    Stefano Biagetti

    2016-03-01

    Full Text Available We examined the settlement structure from the Kel Tadrart Tuareg, a small pastoral society from southwest Libya. Our objective was to apply spatial analysis to establish the statistical significance of specific patterns in the settlement layout. In particular, we examined whether there is a separation between domestic and livestock spaces, and whether particular residential features dedicated to guests are spatially isolated. We used both established statistical techniques and newly developed bespoke analyses to test our hypotheses, and then discuss the results in the light of possible applications to other case studies.

  15. The method of determining surface water erosion influence on agricultural valorization of soils with usage of geoprocessing techniques and spatial information systems

    Directory of Open Access Journals (Sweden)

    Prus Barbara

    2016-12-01

    Full Text Available The aim of the paper is to propose methodical solutions concerning synthetic agricultural analysis of production space which consists in combined (synthetic – in spatial and statistical contexts – analysis and evaluation of quality and farming utility of soils in connection with soils erosive risk level. The paper is aimed at presentation of methodology useful in such type of analyses as well as demonstration to what extent the areas of farming production space being subject to restrictive protection are exposed to destructive effect of surface water erosion. Own factor (HDSP.E was suggested, which is a high degree synthesis of soil protection in connection with degrees of surface water erosion risk. The proposed methodology was used for detailed spatial analyses performed for Tomice – the Małopolska rural commune (case study. The area model elaborated for the proposed methodology’s purpose faced with soils mechanical composition allowed to make a model of surface water erosion in five-grade scale. Synthetic evaluation (product of spatial objects on numerous thematic layers of quality and farming utility of soils and also zones of surface water erosion risk allowed to assign spatial distribution of HDSP.E factor (abbreviation of high degree of soil protection combined with erosion. The analyses enabled to determine proportional contribution of the most valuable resources of farming production space that are subject to soil erosion negative phenomenon. Geoprocessing techniques used for the analyses of environmental elements of farming production space were applied in the paper. The analysis of spatial distribution of researched phenomena was elaborated in Quantum GIS programme.

  16. Probing spatial locality in ionic liquids with the grand canonical adaptive resolution molecular dynamics technique

    Science.gov (United States)

    Shadrack Jabes, B.; Krekeler, C.; Klein, R.; Delle Site, L.

    2018-05-01

    We employ the Grand Canonical Adaptive Resolution Simulation (GC-AdResS) molecular dynamics technique to test the spatial locality of the 1-ethyl 3-methyl imidazolium chloride liquid. In GC-AdResS, atomistic details are kept only in an open sub-region of the system while the environment is treated at coarse-grained level; thus, if spatial quantities calculated in such a sub-region agree with the equivalent quantities calculated in a full atomistic simulation, then the atomistic degrees of freedom outside the sub-region play a negligible role. The size of the sub-region fixes the degree of spatial locality of a certain quantity. We show that even for sub-regions whose radius corresponds to the size of a few molecules, spatial properties are reasonably reproduced thus suggesting a higher degree of spatial locality, a hypothesis put forward also by other researchers and that seems to play an important role for the characterization of fundamental properties of a large class of ionic liquids.

  17. Development of a new analysis technique to measure low radial-order p modes in spatially-resolved helioseismic data

    Energy Technology Data Exchange (ETDEWEB)

    Salabert, David; Leibacher, John W [National Solar Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States); Appourchaux, Thierry [Institut d' Astrophysique Spatiale, CNRS-Universite Paris XI UMR 8617, 91405 Orsay Cedex (France)], E-mail: dsalabert@nso.edu

    2008-10-15

    In order to take full advantage of the long time series collected by the GONG and MDI helioseismic projects, we present here an adaptation of the rotation-corrected m-averaged spectrum technique in order to observe low radial-order solar p modes. Modeled profiles of the solar rotation demonstrated the potential advantage of such a technique. Here we develop a new analysis procedure which finds the best estimates of the shift of each m of a given (n, {iota}) multiplet, commonly expressed as an expansion in a set of orthogonal polynomials, which yield the narrowest mode in the m-averaged spectrum. We apply the technique to the GONG data for modes with 1 {<=} {iota} {<=} 25 and show that it allows us to measure lower-frequency modes than with classic peak-fitting analysis of the individual-m spectra.

  18. Research progress and hotspot analysis of spatial interpolation

    Science.gov (United States)

    Jia, Li-juan; Zheng, Xin-qi; Miao, Jin-li

    2018-02-01

    In this paper, the literatures related to spatial interpolation between 1982 and 2017, which are included in the Web of Science core database, are used as data sources, and the visualization analysis is carried out according to the co-country network, co-category network, co-citation network, keywords co-occurrence network. It is found that spatial interpolation has experienced three stages: slow development, steady development and rapid development; The cross effect between 11 clustering groups, the main convergence of spatial interpolation theory research, the practical application and case study of spatial interpolation and research on the accuracy and efficiency of spatial interpolation. Finding the optimal spatial interpolation is the frontier and hot spot of the research. Spatial interpolation research has formed a theoretical basis and research system framework, interdisciplinary strong, is widely used in various fields.

  19. Ion beam analysis techniques applied to large scale pollution studies

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, D D; Bailey, G; Martin, J; Garton, D; Noorman, H; Stelcer, E; Johnson, P [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW (Australia)

    1994-12-31

    Ion Beam Analysis (IBA) techniques are ideally suited to analyse the thousands of filter papers a year that may originate from a large scale aerosol sampling network. They are fast multi-elemental and, for the most part, non-destructive so other analytical methods such as neutron activation and ion chromatography can be performed afterwards. ANSTO in collaboration with the NSW EPA, Pacific Power and the Universities of NSW and Macquarie has established a large area fine aerosol sampling network covering nearly 80,000 square kilometres of NSW with 25 fine particle samplers. This network known as ASP was funded by the Energy Research and Development Corporation (ERDC) and commenced sampling on 1 July 1991. The cyclone sampler at each site has a 2.5 {mu}m particle diameter cut off and runs for 24 hours every Sunday and Wednesday using one Gillman 25mm diameter stretched Teflon filter for each day. These filters are ideal targets for ion beam analysis work. Currently ANSTO receives 300 filters per month from this network for analysis using its accelerator based ion beam techniques on the 3 MV Van de Graaff accelerator. One week a month of accelerator time is dedicated to this analysis. Four simultaneous accelerator based IBA techniques are used at ANSTO, to analyse for the following 24 elements: H, C, N, O, F, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Cu, Ni, Co, Zn, Br and Pb. The IBA techniques were proved invaluable in identifying sources of fine particles and their spatial and seasonal variations accross the large area sampled by the ASP network. 3 figs.

  20. Ion beam analysis techniques applied to large scale pollution studies

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, D.D.; Bailey, G.; Martin, J.; Garton, D.; Noorman, H.; Stelcer, E.; Johnson, P. [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW (Australia)

    1993-12-31

    Ion Beam Analysis (IBA) techniques are ideally suited to analyse the thousands of filter papers a year that may originate from a large scale aerosol sampling network. They are fast multi-elemental and, for the most part, non-destructive so other analytical methods such as neutron activation and ion chromatography can be performed afterwards. ANSTO in collaboration with the NSW EPA, Pacific Power and the Universities of NSW and Macquarie has established a large area fine aerosol sampling network covering nearly 80,000 square kilometres of NSW with 25 fine particle samplers. This network known as ASP was funded by the Energy Research and Development Corporation (ERDC) and commenced sampling on 1 July 1991. The cyclone sampler at each site has a 2.5 {mu}m particle diameter cut off and runs for 24 hours every Sunday and Wednesday using one Gillman 25mm diameter stretched Teflon filter for each day. These filters are ideal targets for ion beam analysis work. Currently ANSTO receives 300 filters per month from this network for analysis using its accelerator based ion beam techniques on the 3 MV Van de Graaff accelerator. One week a month of accelerator time is dedicated to this analysis. Four simultaneous accelerator based IBA techniques are used at ANSTO, to analyse for the following 24 elements: H, C, N, O, F, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Cu, Ni, Co, Zn, Br and Pb. The IBA techniques were proved invaluable in identifying sources of fine particles and their spatial and seasonal variations accross the large area sampled by the ASP network. 3 figs.

  1. Asymptotic analysis of spatial discretizations in implicit Monte Carlo

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2009-01-01

    We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large. We demonstrate the validity of our analysis with a set of numerical examples.

  2. Regional Convergence of Income: Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Vera Ivanovna Ivanova

    2014-12-01

    Full Text Available Russia has a huge territory and a strong interregional heterogeneity, so we can assume that geographical factors have a significant impact on the pace of economic growth in Russian regions. Therefore the article is focused on the following issues: 1 correlation between comparative advantages of geographical location and differences in growth rates; 2 impact of more developed regions on their neighbors and 3 correlation between economic growth of regions and their spatial interaction. The article is devoted to the empirical analysis of regional per capita incomes from 1996 to 2012 and explores the dynamics of the spatial autocorrelation of regional development indicator. It is shown that there is a problem of measuring the intensity of spatial dependence: factor value of Moran’s index varies greatly depending on the choice of the matrix of distances. In addition, with the help of spatial econometrics the author tests the following hypotheses: 1 there is convergence between regions for a specified period; 2 the process of beta convergence is explained by the spatial arrangement of regions and 3 there is positive impact of market size on regional growth. The author empirically confirmed all three hypotheses

  3. Quantifying spatial heterogeneity from images

    International Nuclear Information System (INIS)

    Pomerantz, Andrew E; Song Yiqiao

    2008-01-01

    Visualization techniques are extremely useful for characterizing natural materials with complex spatial structure. Although many powerful imaging modalities exist, simple display of the images often does not convey the underlying spatial structure. Instead, quantitative image analysis can extract the most important features of the imaged object in a manner that is easier to comprehend and to compare from sample to sample. This paper describes the formulation of the heterogeneity spectrum to show the extent of spatial heterogeneity as a function of length scale for all length scales to which a particular measurement is sensitive. This technique is especially relevant for describing materials that simultaneously present spatial heterogeneity at multiple length scales. In this paper, the heterogeneity spectrum is applied for the first time to images from optical microscopy. The spectrum is measured for thin section images of complex carbonate rock cores showing heterogeneity at several length scales in the range 10-10 000 μm.

  4. Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means

    Science.gov (United States)

    Song, Chengyun; Liu, Zhining; Cai, Hanpeng; Wang, Yaojun; Li, Xingming; Hu, Guangmin

    2017-12-01

    Seismic facies analysis techniques combine classification algorithms and seismic attributes to generate a map that describes main reservoir heterogeneities. However, most of the current classification algorithms only view the seismic attributes as isolated data regardless of their spatial locations, and the resulting map is generally sensitive to noise. In this paper, a regularized fuzzy c-means (RegFCM) algorithm is used for unsupervised seismic facies analysis. Due to the regularized term of the RegFCM algorithm, the data whose adjacent locations belong to same classification will play a more important role in the iterative process than other data. Therefore, this method can reduce the effect of seismic data noise presented in discontinuous regions. The synthetic data with different signal/noise values are used to demonstrate the noise tolerance ability of the RegFCM algorithm. Meanwhile, the fuzzy factor, the neighbour window size and the regularized weight are tested using various values, to provide a reference of how to set these parameters. The new approach is also applied to a real seismic data set from the F3 block of the Netherlands. The results show improved spatial continuity, with clear facies boundaries and channel morphology, which reveals that the method is an effective seismic facies analysis tool.

  5. Comparison of spatial interpolation techniques to predict soil properties in the colombian piedmont eastern plains

    Directory of Open Access Journals (Sweden)

    Mauricio Castro Franco

    2017-07-01

    Full Text Available Context: Interpolating soil properties at field-scale in the Colombian piedmont eastern plains is challenging due to: the highly and complex variable nature of some processes; the effects of the soil; the land use; and the management. While interpolation techniques are being adapted to include auxiliary information of these effects, the soil data are often difficult to predict using conventional techniques of spatial interpolation. Method: In this paper, we evaluated and compared six spatial interpolation techniques: Inverse Distance Weighting (IDW, Spline, Ordinary Kriging (KO, Universal Kriging (UK, Cokriging (Ckg, and Residual Maximum Likelihood-Empirical Best Linear Unbiased Predictor (REML-EBLUP, from conditioned Latin Hypercube as a sampling strategy. The ancillary information used in Ckg and REML-EBLUP was indexes calculated from a digital elevation model (MDE. The “Random forest” algorithm was used for selecting the most important terrain index for each soil properties. Error metrics were used to validate interpolations against cross validation. Results: The results support the underlying assumption that HCLc captured adequately the full distribution of variables of ancillary information in the Colombian piedmont eastern plains conditions. They also suggest that Ckg and REML-EBLUP perform best in the prediction in most of the evaluated soil properties. Conclusions: Mixed interpolation techniques having auxiliary soil information and terrain indexes, provided a significant improvement in the prediction of soil properties, in comparison with other techniques.

  6. Geo-Spatial Social Network Analysis of Social Media to Mitigate Disasters

    Science.gov (United States)

    Carley, K. M.

    2017-12-01

    Understanding the spatial layout of human activity can afford a better understanding many phenomena - such as local cultural, the spread of ideas, and the scope of a disaster. Today, social media is one of the key sensors for acquiring information on socio-cultural activity, some with cues as to the geo-location. We ask, What can be learned by putting such data on maps? For example, are people who chat on line more likely to be near each other? Can Twitter data support disaster planning or early warning? In this talk, such issues are examined using data collected via Twitter and analyzed using ORA. ORA is a network analysis and visualization system. It supports not just social networks (who is interacting with whom), but also high dimensional networks with many types of nodes (e.g. people, organizations, resources, activities …) and relations, geo-spatial network analysis, dynamic network analysis, & geo-temporal analysis. Using ORA lessons learned from five case studies are considered: Arab Spring, Tsunami warning in Padang Indonesia, Twitter around Fukushima in Japan, Typhoon Haiyan (Yolanda), & regional conflict. Using Padang Indonesia data, we characterize the strengths and limitations of social media data to support disaster planning & early warning, identify at risk areas & issues of concern, and estimate where people are and which areas are impacted. Using Fukushima Japanese data, social media is used to estimate geo-spatial regularities in movement and communication that can inform disaster response and risk estimation. Using Arab Spring data, we find that the spread of bots & extremists varies by country and time, to the extent that using twitter to understand who is important or what ideas are critical can be compromised. Bots and extremists can exploit disaster messaging to create havoc and facilitate criminal activity e.g. human trafficking. Event discovery mechanisms support isolating geo-epi-centers for key events become crucial. Spatial inference

  7. SPHARA--a generalized spatial Fourier analysis for multi-sensor systems with non-uniformly arranged sensors: application to EEG.

    Science.gov (United States)

    Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

    2015-01-01

    Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications.

  8. UTOOLS: microcomputer software for spatial analysis and landscape visualization.

    Science.gov (United States)

    Alan A. Ager; Robert J. McGaughey

    1997-01-01

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

  9. Control of spatial discretisation in coastal oil spill modelling

    OpenAIRE

    Li, Yang

    2007-01-01

    Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Searc...

  10. Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

    Directory of Open Access Journals (Sweden)

    Pierre Lafaye de Micheaux

    2011-10-01

    Full Text Available For statistical analysis of functional magnetic resonance imaging (fMRI data sets, we propose a data-driven approach based on independent component analysis (ICA implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package.

  11. Helmintic infections in water buffaloes on Italian farms: a spatial analysis

    Directory of Open Access Journals (Sweden)

    Laura Rinaldi

    2009-05-01

    Full Text Available The present paper reports the results of a cross-sectional survey aimed at obtaining up-to-date information on the spatial distribution of different groups and/or species of helminths in water buffaloes from central Italy. Geographical information systems (GIS and spatial analysis were used to plan the sampling procedures, to display the results as maps and to detect spatial clusters of helminths in the study area. The survey was conducted on 127 water buffalo farms, which were selected in the study area using a grid sampling approach, followed by proportional allocation. Faecal samples (n. = 1,883 collected from the 127 farms were examined using the Flotac dual technique. Gastrointestinal strongyles were the most frequent helminths (33.1% on the tested farms, followed by the liver fluke Fasciola hepatica (7.1%, the rumen fluke Calicophoron daubneyi (7.1%, the nematode Strongyloides spp. (3.1%, the lancet liver fluke Dicrocoelium dendriticum (2.4% and the tapeworm Moniezia spp. (2.4%. In order to display the spatial distribution of the various helminths detected on the water buffalo farms (used as epidemiological unit in our study, point maps were drawn within the GIS. In addition, for each helminth, clustering of test-positive farms were investigated based on location determined by exact coordinates. Using spatial scan statistic, spatial clusters were found for the flukes F. hepatica and C. daubneyi and the cestode Moniezia spp.; these findings are consistent with the life cycle of these parasites, which have strong environmental determinants. In conclusion, the present study demonstrated that, with the appropriate survey-based data at hand, GIS is a useful tool to study epidemiological patterns of infections in veterinary health, in particular in water buffaloes.

  12. Spatial analysis of infection by the human immunodeficiency virus among pregnant women1

    Science.gov (United States)

    de Holanda, Eliane Rolim; Galvão, Marli Teresinha Gimeniz; Pedrosa, Nathália Lima; Paiva, Simone de Sousa; de Almeida, Rosa Lívia Freitas

    2015-01-01

    OBJECTIVES: to analyze the spatial distribution of reported cases of pregnant women infected by the human immunodeficiency virus and to identify the urban areas with greater social vulnerability to the infection among pregnant women. METHOD: ecological study, developed by means of spatial analysis techniques of area data. Secondary data were used from the Brazilian National Disease Notification System for the city of Recife, Pernambuco. Birth data were obtained from the Brazilian Information System on Live Births and socioeconomic data from the 2010 Demographic Census. RESULTS: the presence of spatial self-correlation was verified. Moran's Index was significant for the distribution. Clusters were identified, considered as high-risk areas, located in grouped neighborhoods, with equally high infection rates among pregnant women. A neighborhood located in the Northwest of the city was distinguished, considered in an epidemiological transition phase. CONCLUSION: precarious living conditions, as evidenced by the indicators illiteracy, absence of prenatal care and poverty, were relevant for the risk of vertical HIV transmission, converging to the grouping of cases among disadvantaged regions. PMID:26155005

  13. Geospatial analysis platform: Supporting strategic spatial analysis and planning

    CSIR Research Space (South Africa)

    Naude, A

    2008-11-01

    Full Text Available Whilst there have been rapid advances in satellite imagery and related fine resolution mapping and web-based interfaces (e.g. Google Earth), the development of capabilities for strategic spatial analysis and planning support has lagged behind...

  14. Portable (handheld) clinical device for quantitative spectroscopy of skin, utilizing spatial frequency domain reflectance techniques

    Science.gov (United States)

    Saager, Rolf B.; Dang, An N.; Huang, Samantha S.; Kelly, Kristen M.; Durkin, Anthony J.

    2017-09-01

    Spatial Frequency Domain Spectroscopy (SFDS) is a technique for quantifying in-vivo tissue optical properties. SFDS employs structured light patterns that are projected onto tissues using a spatial light modulator, such as a digital micromirror device. In combination with appropriate models of light propagation, this technique can be used to quantify tissue optical properties (absorption, μa, and scattering, μs', coefficients) and chromophore concentrations. Here we present a handheld implementation of an SFDS device that employs line (one dimensional) imaging. This instrument can measure 1088 spatial locations that span a 3 cm line as opposed to our original benchtop SFDS system that only collects a single 1 mm diameter spot. This imager, however, retains the spectral resolution (˜1 nm) and range (450-1000 nm) of our original benchtop SFDS device. In the context of homogeneous turbid media, we demonstrate that this new system matches the spectral response of our original system to within 1% across a typical range of spatial frequencies (0-0.35 mm-1). With the new form factor, the device has tremendously improved mobility and portability, allowing for greater ease of use in a clinical setting. A smaller size also enables access to different tissue locations, which increases the flexibility of the device. The design of this portable system not only enables SFDS to be used in clinical settings but also enables visualization of properties of layered tissues such as skin.

  15. An experimental magnetic moment determination method based on spatial harmonic analysis of magnetic flux density signatures

    Directory of Open Access Journals (Sweden)

    A.V. Getman

    2013-12-01

    Full Text Available Theoretical aspects of an experimental determination method for residual and inductive magnetic moments of a technical object are considered. As input data, the technical object magnetic induction signatures obtained under its linear movement near a pair of three-component sensors are used. A magnetic signature integration technique based on spatial harmonic analysis of the magnetic field represented by twenty-four multipole coefficients is introduced.

  16. Spatial gene expression quantification: a tool for analysis of in situ hybridizations in sea anemone Nematostella vectensis

    Directory of Open Access Journals (Sweden)

    Botman Daniel

    2012-10-01

    Full Text Available Abstract Background Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly Drosophila melanogaster is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom. In the sea anemone Nematostella vectensis the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. Nematostella is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques. Findings Our new quantification method produces standardized gene expression profiles from raw or annotated Nematostella in situ hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation. Conclusions We created a standard format for gene expression data, which enables quantitative analysis of in situ hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar Nematostella morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.

  17. Rings and sector : intrasite spatial analysis of stone age sites

    NARCIS (Netherlands)

    Stapert, Durk

    1992-01-01

    This thesis deals with intrasite spatial analysis: the analysis of spatial patterns on site level. My main concern has been to develop a simple method for analysing Stone Age sites of a special type: those characterised by the presence of a hearth closely associated in space with an artefact

  18. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  19. Stereological analysis of spatial structures

    DEFF Research Database (Denmark)

    Hansen, Linda Vadgård

    The thesis deals with stereological analysis of spatial structures. One area of focus has been to improve the precision of well-known stereological estimators by including information that is available via automatic image analysis. Furthermore, the thesis presents a stochastic model for star......-shaped three-dimensional objects using the radial function. It appears that the model is highly fleksiblel in the sense that it can be used to describe an object with arbitrary irregular surface. Results on the distribution of well-known local stereological volume estimators are provided....

  20. Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

    Science.gov (United States)

    Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

    2013-01-01

    Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

  1. Asymptotic analysis of the spatial discretization of radiation absorption and re-emission in Implicit Monte Carlo

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2011-01-01

    We perform an asymptotic analysis of the spatial discretization of radiation absorption and re-emission in Implicit Monte Carlo (IMC), a Monte Carlo technique for simulating nonlinear radiative transfer. Specifically, we examine the approximation of absorption and re-emission by a spatially continuous artificial-scattering process and either a piecewise-constant or piecewise-linear emission source within each spatial cell. We consider three asymptotic scalings representing (i) a time step that resolves the mean-free time, (ii) a Courant limit on the time-step size, and (iii) a fixed time step that does not depend on any asymptotic scaling. For the piecewise-constant approximation, we show that only the third scaling results in a valid discretization of the proper diffusion equation, which implies that IMC may generate inaccurate solutions with optically large spatial cells if time steps are refined. However, we also demonstrate that, for a certain class of problems, the piecewise-linear approximation yields an appropriate discretized diffusion equation under all three scalings. We therefore expect IMC to produce accurate solutions for a wider range of time-step sizes when the piecewise-linear instead of piecewise-constant discretization is employed. We demonstrate the validity of our analysis with a set of numerical examples.

  2. Analysis of spatial diffusion of ferric ions in PVA-GTA gel dosimeters through magnetic resonance imaging

    Energy Technology Data Exchange (ETDEWEB)

    Marrale, Maurizio [Dipartimento di Fisica e Chimica, Universitá di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Istituto Nazionale di Fisica Nucleare (INFN) – Gruppo V Sezione di Catania, Via Santa Sofia, 64, 95123 Catania (Italy); ATeN Center, Università di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Collura, Giorgio [Dipartimento di Fisica e Chimica, Universitá di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Istituto Nazionale di Fisica Nucleare (INFN) – Gruppo V Sezione di Catania, Via Santa Sofia, 64, 95123 Catania (Italy); Gallo, Salvatore, E-mail: salvatore.gallo05@unipa.it [Dipartimento di Fisica e Chimica, Universitá di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Istituto Nazionale di Fisica Nucleare (INFN) – Gruppo V Sezione di Catania, Via Santa Sofia, 64, 95123 Catania (Italy); Dipartimento di Fisica, Universitá di Milano, Via Giovanni Celoria 16, 20133 Milano (Italy); Nici, Stefania [Dipartimento di Fisica e Chimica, Universitá di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Tranchina, Luigi [ATeN Center, Università di Palermo, Viale delle Scienze, Edificio 18, 90128 Palermo (Italy); Abbate, Boris Federico [U.O.C. Fisica Sanitaria, A.R.N.A.S., Ospedale Civico Palermo, Piazza Nicola Leotta 4, 90127 Palermo (Italy); Marineo, Sandra; Caracappa, Santo [Istituto Zooprofilattico Sperimentale della Sicilia (IZS), Via Gino Marinuzzi, 3, 90129 Palermo (Italy); and others

    2017-04-01

    Highlights: • Analysis of ferric ions diffusion throughout the gel matrix in PVA-GTA samples. • Measurements with preclinical 7T MRI scanner with spatial resolution of 200 μm. • Diffusion process is much slower for PVA-GTA gels than for agarose ones. - Abstract: This work focused on the analysis of the temporal diffusion of ferric ions through PVA-GTA gel dosimeters. PVA-GTA gel samples, partly exposed with 6 MV X-rays in order to create an initial steep gradient, were mapped using magnetic resonance imaging on a 7T MRI scanner for small animals. Multiple images of the gels were acquired over several hours after irradiation and were analyzed to quantitatively extract the signal profile. The spatial resolution achieved is 200 μm and this makes this technique particularly suitable for the analysis of steep gradients of ferric ion concentration. The results obtained with PVA-GTA gels were compared with those achieved with agarose gels, which is a standard dosimetric gel formulation. The analysis showed that the diffusion process is much slower (more than five times) for PVA-GTA gels than for agarose ones. Furthermore, it is noteworthy that the diffusion coefficient value obtained through MRI analysis is significantly consistent with that obtained in separate study Marini et al. (Submitted for publication) using a totally independent method such as spectrophotometry. This is a valuable result highlighting that the good dosimetric features of this gel matrix not only can be reproduced but also can be measured through independent experimental techniques based on different physical principles.

  3. Digital holography based on multiwavelength spatial-bandwidth-extended capturing-technique using a reference arm (Multi-SPECTRA).

    Science.gov (United States)

    Tahara, Tatsuki; Kaku, Toru; Arai, Yasuhiko

    2014-12-01

    Single-shot digital holography based on multiwavelength spatial-bandwidth-extended capturing-technique using a reference arm (Multi-SPECTRA) is proposed. Both amplitude and quantitative phase distributions of waves containing multiple wavelengths are simultaneously recorded with a single reference arm in a single monochromatic image. Then, multiple wavelength information is separately extracted in the spatial frequency domain. The crosstalk between the object waves with different wavelengths is avoided and the number of wavelengths recorded with both a single-shot exposure and no crosstalk can be increased, by a large spatial carrier that causes the aliasing, and/or by use of a grating. The validity of Multi-SPECTRA is quantitatively, numerically, and experimentally confirmed.

  4. Improving 3d Spatial Queries Search: Newfangled Technique of Space Filling Curves in 3d City Modeling

    Science.gov (United States)

    Uznir, U.; Anton, F.; Suhaibah, A.; Rahman, A. A.; Mioc, D.

    2013-09-01

    The advantages of three dimensional (3D) city models can be seen in various applications including photogrammetry, urban and regional planning, computer games, etc.. They expand the visualization and analysis capabilities of Geographic Information Systems on cities, and they can be developed using web standards. However, these 3D city models consume much more storage compared to two dimensional (2D) spatial data. They involve extra geometrical and topological information together with semantic data. Without a proper spatial data clustering method and its corresponding spatial data access method, retrieving portions of and especially searching these 3D city models, will not be done optimally. Even though current developments are based on an open data model allotted by the Open Geospatial Consortium (OGC) called CityGML, its XML-based structure makes it challenging to cluster the 3D urban objects. In this research, we propose an opponent data constellation technique of space-filling curves (3D Hilbert curves) for 3D city model data representation. Unlike previous methods, that try to project 3D or n-dimensional data down to 2D or 3D using Principal Component Analysis (PCA) or Hilbert mappings, in this research, we extend the Hilbert space-filling curve to one higher dimension for 3D city model data implementations. The query performance was tested using a CityGML dataset of 1,000 building blocks and the results are presented in this paper. The advantages of implementing space-filling curves in 3D city modeling will improve data retrieval time by means of optimized 3D adjacency, nearest neighbor information and 3D indexing. The Hilbert mapping, which maps a subinterval of the [0, 1] interval to the corresponding portion of the d-dimensional Hilbert's curve, preserves the Lebesgue measure and is Lipschitz continuous. Depending on the applications, several alternatives are possible in order to cluster spatial data together in the third dimension compared to its

  5. Research on the spatial analysis method of seismic hazard for island

    International Nuclear Information System (INIS)

    Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

    2017-01-01

    Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform. (paper)

  6. Research on the spatial analysis method of seismic hazard for island

    Science.gov (United States)

    Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

    2017-05-01

    Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform.

  7. Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities.

    Science.gov (United States)

    Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell

    2017-01-01

    In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

  8. Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae habitat and population densities

    Directory of Open Access Journals (Sweden)

    Khalifa M. Al-Kindi

    2017-08-01

    Full Text Available In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

  9. Quantification of Spatial Heterogeneity in Old Growth Forst of Korean Pine

    Science.gov (United States)

    Wang Zhengquan; Wang Qingcheng; Zhang Yandong

    1997-01-01

    Spatial hetergeneity is a very important issue in studying functions and processes of ecological systems at various scales. Semivariogram analysis is an effective technique to summarize spatial data, and quantification of sptail heterogeneity. In this paper, we propose some principles to use semivariograms to characterize and compare spatial heterogeneity of...

  10. a Temporal and Spatial Analysis of Urban Heat Island in Basin City Utilizing Remote Sensing Techniques

    Science.gov (United States)

    Chang, Hsiao-Tung

    2016-06-01

    Urban Heat Island (UHI) has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city's UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST) at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls "sinking heat island". From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  11. A TEMPORAL AND SPATIAL ANALYSIS OF URBAN HEAT ISLAND IN BASIN CITY UTILIZING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    H.-T. Chang

    2016-06-01

    Full Text Available Urban Heat Island (UHI has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city’s UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls “sinking heat island”. From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  12. Research on spatio-temporal database techniques for spatial information service

    Science.gov (United States)

    Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

    2007-06-01

    Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

  13. Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

    Science.gov (United States)

    Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

    2016-12-01

    Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  16. Application of Fourier analysis to multispectral/spatial recognition

    Science.gov (United States)

    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.

  17. Structure analysis of turbulent liquid phase by POD and LSE techniques

    International Nuclear Information System (INIS)

    Munir, S.; Muthuvalu, M. S.; Siddiqui, M. I.; Heikal, M. R.; Aziz, A. Rashid A.

    2014-01-01

    In this paper, vortical structures and turbulence characteristics of liquid phase in both single liquid phase and two-phase slug flow in pipes were studied. Two dimensional velocity vector fields of liquid phase were obtained by Particle image velocimetry (PIV). Two cases were considered one single phase liquid flow at 80 l/m and second slug flow by introducing gas at 60 l/m while keeping liquid flow rate same. Proper orthogonal decomposition (POD) and Linear stochastic estimation techniques were used for the extraction of coherent structures and analysis of turbulence in liquid phase for both cases. POD has successfully revealed large energy containing structures. The time dependent POD spatial mode coefficients oscillate with high frequency for high mode numbers. The energy distribution of spatial modes was also achieved. LSE has pointed out the coherent structured for both cases and the reconstructed velocity fields are in well agreement with the instantaneous velocity fields

  18. Structure analysis of turbulent liquid phase by POD and LSE techniques

    Energy Technology Data Exchange (ETDEWEB)

    Munir, S., E-mail: shahzad-munir@comsats.edu.pk; Muthuvalu, M. S.; Siddiqui, M. I. [Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Heikal, M. R., E-mail: morgan.heikal@petronas.com.my; Aziz, A. Rashid A., E-mail: morgan.heikal@petronas.com.my [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia)

    2014-10-24

    In this paper, vortical structures and turbulence characteristics of liquid phase in both single liquid phase and two-phase slug flow in pipes were studied. Two dimensional velocity vector fields of liquid phase were obtained by Particle image velocimetry (PIV). Two cases were considered one single phase liquid flow at 80 l/m and second slug flow by introducing gas at 60 l/m while keeping liquid flow rate same. Proper orthogonal decomposition (POD) and Linear stochastic estimation techniques were used for the extraction of coherent structures and analysis of turbulence in liquid phase for both cases. POD has successfully revealed large energy containing structures. The time dependent POD spatial mode coefficients oscillate with high frequency for high mode numbers. The energy distribution of spatial modes was also achieved. LSE has pointed out the coherent structured for both cases and the reconstructed velocity fields are in well agreement with the instantaneous velocity fields.

  19. A method for in-situ spatially-resolved analysis of actinides in geomedia

    International Nuclear Information System (INIS)

    Clark, S.B.; Payne, R.F.

    2005-01-01

    It is well documented that U and Pu contamination in soils and sediments is not homogeneously distributed among all environmental surfaces, yet the composition of soil/sediment grains is quite variable and the chemistry controlling the partitioning to specific grains is not well understood. Fission track analysis (FTA) is a technique that directly detects nuclides with high fission cross sections, such as 235 U and 239 Pu, in many matrices including environmental materials. The fission track detector can be used to record the spatial distribution of contamination within the geomedia matrix. One limitation to FTA is that it cannot differentiate between 235 U and 239 Pu, nor does it provide any information about the composition of the grains to which the U or Pu is sorbed. In this work, we have developed an epoxy sample preparation technique that allows location of soil/sediment grains via FTA, and the irradiated sample can subsequently be coupled to laser ablation mass spectrometry (LAMS) with no additional sample preparation. This technique successfully allows grains containing 235 U and/or 239 Pu to be located and further analyzed. LAMS data provides Pu and U isotopic information and stable element analysis of the grains, thus providing the ability to study the nature of the interactions between the Pu and U with the environmental matrix.

  20. Leveraging spatial abstraction in traffic analysis and forecasting with visual analytics

    OpenAIRE

    Andrienko, N.; Andrienko, G.; Rinzivillo, S.

    2016-01-01

    A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered that the traffic intensity (a.k.a. traffic flow or traffic flux) and the mean velocity are interrelated in a spatially abstracted transportation net...

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

    Science.gov (United States)

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

    2017-04-01

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

  2. Multi-spatial analysis of aeolian dune-field patterns

    Science.gov (United States)

    Ewing, Ryan C.; McDonald, George D.; Hayes, Alex G.

    2015-07-01

    Aeolian dune-fields are composed of different spatial scales of bedform patterns that respond to changes in environmental boundary conditions over a wide range of time scales. This study examines how variations in spatial scales of dune and ripple patterns found within dune fields are used in environmental reconstructions on Earth, Mars and Titan. Within a single bedform type, different spatial scales of bedforms emerge as a pattern evolves from an initial state into a well-organized pattern, such as with the transition from protodunes to dunes. Additionally, different types of bedforms, such as ripples, coarse-grained ripples and dunes, coexist at different spatial scales within a dune-field. Analysis of dune-field patterns at the intersection of different scales and types of bedforms at different stages of development provides a more comprehensive record of sediment supply and wind regime than analysis of a single scale and type of bedform. Interpretations of environmental conditions from any scale of bedform, however, are limited to environmental signals associated with the response time of that bedform. Large-scale dune-field patterns integrate signals over long-term climate cycles and reveal little about short-term variations in wind or sediment supply. Wind ripples respond instantly to changing conditions, but reveal little about longer-term variations in wind or sediment supply. Recognizing the response time scales across different spatial scales of bedforms maximizes environmental interpretations from dune-field patterns.

  3. Spatial-temporal-covariance-based modeling, analysis, and simulation of aero-optics wavefront aberrations.

    Science.gov (United States)

    Vogel, Curtis R; Tyler, Glenn A; Wittich, Donald J

    2014-07-01

    We introduce a framework for modeling, analysis, and simulation of aero-optics wavefront aberrations that is based on spatial-temporal covariance matrices extracted from wavefront sensor measurements. Within this framework, we present a quasi-homogeneous structure function to analyze nonhomogeneous, mildly anisotropic spatial random processes, and we use this structure function to show that phase aberrations arising in aero-optics are, for an important range of operating parameters, locally Kolmogorov. This strongly suggests that the d5/3 power law for adaptive optics (AO) deformable mirror fitting error, where d denotes actuator separation, holds for certain important aero-optics scenarios. This framework also allows us to compute bounds on AO servo lag error and predictive control error. In addition, it provides us with the means to accurately simulate AO systems for the mitigation of aero-effects, and it may provide insight into underlying physical processes associated with turbulent flow. The techniques introduced here are demonstrated using data obtained from the Airborne Aero-Optics Laboratory.

  4. Surface analysis the principal techniques

    CERN Document Server

    Vickerman, John C

    2009-01-01

    This completely updated and revised second edition of Surface Analysis: The Principal Techniques, deals with the characterisation and understanding of the outer layers of substrates, how they react, look and function which are all of interest to surface scientists. Within this comprehensive text, experts in each analysis area introduce the theory and practice of the principal techniques that have shown themselves to be effective in both basic research and in applied surface analysis. Examples of analysis are provided to facilitate the understanding of this topic and to show readers how they c

  5. Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.

    Science.gov (United States)

    Nugent, Allison C; Luber, Bruce; Carver, Frederick W; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A

    2017-02-01

    Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

  6. Uses of virtual reality for diagnosis, rehabilitation and study of unilateral spatial neglect: review and analysis.

    Science.gov (United States)

    Tsirlin, Inna; Dupierrix, Eve; Chokron, Sylvie; Coquillart, Sabine; Ohlmann, Theophile

    2009-04-01

    Unilateral spatial neglect is a disabling condition frequently occurring after stroke. People with neglect suffer from various spatial deficits in several modalities, which in many cases impair everyday functioning. A successful treatment is yet to be found. Several techniques have been proposed in the last decades, but only a few showed long-lasting effects and none could completely rehabilitate the condition. Diagnostic methods of neglect could be improved as well. The disorder is normally diagnosed with pen-and-paper methods, which generally do not assess patients in everyday tasks and do not address some forms of the disorder. Recently, promising new methods based on virtual reality have emerged. Virtual reality technologies hold great opportunities for the development of effective assessment and treatment techniques for neglect because they provide rich, multimodal, and highly controllable environments. In order to stimulate advancements in this domain, we present a review and an analysis of the current work. We describe past and ongoing research of virtual reality applications for unilateral neglect and discuss the existing problems and new directions for development.

  7. Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

    Science.gov (United States)

    Altuntas, Alper; Baugh, John

    2017-07-01

    Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

  8. 3D spatially-adaptive canonical correlation analysis: Local and global methods.

    Science.gov (United States)

    Yang, Zhengshi; Zhuang, Xiaowei; Sreenivasan, Karthik; Mishra, Virendra; Curran, Tim; Byrd, Richard; Nandy, Rajesh; Cordes, Dietmar

    2018-04-01

    Local spatially-adaptive canonical correlation analysis (local CCA) with spatial constraints has been introduced to fMRI multivariate analysis for improved modeling of activation patterns. However, current algorithms require complicated spatial constraints that have only been applied to 2D local neighborhoods because the computational time would be exponentially increased if the same method is applied to 3D spatial neighborhoods. In this study, an efficient and accurate line search sequential quadratic programming (SQP) algorithm has been developed to efficiently solve the 3D local CCA problem with spatial constraints. In addition, a spatially-adaptive kernel CCA (KCCA) method is proposed to increase accuracy of fMRI activation maps. With oriented 3D spatial filters anisotropic shapes can be estimated during the KCCA analysis of fMRI time courses. These filters are orientation-adaptive leading to rotational invariance to better match arbitrary oriented fMRI activation patterns, resulting in improved sensitivity of activation detection while significantly reducing spatial blurring artifacts. The kernel method in its basic form does not require any spatial constraints and analyzes the whole-brain fMRI time series to construct an activation map. Finally, we have developed a penalized kernel CCA model that involves spatial low-pass filter constraints to increase the specificity of the method. The kernel CCA methods are compared with the standard univariate method and with two different local CCA methods that were solved by the SQP algorithm. Results show that SQP is the most efficient algorithm to solve the local constrained CCA problem, and the proposed kernel CCA methods outperformed univariate and local CCA methods in detecting activations for both simulated and real fMRI episodic memory data. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Algorithms for large scale singular value analysis of spatially variant tomography systems

    International Nuclear Information System (INIS)

    Cao-Huu, Tuan; Brownell, G.; Lachiver, G.

    1996-01-01

    The problem of determining the eigenvalues of large matrices occurs often in the design and analysis of modem tomography systems. As there is an interest in solving systems containing an ever-increasing number of variables, current research effort is being made to create more robust solvers which do not depend on some special feature of the matrix for convergence (e.g. block circulant), and to improve the speed of already known and understood solvers so that solving even larger systems in a reasonable time becomes viable. Our standard techniques for singular value analysis are based on sparse matrix factorization and are not applicable when the input matrices are large because the algorithms cause too much fill. Fill refers to the increase of non-zero elements in the LU decomposition of the original matrix A (the system matrix). So we have developed iterative solutions that are based on sparse direct methods. Data motion and preconditioning techniques are critical for performance. This conference paper describes our algorithmic approaches for large scale singular value analysis of spatially variant imaging systems, and in particular of PCR2, a cylindrical three-dimensional PET imager 2 built at the Massachusetts General Hospital (MGH) in Boston. We recommend the desirable features and challenges for the next generation of parallel machines for optimal performance of our solver

  10. Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

    Science.gov (United States)

    Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

    2010-05-01

    The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented

  11. Soil analysis. Modern instrumental technique

    International Nuclear Information System (INIS)

    Smith, K.A.

    1993-01-01

    This book covers traditional methods of analysis and specialist monographs on individual instrumental techniques, which are usually not written with soil or plant analysis specifically in mind. The principles of the techniques are combined with discussions of sample preparation and matrix problems, and critical reviews of applications in soil science and related disciplines. Individual chapters are processed separately for inclusion in the appropriate data bases

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

    Science.gov (United States)

    Keenan, Michael R [Albuquerque, NM

    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.

  13. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    International Nuclear Information System (INIS)

    Churmakov, D Y; Meglinski, I V; Piletsky, S A; Greenhalgh, D A

    2003-01-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth

  14. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Churmakov, D Y [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Meglinski, I V [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Piletsky, S A [Institute of BioScience and Technology, Cranfield University, Silsoe, MK45 4DT (United Kingdom); Greenhalgh, D A [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom)

    2003-07-21

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth.

  15. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Science.gov (United States)

    Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

    2003-07-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

  16. Development of a new technique of localised analysis of electrically active defects in semiconductors

    International Nuclear Information System (INIS)

    Heiser, T.

    1988-07-01

    An analysis technique derived from minority carrier transient spectroscopy (MCTS) was developed. By giving this technique spatial resolution via a focused optical beam, it is possible to exploit the high sensitivity and the spectroscopic nature of the technique to develop a method called scanning MCTS (SMCTS) which can be used to acquire information on lateral distribution of electrically active flaws in semiconductors or associated chemical impurities. The optimum conditions, corresponding to the maximum signal for the highest resolution, can be expressed by the value of a signal parameter. The transients system was digitized, considerably reducing background noise. In order to link the SMCTS to a given flaw, two methods for exploiting the transients are used. The method was verified in tests with artificial defects created by laser and on real cases, arising in industrial processes [fr

  17. Computer-assisted techniques to evaluate fringe patterns

    Science.gov (United States)

    Sciammarella, Cesar A.; Bhat, Gopalakrishna K.

    1992-01-01

    Strain measurement using interferometry requires an efficient way to extract the desired information from interferometric fringes. Availability of digital image processing systems makes it possible to use digital techniques for the analysis of fringes. In the past, there have been several developments in the area of one dimensional and two dimensional fringe analysis techniques, including the carrier fringe method (spatial heterodyning) and the phase stepping (quasi-heterodyning) technique. This paper presents some new developments in the area of two dimensional fringe analysis, including a phase stepping technique supplemented by the carrier fringe method and a two dimensional Fourier transform method to obtain the strain directly from the discontinuous phase contour map.

  18. Spatial Search Techniques for Mobile 3D Queries in Sensor Web Environments

    Directory of Open Access Journals (Sweden)

    James D. Carswell

    2013-03-01

    Full Text Available Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query is our novel mobile spatial interaction (MSI prototype that acts as a next-generation base for human interaction within such geospatial sensor web environments/urban landscapes. It filters information using “Hidden Query Removal” functionality that intelligently refines the search space by calculating the geometry of a three dimensional visibility shape (Vista space at a user’s current location. This 3D shape then becomes the query “window” in a spatial database for retrieving information on only those objects visible within a user’s actual 3D field-of-view. 3DQ reduces information overload and serves to heighten situation awareness on constrained commercial off-the-shelf devices by providing visibility space searching as a mobile web service. The effects of variations in mobile spatial search techniques in terms of query speed vs. accuracy are evaluated and presented in this paper.

  19. A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

    Science.gov (United States)

    Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

    2017-02-01

    Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

  20. Statistical and Economic Techniques for Site-specific Nematode Management.

    Science.gov (United States)

    Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

    2014-03-01

    Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

  1. Spatial resolution in depth-controlled surface sensitive x-ray techniques

    International Nuclear Information System (INIS)

    Yun, W.B.; Viccaro, P.J.

    1992-01-01

    The spatial resolution along the surface normal and the total depth probed are two important parameters in depth-controlled surface sensitive X-ray techniques employing grazing incidence geometry. The two parameters are analyzed in terms of optical properties (refractive indices) of the media involved and parameters of the incident X-ray beam: beam divergence, X-ray energy, and spectral bandwidth. We derive analytical expressions of the required beam divergence and spectral bandwidth of the incident beam as a function of the two parameters. Sample calculations are made for X-ray energies between 0.1 and 100 keV and for solid Be, Cu, and Au, representing material matrices consisting of low, medium, and high atomic number elements. A brief discussion on obtaining the required beam divergence and spectral bandwidth from present X-ray sources and optics is given

  2. A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China.

    Science.gov (United States)

    Wang, Wenqiao; Ying, Yangyang; Wu, Quanyuan; Zhang, Haiping; Ma, Dedong; Xiao, Wei

    2015-03-01

    Acute exacerbations of COPD (AECOPD) are important events during disease procedure. AECOPD have negative effect on patients' quality of life, symptoms and lung function, and result in high socioeconomic costs. Though previous studies have demonstrated the significant association between outdoor air pollution and AECOPD hospitalizations, little is known about the spatial relationship utilized a spatial analyzing technique- Geographical Information System (GIS). Using GIS to investigate the spatial association between ambient air pollution and AECOPD hospitalizations in Jinan City, 2009. 414 AECOPD hospitalization cases in Jinan, 2009 were enrolled in our analysis. Monthly concentrations of five monitored air pollutants (NO2, SO2, PM10, O3, CO) during January 2009-December 2009 were provided by Environmental Protection Agency of Shandong Province. Each individual was geocoded in ArcGIS10.0 software. The spatial distribution of five pollutants and the temporal-spatial specific air pollutants exposure level for each individual was estimated by ordinary Kriging model. Spatial autocorrelation (Global Moran's I) was employed to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. A generalized linear model (GLM) using a Poisson distribution with log-link function was used to construct a core model. At residence, concentrations of SO2, PM10, NO2, CO, O3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O3, CO at workplace is 11.39, 8.07, 6.10, and 5.08 respectively. After adjusting for potential confounders in the model, only the PM10 concentrations at workplace showed statistical significance, with a 10 μg/m(3) increase of PM10 at

  3. Application of functional analysis techniques to supervisory systems

    International Nuclear Information System (INIS)

    Lambert, Manuel; Riera, Bernard; Martel, Gregory

    1999-01-01

    The aim of this paper is to apply firstly two interesting functional analysis techniques for the design of supervisory systems for complex processes, and secondly to discuss the strength and the weaknesses of each of them. Two functional analysis techniques have been applied, SADT (Structured Analysis and Design Technique) and FAST (Functional Analysis System Technique) on a process, an example of a Water Supply Process Control (WSPC) system. These techniques allow a functional description of industrial processes. The paper briefly discusses the functions of a supervisory system and some advantages of the application of functional analysis for the design of a 'human' centered supervisory system. Then the basic principles of the two techniques applied on the WSPC system are presented. Finally, the different results obtained from the two techniques are discussed

  4. Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

    Science.gov (United States)

    Santos, Monica; Fragoso, Marcelo

    2010-05-01

    Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

  5. Analysis of spatial and temporal spectra of liquid film surface in annular gas-liquid flow

    Science.gov (United States)

    Alekseenko, Sergey; Cherdantsev, Andrey; Heinz, Oksana; Kharlamov, Sergey; Markovich, Dmitriy

    2013-09-01

    Wavy structure of liquid film in annular gas-liquid flow without liquid entrainment consists of fast long-living primary waves and slow short-living secondary waves. In present paper, results of spectral analysis of this wavy structure are presented. Application of high-speed LIF technique allowed us to perform such analysis in both spatial and temporal domains. Power spectra in both domains are characterized by one-humped shape with long exponential tail. Influence of gas velocity, liquid Reynolds number, liquid viscosity and pipe diameter on frequency of the waves is investigated. When gravity effect is much lesser than the shear stress, similarity of power spectra at different gas velocities is observed. Using combination of spectral analysis and identification of characteristic lines of primary waves, frequency of generation of secondary waves by primary waves is measured.

  6. Review of Spatial Indexing Techniques for Large Urban Data Management

    DEFF Research Database (Denmark)

    Azri, Suhaibah; Ujang, Uznir; Anton, François

    Pressure on land development in urban areas causes progressive efforts in spatial planning and management. The physical expansion of urban areas to accommodate rural migration implies a massive impact to social, economical and political situations of major cities. Most of the models used...... in managing urban areas are moving towards sustainable urban development in order to fulfill current necessities while preserving the resources for future generations. However, in order to manage large amounts of urban spatial data, an efficient spatial data constellation method is needed. With the ease...... of three dimensional (3D) spatial data usage in urban areas as a new source of data input, practical spatial data indexing is necessary to improve data retrieval and management. Current two dimensional (2D) spatial indexing approaches seem not applicable to the current and future spatial developments...

  7. Spatial Analysis for Potential Water Catchment Areas using GIS: Weighted Overlay Technique

    Science.gov (United States)

    Awanda, Disyacitta; Anugrah Nurul, H.; Musfiroh, Zahrotul; Dinda Dwi, N. P.

    2017-12-01

    The development of applied GIS is growing rapidly and has been widely applied in various fields. Preparation of a model to obtain information is one of the benefits of GIS. Obtaining information for water resources such as water catchment areas is one part of GIS modelling. Water catchment model can be utilized to see the distribution of potential and ability of a region in water absorbing. The use of overlay techniques with the weighting obtained from the literature from previous research is used to build the model. Model builder parameters are obtained through remote sensing interpretation techniques such as land use, landforms, and soil texture. Secondary data such as rock type maps are also used as water catchment model parameters. The location of this research is in the upstream part of the Opak river basin. The purpose of this research is to get information about potential distribution of water catchment area with overlay technique. The results of this study indicate the potential of water catchment areas with excellent category, good, medium, poor and very poor. These results may indicate that the Upper river basin is either good or in bad condition, so it can be used for better water resources management policy determination.

  8. An in situ spatially resolved analytical technique to simultaneously probe gas phase reactions and temperature within the packed bed of a plug flow reactor.

    Science.gov (United States)

    Touitou, Jamal; Burch, Robbie; Hardacre, Christopher; McManus, Colin; Morgan, Kevin; Sá, Jacinto; Goguet, Alexandre

    2013-05-21

    This paper reports the detailed description and validation of a fully automated, computer controlled analytical method to spatially probe the gas composition and thermal characteristics in packed bed systems. As an exemplar, we have examined a heterogeneously catalysed gas phase reaction within the bed of a powdered oxide supported metal catalyst. The design of the gas sampling and the temperature recording systems are disclosed. A stationary capillary with holes drilled in its wall and a moveable reactor coupled with a mass spectrometer are used to enable sampling and analysis. This method has been designed to limit the invasiveness of the probe on the reactor by using the smallest combination of thermocouple and capillary which can be employed practically. An 80 μm (O.D.) thermocouple has been inserted in a 250 μm (O.D.) capillary. The thermocouple is aligned with the sampling holes to enable both the gas composition and temperature profiles to be simultaneously measured at equivalent spatially resolved positions. This analysis technique has been validated by studying CO oxidation over a 1% Pt/Al2O3 catalyst and the spatial resolution profiles of chemical species concentrations and temperature as a function of the axial position within the catalyst bed are reported.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  10. Digital autoradiography technique for studying of spatial Impurity distributions Delara

    International Nuclear Information System (INIS)

    Khamrayeva, S.

    2001-01-01

    In this report, the possibilities of the digital image processing for autoradiographic investigations of impurity distributions in the different objects (crystals, biology, geology et al) are shown. Activation autoradiography based on the secondary beta-irradiation is the method spread widely for investigations of the spatial distribution of chemical elements in the different objects. The analysis of autoradiography features is connected with the elucidation of optical density distribution of photoemulsion by means of photometry. The photoemulsion is used as detector of secondary beta irradiation. For different technological and nature materials to have elemental shifts the fine structure of chemical element distribution is often interested. But photometry makes it difficult to study the inhomogeneous chemical elements with the little gradient of concentration (near 20%). Therefore, the suppression of the background and betterment of linear solvability are the main problems of autoradiographic analysis. Application of the fast-acting digital computers and the technical means of signals treatment are allowed to spread the possibilities and the resolution of activation autoradiography. Mechanism of creation of autoradiographic features is described. The treatment of autoradiograms was conducted with the help of the dialogue system having matrix in 512 x 512 elements. For the interpretation of the experimental data clustering analysis methodology was used. Classification of the zones on the minimum of the square mistake was conducted according to the data of histograms of the optical densities of the studying autoradiograms. It was proposed algorithm for digital treatment for reconstruction of autoradiographic features. At a minimal contrast the resolution of the method has been enhanced on the degree by adaptation of methods of digital image processing (DIP) to suppress background activity. Results of the digital autoradiographic investigations of spatial impurity

  11. Time dependent analysis of Xenon spatial oscillations in small power reactors

    International Nuclear Information System (INIS)

    Decco, Claudia Cristina Ghirardello

    1997-01-01

    This work presents time dependent analysis of xenon spatial oscillations studying the influence of the power density distribution, type of reactivity perturbation, power level and core size, using the one-dimensional and three-dimensional analysis with the MID2 and citation codes, respectively. It is concluded that small pressurized water reactors with height smaller than 1.5 m are stable and do not have xenon spatial oscillations. (author)

  12. Spectro-spatial analysis of wave packet propagation in nonlinear acoustic metamaterials

    Science.gov (United States)

    Zhou, W. J.; Li, X. P.; Wang, Y. S.; Chen, W. Q.; Huang, G. L.

    2018-01-01

    The objective of this work is to analyze wave packet propagation in weakly nonlinear acoustic metamaterials and reveal the interior nonlinear wave mechanism through spectro-spatial analysis. The spectro-spatial analysis is based on full-scale transient analysis of the finite system, by which dispersion curves are generated from the transmitted waves and also verified by the perturbation method (the L-P method). We found that the spectro-spatial analysis can provide detailed information about the solitary wave in short-wavelength region which cannot be captured by the L-P method. It is also found that the optical wave modes in the nonlinear metamaterial are sensitive to the parameters of the nonlinear constitutive relation. Specifically, a significant frequency shift phenomenon is found in the middle-wavelength region of the optical wave branch, which makes this frequency region behave like a band gap for transient waves. This special frequency shift is then used to design a direction-biased waveguide device, and its efficiency is shown by numerical simulations.

  13. Analysis of Surface Water Pollution in the Kinta River Using Multivariate Technique

    International Nuclear Information System (INIS)

    Hamza Ahmad Isiyaka; Hafizan Juahir

    2015-01-01

    This study aims to investigate the spatial variation in the characteristics of water quality monitoring sites, identify the most significant parameters and the major possible sources of pollution, and apportion the source category in the Kinta River. 31 parameters collected from eight monitoring sites for eight years (2006-2013) were employed. The eight monitoring stations were spatially grouped into three independent clusters in a dendrogram. A drastic reduction in the number of monitored parameters from 31 to eight and nine significant parameters (P<0.05) was achieved using the forward stepwise and backward stepwise discriminate analysis (DA). Principal component analysis (PCA) accounted for more than 76 % in the total variance and attributes the source of pollution to anthropogenic and natural processes. The source apportionment using a combined multiple linear regression and principal component scores indicates that 41 % of the total pollution load is from rock weathering and untreated waste water, 26 % from waste discharge, 24 % from surface runoff and 7 % from faecal waste. This study proposes a reduction in the number of monitoring stations and parameters for a cost effective and time management in the monitoring processes and multivariate technique can provide a simple representation of complex and dynamic water quality characteristics. (author)

  14. Assessment of tuberculosis spatial hotspot areas in Antananarivo, Madagascar, by combining spatial analysis and genotyping.

    Science.gov (United States)

    Ratovonirina, Noël Harijaona; Rakotosamimanana, Niaina; Razafimahatratra, Solohery Lalaina; Raherison, Mamy Serge; Refrégier, Guislaine; Sola, Christophe; Rakotomanana, Fanjasoa; Rasolofo Razanamparany, Voahangy

    2017-08-14

    Tuberculosis (TB) remains a public health problem in Madagascar. A crucial element of TB control is the development of an easy and rapid method for the orientation of TB control strategies in the country. Our main objective was to develop a TB spatial hotspot identification method by combining spatial analysis and TB genotyping method in Antananarivo. Sputa of new pulmonary TB cases from 20 TB diagnosis and treatment centers (DTCs) in Antananarivo were collected from August 2013 to May 2014 for culture. Mycobacterium tuberculosis complex (MTBC) clinical isolates were typed by spoligotyping on a Luminex® 200 platform. All TB patients were respectively localized according to their neighborhood residence and the spatial distribution of all pulmonary TB patients and patients with genotypic clustered isolates were scanned respectively by the Kulldorff spatial scanning method for identification of significant spatial clustering. Areas exhibiting spatial clustering of patients with genotypic clustered isolates were considered as hotspot TB areas for transmission. Overall, 467 new cases were included in the study, and 394 spoligotypes were obtained (84.4%). New TB cases were distributed in 133 of the 192 Fokontany (administrative neighborhoods) of Antananarivo (1 to 15 clinical patients per Fokontany) and patients with genotypic clustered isolates were distributed in 127 of the 192 Fokontany (1 to 13 per Fokontany). A single spatial focal point of epidemics was detected when ignoring genotypic data (p = 0.039). One Fokontany of this focal point and three additional ones were detected to be spatially clustered when taking genotypes into account (p Madagascar and will allow better TB control strategies by public health authorities.

  15. Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis.

    Science.gov (United States)

    Mustapha, Adamu; Aris, Ahmad Zaharin

    2012-01-01

    Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.

  16. Tucker Tensor analysis of Matern functions in spatial statistics

    KAUST Repository

    Litvinenko, Alexander

    2018-03-09

    In this work, we describe advanced numerical tools for working with multivariate functions and for the analysis of large data sets. These tools will drastically reduce the required computing time and the storage cost, and, therefore, will allow us to consider much larger data sets or finer meshes. Covariance matrices are crucial in spatio-temporal statistical tasks, but are often very expensive to compute and store, especially in 3D. Therefore, we approximate covariance functions by cheap surrogates in a low-rank tensor format. We apply the Tucker and canonical tensor decompositions to a family of Matern- and Slater-type functions with varying parameters and demonstrate numerically that their approximations exhibit exponentially fast convergence. We prove the exponential convergence of the Tucker and canonical approximations in tensor rank parameters. Several statistical operations are performed in this low-rank tensor format, including evaluating the conditional covariance matrix, spatially averaged estimation variance, computing a quadratic form, determinant, trace, loglikelihood, inverse, and Cholesky decomposition of a large covariance matrix. Low-rank tensor approximations reduce the computing and storage costs essentially. For example, the storage cost is reduced from an exponential O(n^d) to a linear scaling O(drn), where d is the spatial dimension, n is the number of mesh points in one direction, and r is the tensor rank. Prerequisites for applicability of the proposed techniques are the assumptions that the data, locations, and measurements lie on a tensor (axes-parallel) grid and that the covariance function depends on a distance, ||x-y||.

  17. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather.

    Science.gov (United States)

    Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

    2013-09-01

    Concurrently high values of the maximum potential wind speed of updrafts ( W max ) and 0-6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd.

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

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

    2013-10-01

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

  20. Students’ Errors in Geometry Viewed from Spatial Intelligence

    Science.gov (United States)

    Riastuti, N.; Mardiyana, M.; Pramudya, I.

    2017-09-01

    Geometry is one of the difficult materials because students must have ability to visualize, describe images, draw shapes, and know the kind of shapes. This study aim is to describe student error based on Newmans’ Error Analysis in solving geometry problems viewed from spatial intelligence. This research uses descriptive qualitative method by using purposive sampling technique. The datas in this research are the result of geometri material test and interview by the 8th graders of Junior High School in Indonesia. The results of this study show that in each category of spatial intelligence has a different type of error in solving the problem on the material geometry. Errors are mostly made by students with low spatial intelligence because they have deficiencies in visual abilities. Analysis of student error viewed from spatial intelligence is expected to help students do reflection in solving the problem of geometry.

  1. Spatial Data Analysis: Recommendations for Educational Infrastructure in Sindh

    Directory of Open Access Journals (Sweden)

    Abdul Aziz Ansari

    2017-06-01

    Full Text Available Analysing the Education infrastructure has become a crucial activity in imparting quality teaching and resources to students. Facilitations required in improving current education status and future schools is an important analytical component. This is best achieved through a Geographical Information System (GIS analysis of the spatial distribution of schools. In this work, we will execute GIS Analytics on the rural and urban school distributions in Sindh, Pakistan. Using a reliable dataset collected from an international survey team, GIS analysis is done with respect to: 1 school locations, 2 school facilities (water, sanitation, class rooms etc. and 3 student’s results. We will carry out analysis at district level by presenting several spatial results. Correlational analysis of highly influential factors, which may impact the educational performance will generate recommendations for planning and development in weak areas which will provide useful insights regarding effective utilization of resources and new locations to build future schools. The time series analysis will predict the future results which may be witnessed through keen observations and data collections.

  2. Statistical analysis of long term spatial and temporal trends of ...

    Indian Academy of Sciences (India)

    Statistical analysis of long term spatial and temporal trends of temperature ... CGCM3; HadCM3; modified Mann–Kendall test; statistical analysis; Sutlej basin. ... Water Resources Systems Division, National Institute of Hydrology, Roorkee 247 ...

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

    Science.gov (United States)

    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

  4. A spatial analysis of patterns of growth and concentration of population based on homogeneous population censuses: Spain (1877-2001

    Directory of Open Access Journals (Sweden)

    Xavier Franch Auladell

    2013-01-01

    Full Text Available This work constitutes a contribution to the analysis of long term patterns of population concentration applied to the case of Spain. The proposed methodology is based on the homogenisation of both data and administrative units which takes the municipal structure of the 2001 census as its base reference. This work seeks to show how applying spatial analysis techniques to this type of homogeneous data series allows us to make more detailed studies of population patterns within a given territory. The most important conclusions that we reached was that, in Spain, sustained population growth has followed a spatial pattern that has become increasingly consolidated over time. The tendencies observed have produced an uneven distribution of population within the national territory marked by the existence of a series of well-defined, and often very localised, areas that spread beyond the limits of the official administrative boundaries.

  5. Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

    Directory of Open Access Journals (Sweden)

    Gesche Westphal-Fitch

    Full Text Available Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

  6. Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

    Science.gov (United States)

    Westphal-Fitch, Gesche; Fitch, W Tecumseh

    2013-01-01

    Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

  7. Capacity analysis of spectrum sharing spatial multiplexing MIMO systems

    KAUST Repository

    Yang, Liang

    2014-12-01

    This paper considers a spectrum sharing (SS) multiple-input multiple-output (MIMO) system operating in a Rayleigh fading environment. First the capacity of a single-user SS spatial multiplexing system is investigated in two scenarios that assume different receivers. To explicitly show the capacity scaling law of SS MIMO systems, some approximate capacity expressions for the two scenarios are derived. Next, we extend our analysis to a multiple user system with zero-forcing receivers (ZF) under spatially-independent scheduling and analyze the sum-rate. Furthermore, we provide an asymptotic sum-rate analysis to investigate the effects of different parameters on the multiuser diversity gain. Our results show that the secondary system with a smaller number of transmit antennas Nt and a larger number of receive antennas Nr can achieve higher capacity at lower interference temperature Q, but at high Q the capacity follows the scaling law of the conventional MIMO systems. However, for a ZF SS spatial multiplexing system, the secondary system with small Nt and large Nr can achieve the highest capacity throughout the entire region of Q. For a ZF SS spatial multiplexing system with scheduling, the asymptotic sum-rate scales like Ntlog2(Q(KNtNp-1)/Nt), where Np denotes the number of antennas of the primary receiver and K represents the number of secondary transmitters.

  8. Violence in public transportation: an approach based on spatial analysis.

    Science.gov (United States)

    Sousa, Daiane Castro Bittencourt de; Pitombo, Cira Souza; Rocha, Samille Santos; Salgueiro, Ana Rita; Delgado, Juan Pedro Moreno

    2017-12-11

    To carry out a spatial analysis of the occurrence of acts of violence (specifically robberies) in public transportation, identifying the regions of greater incidence, using geostatistics, and possible causes with the aid of a multicriteria analysis in the Geographic Information System. The unit of analysis is the traffic analysis zone of the survey named Origem-Destino, carried out in Salvador, state of Bahia, in 2013. The robberies recorded by the Department of Public Security of Bahia in 2013 were located and made compatible with the limits of the traffic analysis zones and, later, associated with the respective centroids. After determining the regions with the highest probability of robbery, we carried out a geographic analysis of the possible causes in the region with the highest robbery potential, considering the factors analyzed using a multicriteria analysis in a Geographic Information System environment. The execution of the two steps of this study allowed us to identify areas corresponding to the greater probability of occurrence of robberies in public transportation. In addition, the three most vulnerable road sections (Estrada da Liberdade, Rua Pero Vaz, and Avenida General San Martin) were identified in these areas. In these sections, the factors that most contribute with the potential for robbery in buses are: F1 - proximity to places that facilitate escape, F3 - great movement of persons, and F2 - absence of policing, respectively. Indicator Kriging (geostatistical estimation) can be used to construct a spatial probability surface, which can be a useful tool for the implementation of public policies. The multicriteria analysis in the Geographic Information System environment allowed us to understand the spatial factors related to the phenomenon under analysis.

  9. GHGs and air pollutants embodied in China's international trade: Temporal and spatial index decomposition analysis.

    Science.gov (United States)

    Liu, Zhengyan; Mao, Xianqiang; Song, Peng

    2017-01-01

    Temporal index decomposition analysis and spatial index decomposition analysis were applied to understand the driving forces of the emissions embodied in China's exports and net exports during 2002-2011, respectively. The accumulated emissions embodied in exports accounted for approximately 30% of the total emissions in China; although the contribution of the sectoral total emissions intensity (technique effect) declined, the scale effect was largely responsible for the mounting emissions associated with export, and the composition effect played a largely insignificant role. Calculations of the emissions embodied in net exports suggest that China is generally in an environmentally inferior position compared with its major trade partners. The differences in the economy-wide emission intensities between China and its major trade partners were the biggest contribution to this reality, and the trade balance effect played a less important role. However, a lower degree of specialization in pollution intensive products in exports than in imports helped to reduce slightly the emissions embodied in net exports. The temporal index decomposition analysis results suggest that China should take effective measures to optimize export and supply-side structure and reduce the total emissions intensity. According to spatial index decomposition analysis, it is suggested that a more aggressive import policy was useful for curbing domestic and global emissions, and the transfer of advanced production technologies and emission control technologies from developed to developing countries should be a compulsory global environmental policy option to mitigate the possible leakage of pollution emissions caused by international trade.

  10. Bulk analysis using nuclear techniques

    International Nuclear Information System (INIS)

    Borsaru, M.; Holmes, R.J.; Mathew, P.J.

    1983-01-01

    Bulk analysis techniques developed for the mining industry are reviewed. Using penetrating neutron and #betta#-radiations, measurements are obtained directly from a large volume of sample (3-30 kg) #betta#-techniques were used to determine the grade of iron ore and to detect shale on conveyor belts. Thermal neutron irradiation was developed for the simultaneous determination of iron and aluminium in iron ore on a conveyor belt. Thermal-neutron activation analysis includes the determination of alumina in bauxite, and manganese and alumina in manganese ore. Fast neutron activation analysis is used to determine silicon in iron ores, and alumina and silica in bauxite. Fast and thermal neutron activation has been used to determine the soil in shredded sugar cane. (U.K.)

  11. Spatial Data Management

    CERN Document Server

    Mamoulis, Nikos

    2011-01-01

    Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data.

  12. Reliability analysis techniques in power plant design

    International Nuclear Information System (INIS)

    Chang, N.E.

    1981-01-01

    An overview of reliability analysis techniques is presented as applied to power plant design. The key terms, power plant performance, reliability, availability and maintainability are defined. Reliability modeling, methods of analysis and component reliability data are briefly reviewed. Application of reliability analysis techniques from a design engineering approach to improving power plant productivity is discussed. (author)

  13. Biokinematic structure of techniques wrestlers during pre-basic training

    OpenAIRE

    S.V. Sinіgovets

    2013-01-01

    The theoretical aspects of freestyle wrestlers. Experimentally investigated the structural elements of techniques during pre-basic training. The study involved 28 young fighters. Held video computer analysis techniques. Identified biomechanical characteristics defined kinematic structure of the temporal and spatial-temporal characteristics of the basic techniques. Shown variability of the individual phases of the basic techniques. Structural dynamics of the resulting velocities of the individ...

  14. Cytogenetic analysis of quinoa chromosomes using nanoscale imaging and spectroscopy techniques

    Science.gov (United States)

    Yangquanwei, Zhong; Neethirajan, Suresh; Karunakaran, Chithra

    2013-11-01

    Here we present a high-resolution chromosomal spectral map derived from synchrotron-based soft X-ray spectromicroscopy applied to quinoa species. The label-free characterization of quinoa metaphase chromosomes shows that it consists of organized substructures of DNA-protein complex. The analysis of spectra of chromosomes using the scanning transmission X-ray microscope (STXM) and its superposition of the pattern with the atomic force microscopy (AFM) and scanning electron microscopy (SEM) images proves that it is possible to precisely locate the gene loci and the DNA packaging inside the chromosomes. STXM has been successfully used to distinguish and quantify the DNA and protein components inside the quinoa chromosomes by visualizing the interphase at up to 30-nm spatial resolution. Our study represents the successful attempt of non-intrusive interrogation and integrating imaging techniques of chromosomes using synchrotron STXM and AFM techniques. The methodology developed for 3-D imaging of chromosomes with chemical specificity and temporal resolution will allow the nanoscale imaging tools to emerge from scientific research and development into broad practical applications such as gene loci tools and biomarker libraries.

  15. Spatial Planning of Rural tourism with MAPPAC technique. Case study Khur and Biabanak County, (Iran

    Directory of Open Access Journals (Sweden)

    Hassan Ali Faraji Sabokbar

    2014-12-01

    Full Text Available Reviewing the concepts of space and tourism industry, tourism is in an old, deep, unbreakable bound with spatial and physical dimensions. In this way, the lack of systematic and scientific ranking process in spatial locating of rural tourism spots and also improper distribution of infrastructures are the critical deficiencies in this field. The research intends to introduce the hidden potentials and unique capabilities of Khur and Biabanak County, Iran. And prioritize their tourism spots. So tourism planners would be able to recognize proper space distribution. First, the weights of each criterion were calculated by a pairwise comparison questionnaire of AHP method, and MAPPAC technique was used for ranking. AHP was done in Expert Choice software and MAPPAC in MS Excel. Results showed that villages such as Bayaze, Jandagh, Mehrejan, Garmeh, and Iraj which are also older have a higher rank.

  16. Assessing groundwater quality in Greece based on spatial and temporal analysis.

    Science.gov (United States)

    Dokou, Zoi; Kourgialas, Nektarios N; Karatzas, George P

    2015-12-01

    The recent industrial growth together with the urban expansion and intensive agriculture in Greece has increased groundwater contamination in many regions of the country. In order to design successful remediation strategies and protect public health, it is very important to identify those areas that are most vulnerable to groundwater contamination. In this work, an extensive contamination database from monitoring wells that cover the entire Greek territory during the last decade (2000-2008) was used in order to study the temporal and spatial distribution of groundwater contamination for the most common and serious anionic and cationic trace element pollutants (heavy metals). Spatial and temporal patterns and trends in the occurrence of groundwater contamination were also identified highlighting the regions where the higher groundwater contamination rates have been detected across the country. As a next step, representative contaminated aquifers in Greece, which were identified by the above analysis, were selected in order to analyze the specific contamination problem in more detail. To this end, geostatistical techniques (various types of kriging, co-kriging, and indicator kriging) were employed in order to map the contaminant values and the probability of exceeding critical thresholds (set as the parametric values of the contaminant of interest in each case). The resulting groundwater contamination maps could be used as a useful tool for water policy makers and water managers in order to assist the decision-making process.

  17. Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand

    Directory of Open Access Journals (Sweden)

    Tripathi Nitin K

    2009-06-01

    Full Text Available Abstract Background Diarrhea is a major public health problem in Thailand. The Ministry of Public Health, Thailand, has been trying to monitor and control this disease for many years. The methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks. Methods The objective of this study was to analyse the epidemic outbreak patterns of diarrhea in Chiang Mai province, Northern Thailand, in terms of their geographical distributions and hotspot identification. The data of patients with diarrhea at village level and the 2001–2006 population censuses were collected to achieve the objective. Spatial analysis, using geographic information systems (GIS and other methods, was used to uncover the hidden phenomena from the data. In the data analysis section, spatial statistics such as quadrant analysis (QA, nearest neighbour analysis (NNA, and spatial autocorrelation analysis (SAA, were used to identify the spatial patterns of diarrhea in Chiang Mai province. In addition, local indicators of spatial association (LISA and kernel density (KD estimation were used to detect diarrhea hotspots using data at village level. Results The hotspot maps produced by the LISA and KD techniques showed spatial trend patterns of diarrhea diffusion. Villages in the middle and northern regions revealed higher incidences. Also, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales. Conclusion Spatial analysis methods in GIS revealed the spatial patterns and hotspots of diarrhea in Chiang Mai province from the year 2001 to 2006. To implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.

  18. Nuclear analysis techniques and environmental sciences

    International Nuclear Information System (INIS)

    1997-10-01

    31 theses are collected in this book. It introduced molecular activation analysis micro-PIXE and micro-probe analysis, x-ray fluorescence analysis and accelerator mass spectrometry. The applications about these nuclear analysis techniques are presented and reviewed for environmental sciences

  19. Analysis Of Influence Of Spatial Planning On Performance Of Regional Development At Waropen District. Papua Indonesia

    Directory of Open Access Journals (Sweden)

    Suwandi

    2015-08-01

    Full Text Available The various problems in regional spatial planning in Waropen District Papua shows that the Spatial Planning RTRW of Waropen District Papua drafted in 2010 has not had a positive contribution to the settlement of spatial planning problems. This is most likely caused by the inconsistency in the spatial planning. This study tried to observe the consistency of spatial planning as well as its relation to the regional development performance. The method used to observe the consistency of the preparation of guided Spatial Planning RTRW is the analysis of comparative table followed by analysis of verbal logic. In order to determine if the preparation of Spatial Planning RTRW has already paid attention on the synergy with the surrounding regions Inter-Regional Context a map overlay was conducted followed by analysis of verbal logic. To determine the performance of the regional development a Principal Components Analysis PCA was done. The analysis results showed that inconsistencies in the spatial planning had caused a variety of problems that resulted in decreased performance of the regional development. The main problems that should receive more attention are infrastructure development growth economic growth transportation aspect and new properties.

  20. Statistical evaluation of vibration analysis techniques

    Science.gov (United States)

    Milner, G. Martin; Miller, Patrice S.

    1987-01-01

    An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

  1. Techniques and Applications of Urban Data Analysis

    KAUST Repository

    AlHalawani, Sawsan

    2016-01-01

    Digitization and characterization of urban spaces are essential components as we move to an ever-growing ’always connected’ world. Accurate analysis of such digital urban spaces has become more important as we continue to get spatial and social

  2. Spatial Analysis of Accident Spots Using Weighted Severity Index ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Spatial Analysis of Accident Spots Using Weighted Severity Index (WSI) and ... pedestrians avoiding the use of pedestrian bridges/aid even when they are available. ..... not minding an unforeseen obstruction, miscalculations and wrong break.

  3. Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

    Science.gov (United States)

    Barman, S.; Bhattacharjya, R. K.

    2017-12-01

    The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

  4. Techniques for sensitivity analysis of SYVAC results

    International Nuclear Information System (INIS)

    Prust, J.O.

    1985-05-01

    Sensitivity analysis techniques may be required to examine the sensitivity of SYVAC model predictions to the input parameter values, the subjective probability distributions assigned to the input parameters and to the relationship between dose and the probability of fatal cancers plus serious hereditary disease in the first two generations of offspring of a member of the critical group. This report mainly considers techniques for determining the sensitivity of dose and risk to the variable input parameters. The performance of a sensitivity analysis technique may be improved by decomposing the model and data into subsets for analysis, making use of existing information on sensitivity and concentrating sampling in regions the parameter space that generates high doses or risks. A number of sensitivity analysis techniques are reviewed for their application to the SYVAC model including four techniques tested in an earlier study by CAP Scientific for the SYVAC project. This report recommends the development now of a method for evaluating the derivative of dose and parameter value and extending the Kruskal-Wallis technique to test for interactions between parameters. It is also recommended that the sensitivity of the output of each sub-model of SYVAC to input parameter values should be examined. (author)

  5. Techniques involving extreme environment, nondestructive techniques, computer methods in metals research, and data analysis

    International Nuclear Information System (INIS)

    Bunshah, R.F.

    1976-01-01

    A number of different techniques which range over several different aspects of materials research are covered in this volume. They are concerned with property evaluation of 4 0 K and below, surface characterization, coating techniques, techniques for the fabrication of composite materials, computer methods, data evaluation and analysis, statistical design of experiments and non-destructive test techniques. Topics covered in this part include internal friction measurements; nondestructive testing techniques; statistical design of experiments and regression analysis in metallurgical research; and measurement of surfaces of engineering materials

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

    Science.gov (United States)

    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 ...

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

    Science.gov (United States)

    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.

  8. Reevaluation of Stratospheric Ozone Trends From SAGE II Data Using a Simultaneous Temporal and Spatial Analysis

    Science.gov (United States)

    Damadeo, R. P.; Zawodny, J. M.; Thomason, L. W.

    2014-01-01

    This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data is prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

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

    Science.gov (United States)

    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.

  10. Spatial and temporal predictions of agricultural land prices using DSM techniques.

    Science.gov (United States)

    Carré, F.; Grandgirard, D.; Diafas, I.; Reuter, H. I.; Julien, V.; Lemercier, B.

    2009-04-01

    Agricultural land prices highly impacts land accessibility to farmers and by consequence the evolution of agricultural landscapes (crop changes, land conversion to urban infrastructures…) which can turn to irreversible soil degradation. The economic value of agricultural land has been studied spatially, in every one of the 374 French Agricultural Counties, and temporally- from 1995 to 2007, by using data of the SAFER Institute. To this aim, agricultural land price was considered as a digital soil property. The spatial and temporal predictions were done using Digital Soil Mapping techniques combined with tools mainly used for studying temporal financial behaviors. For making both predictions, a first classification of the Agricultural Counties was done for the 1995-2006 periods (2007 was excluded and served as the date of prediction) using a fuzzy k-means clustering. The Agricultural Counties were then aggregated according to land price at the different times. The clustering allows for characterizing the counties by their memberships to each class centroid. The memberships were used for the spatial prediction, whereas the centroids were used for the temporal prediction. For the spatial prediction, from the 374 Agricultural counties, three fourths were used for modeling and one fourth for validating. Random sampling was done by class to ensure that all classes are represented by at least one county in the modeling and validation datasets. The prediction was done for each class by testing the relationships between the memberships and the following factors: (i) soil variable (organic matter from the French BDAT database), (ii) soil covariates (land use classes from CORINE LANDCOVER, bioclimatic zones from the WorldClim Database, landform attributes and landform classes from the SRTM, major roads and hydrographic densities from EUROSTAT, average field sizes estimated by automatic classification of remote sensed images) and (iii) socio-economic factors (population

  11. Comparative analysis of time efficiency and spatial resolution between different EIT reconstruction algorithms

    International Nuclear Information System (INIS)

    Kacarska, Marija; Loskovska, Suzana

    2002-01-01

    In this paper comparative analysis between different EIT algorithms is presented. Analysis is made for spatial and temporal resolution of obtained images by several different algorithms. Discussions consider spatial resolution dependent on data acquisition method, too. Obtained results show that conventional applied-current EIT is more powerful compared to induced-current EIT. (Author)

  12. Quantitative analysis of spatial variability of geotechnical parameters

    Science.gov (United States)

    Fang, Xing

    2018-04-01

    Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

  13. Backyard housing in Gauteng: An analysis of spatial dynamics

    African Journals Online (AJOL)

    Backyard housing in Gauteng: An analysis of spatial dynamics. Yasmin Shapurjee ... Drawing on quantitative geo-demographic data from GeoTerraImage (GTI). (2010), Knowledge .... a fundamental role in absorbing demand for low-income ...

  14. Applications of Electromigration Techniques: Applications of Electromigration Techniques in Food Analysis

    Science.gov (United States)

    Wieczorek, Piotr; Ligor, Magdalena; Buszewski, Bogusław

    Electromigration techniques, including capillary electrophoresis (CE), are widely used for separation and identification of compounds present in food products. These techniques may also be considered as alternate and complementary with respect to commonly used analytical techniques, such as high-performance liquid chromatography (HPLC), or gas chromatography (GC). Applications of CE concern the determination of high-molecular compounds, like polyphenols, including flavonoids, pigments, vitamins, food additives (preservatives, antioxidants, sweeteners, artificial pigments) are presented. Also, the method developed for the determination of proteins and peptides composed of amino acids, which are basic components of food products, are studied. Other substances such as carbohydrates, nucleic acids, biogenic amines, natural toxins, and other contaminations including pesticides and antibiotics are discussed. The possibility of CE application in food control laboratories, where analysis of the composition of food and food products are conducted, is of great importance. CE technique may be used during the control of technological processes in the food industry and for the identification of numerous compounds present in food. Due to the numerous advantages of the CE technique it is successfully used in routine food analysis.

  15. Flow analysis techniques for phosphorus: an overview.

    Science.gov (United States)

    Estela, José Manuel; Cerdà, Víctor

    2005-04-15

    A bibliographical review on the implementation and the results obtained in the use of different flow analytical techniques for the determination of phosphorus is carried out. The sources, occurrence and importance of phosphorus together with several aspects regarding the analysis and terminology used in the determination of this element are briefly described. A classification as well as a brief description of the basis, advantages and disadvantages of the different existing flow techniques, namely; segmented flow analysis (SFA), flow injection analysis (FIA), sequential injection analysis (SIA), all injection analysis (AIA), batch injection analysis (BIA), multicommutated FIA (MCFIA), multisyringe FIA (MSFIA) and multipumped FIA (MPFIA) is also carried out. The most relevant manuscripts regarding the analysis of phosphorus by means of flow techniques are herein classified according to the detection instrumental technique used with the aim to facilitate their study and obtain an overall scope. Finally, the analytical characteristics of numerous flow-methods reported in the literature are provided in the form of a table and their applicability to samples with different matrixes, namely water samples (marine, river, estuarine, waste, industrial, drinking, etc.), soils leachates, plant leaves, toothpaste, detergents, foodstuffs (wine, orange juice, milk), biological samples, sugars, fertilizer, hydroponic solutions, soils extracts and cyanobacterial biofilms are tabulated.

  16. High-spatial-resolution sub-surface imaging using a laser-based acoustic microscopy technique.

    Science.gov (United States)

    Balogun, Oluwaseyi; Cole, Garrett D; Huber, Robert; Chinn, Diane; Murray, Todd W; Spicer, James B

    2011-01-01

    Scanning acoustic microscopy techniques operating at frequencies in the gigahertz range are suitable for the elastic characterization and interior imaging of solid media with micrometer-scale spatial resolution. Acoustic wave propagation at these frequencies is strongly limited by energy losses, particularly from attenuation in the coupling media used to transmit ultrasound to a specimen, leading to a decrease in the depth in a specimen that can be interrogated. In this work, a laser-based acoustic microscopy technique is presented that uses a pulsed laser source for the generation of broadband acoustic waves and an optical interferometer for detection. The use of a 900-ps microchip pulsed laser facilitates the generation of acoustic waves with frequencies extending up to 1 GHz which allows for the resolution of micrometer-scale features in a specimen. Furthermore, the combination of optical generation and detection approaches eliminates the use of an ultrasonic coupling medium, and allows for elastic characterization and interior imaging at penetration depths on the order of several hundred micrometers. Experimental results illustrating the use of the laser-based acoustic microscopy technique for imaging micrometer-scale subsurface geometrical features in a 70-μm-thick single-crystal silicon wafer with a (100) orientation are presented.

  17. Introduction to analytical techniques of beam-target interactions and resolutions

    International Nuclear Information System (INIS)

    Ruste, J.

    1995-08-01

    For several years, new analysis and observation techniques have been developed, which have considerably improved material research. Almost all these techniques are based on the interaction of a beam of 'primary particles' (electrons, photons, ions, particles, etc) with target. Correct and appropriate use of these techniques requires a good knowledge of these interactions and their consequences (emissions of 'secondary particles', modifications of the primary beam and target, etc). The first part of this report deals with the radiation/material interactions according to the nature of the radiation and its energy. The nature and consequences of the interaction of an electromagnetic wave, a beam of electrons, ions and neutrons are examined over an extended range of energy from MeV to MeV. Certain notions such as the analysis area, spatial resolutions or limits of detection can also be defined. In the second part, some of the most important and widespread techniques of analysis and observation are compared in terms of properties and performance. In particular, there is a brief principle of the technique, nature of the data obtained, spatial resolution, and the limits of detection with today's methods permit. (author). 5 refs., 23 figs., 9 tabs

  18. Analysis of Regional Unemployment in Russia and Germany: Spatial-Econometric Approach

    Directory of Open Access Journals (Sweden)

    Elena Vyacheslavovna Semerikova

    2015-06-01

    Full Text Available The study was supported by the Government of the Russian Federation, grant No.11.G34.31.0059. This paper analyzes the regional unemployment in Russia and Germany in 2005-2010 and addresses issues of choosing the right specification of spatial-econometric models. The analysis based on data of 75 Russian and 370 German regions showed that for Germany the choice of the spatial weighting matrix has a more significant influence on the parameter estimates than for Russia. Presumably this is due to stronger linkages between regional labor markets in Germany compared to Russia. The authors also proposed an algorithm for choosing between spatial matrices and demonstrated the application of this algorithm on simulated Russian data. The authors found that 1 the deviation of the results from the true ones increases when the spatial dependence between regions is higher and 2 the matrix of inverse distances is more preferable than the boundary one for the analysis of regional unemployment in Russia (because of the lower value of the mean squared error. The authors are also planning to apply the proposed algorithm for simulated data of Germany. These results allow accounting the spatial dependence more correctly when modeling regional unemployment which is very important for making proper regional policy

  19. Extreme Precipitation Estimation with Typhoon Morakot Using Frequency and Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2011-01-01

    Full Text Available Typhoon Morakot lashed Taiwan and produced copious amounts of precipitation in 2009. From the point view of hydrological statistics, the impact of the precipitation from typhoon Morakot using a frequency analysis can be analyzed and discussed. The frequency curve, which was fitted mathematically to historical observed data, can be used to estimate the probability of exceedance for runoff events of a certain magnitude. The study integrates frequency analysis and spatial analysis to assess the effect of Typhoon Morakot event on rainfall frequency in the Gaoping River basin of southern Taiwan. First, extreme rainfall data are collected at sixteen stations for durations of 1, 3, 6, 12, and 24 hours and then an appropriate probability distribution was selected to analyze the impact of the extreme hydrological event. Spatial rainfall patterns for a return period of 200-yr with 24-hr duration with and without Typhoon Morakot are estimated. Results show that the rainfall amount is significantly different with long duration with and without the event for frequency analysis. Furthermore, spatial analysis shows that extreme rainfall for a return period of 200-yr is highly dependent on topography and is smaller in the southwest than that in the east. The results not only demonstrate the distinct effect of Typhoon Morakot on frequency analysis, but also could provide reference in future planning of hydrological engineering.

  20. TV content analysis techniques and applications

    CERN Document Server

    Kompatsiaris, Yiannis

    2012-01-01

    The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers. Leaving no stone unturned, TV Content Analysis: Techniques and Applications provides a detailed exploration of TV program analysis techniques. Leading researchers and academics from around the world supply scientifically sound treatment of recent developments across the related subject areas--including systems, architectures, algorithms,

  1. [A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

    Science.gov (United States)

    Lakes, Tobia

    2017-12-01

    In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

  2. Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

    NARCIS (Netherlands)

    Harbers, I.; Ingram, M.C.

    Mixed-methods designs, especially those where cases selected for small-N analysis (SNA) are nested within a large-N analysis (LNA), have become increasingly popular. Yet, since the LNA in this approach assumes that units are independently distributed, such designs are unable to account for spatial

  3. Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia

    Energy Technology Data Exchange (ETDEWEB)

    Carranza, Emmanuel John M.; Barritt, Sally D. [Department of Earth Systems Analysis, International Institute for Geo-information Science and Earth Observation (ITC), Enschede (Netherlands); Wibowo, Hendro; Sumintadireja, Prihadi [Laboratory of Volcanology and Geothermal, Geology Department, Institute of Technology Bandung (ITB), Bandung (Indonesia)

    2008-06-15

    Conceptual modeling and predictive mapping of potential for geothermal resources at the regional-scale in West Java are supported by analysis of the spatial distribution of geothermal prospects and thermal springs, and their spatial associations with geologic features derived from publicly available regional-scale spatial data sets. Fry analysis shows that geothermal occurrences have regional-scale spatial distributions that are related to Quaternary volcanic centers and shallow earthquake epicenters. Spatial frequency distribution analysis shows that geothermal occurrences have strong positive spatial associations with Quaternary volcanic centers, Quaternary volcanic rocks, quasi-gravity lows, and NE-, NNW-, WNW-trending faults. These geological features, with their strong positive spatial associations with geothermal occurrences, constitute spatial recognition criteria of regional-scale geothermal potential in a study area. Application of data-driven evidential belief functions in GIS-based predictive mapping of regional-scale geothermal potential resulted in delineation of high potential zones occupying 25% of West Java, which is a substantial reduction of the search area for further exploration of geothermal resources. The predicted high potential zones delineate about 53-58% of the training geothermal areas and 94% of the validated geothermal occurrences. The results of this study demonstrate the value of regional-scale geothermal potential mapping in: (a) data-poor situations, such as West Java, and (b) regions with geotectonic environments similar to the study area. (author)

  4. Non-standard spatial statistics and spatial econometrics

    CERN Document Server

    Griffith, Daniel A

    2011-01-01

    Spatial statistics and spatial econometrics are recent sprouts of the tree "spatial analysis with measurement". Still, several general themes have emerged. Exploring selected fields of possible interest is tantalizing, and this is what the authors aim here.

  5. PHOTOGRAMMETRIC TECHNIQUES FOR ROAD SURFACE ANALYSIS

    Directory of Open Access Journals (Sweden)

    V. A. Knyaz

    2016-06-01

    Full Text Available The quality and condition of a road surface is of great importance for convenience and safety of driving. So the investigations of the behaviour of road materials in laboratory conditions and monitoring of existing roads are widely fulfilled for controlling a geometric parameters and detecting defects in the road surface. Photogrammetry as accurate non-contact measuring method provides powerful means for solving different tasks in road surface reconstruction and analysis. The range of dimensions concerned in road surface analysis can have great variation from tenths of millimetre to hundreds meters and more. So a set of techniques is needed to meet all requirements of road parameters estimation. Two photogrammetric techniques for road surface analysis are presented: for accurate measuring of road pavement and for road surface reconstruction based on imagery obtained from unmanned aerial vehicle. The first technique uses photogrammetric system based on structured light for fast and accurate surface 3D reconstruction and it allows analysing the characteristics of road texture and monitoring the pavement behaviour. The second technique provides dense 3D model road suitable for road macro parameters estimation.

  6. Spatial Techniques to Visualize Acoustic Comfort along Cultural and Heritage Routes for a World Heritage City

    Directory of Open Access Journals (Sweden)

    Ni Sheng

    2015-07-01

    Full Text Available This paper proposes to visualize acoustic comfort along tourist routes. Route-based tourism is crucial to the sustainability of tourism development in historic areas. Applying the concept of route-based tourism to guide tourists rambling along cultural and heritage routes can relieve overcrowded condition at hot scenic spots and increase the overall carrying capacity of the city. However, acoustic comfort along tourist routes is rarely addressed in academic studies and decision-making. Taking Macao as an example, this paper has studied pedestrian exposure to traffic noise along the cultural and heritage routes. The study is based on a GIS-based traffic noise model system with a high spatial resolution down to individual buildings along both sides of the street. Results show that tourists suffer from excessive traffic noise at certain sites, which may have negative impact on the promotion of route-based tourism in the long run. In addition, it is found that urban growth affects urban form and street layout, which in turn affect traffic flow and acoustic comfort in urban area. The present study demonstrates spatial techniques to visualize acoustic comfort along tourist routes, and the techniques are foreseen to be used more frequently to support effective tourism planning in the future.

  7. Spatial analysis and characteristics of pig farming in Thailand.

    Science.gov (United States)

    Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

    2016-10-06

    In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed

  8. GHGs and air pollutants embodied in China's international trade: Temporal and spatial index decomposition analysis.

    Directory of Open Access Journals (Sweden)

    Zhengyan Liu

    Full Text Available Temporal index decomposition analysis and spatial index decomposition analysis were applied to understand the driving forces of the emissions embodied in China's exports and net exports during 2002-2011, respectively. The accumulated emissions embodied in exports accounted for approximately 30% of the total emissions in China; although the contribution of the sectoral total emissions intensity (technique effect declined, the scale effect was largely responsible for the mounting emissions associated with export, and the composition effect played a largely insignificant role. Calculations of the emissions embodied in net exports suggest that China is generally in an environmentally inferior position compared with its major trade partners. The differences in the economy-wide emission intensities between China and its major trade partners were the biggest contribution to this reality, and the trade balance effect played a less important role. However, a lower degree of specialization in pollution intensive products in exports than in imports helped to reduce slightly the emissions embodied in net exports. The temporal index decomposition analysis results suggest that China should take effective measures to optimize export and supply-side structure and reduce the total emissions intensity. According to spatial index decomposition analysis, it is suggested that a more aggressive import policy was useful for curbing domestic and global emissions, and the transfer of advanced production technologies and emission control technologies from developed to developing countries should be a compulsory global environmental policy option to mitigate the possible leakage of pollution emissions caused by international trade.

  9. Spatial Analysis of “Crazy Quilts”, a Class of Potentially Random Aesthetic Artefacts

    Science.gov (United States)

    Westphal-Fitch, Gesche; Fitch, W. Tecumseh

    2013-01-01

    Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. “Crazy quilts” represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures. PMID:24066095

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

    Science.gov (United States)

    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.

  11. Spatially Resolved Analysis of Bragg Selectivity

    Directory of Open Access Journals (Sweden)

    Tina Sabel

    2015-11-01

    Full Text Available This paper targets an inherent control of optical shrinkage in photosensitive polymers, contributing by means of spatially resolved analysis of volume holographic phase gratings. Point by point scanning of the local material response to the Gaussian intensity distribution of the recording beams is accomplished. Derived information on the local grating period and grating slant is evaluated by mapping of optical shrinkage in the lateral plane as well as through the depth of the layer. The influence of recording intensity, exposure duration and the material viscosity on the Bragg selectivity is investigated.

  12. High resolution or optimum resolution? Spatial analysis of the Federmesser site at Andernach, Germany

    NARCIS (Netherlands)

    Stapert, D; Street, M

    1997-01-01

    This paper discusses spatial analysis at site level. It is suggested that spatial analysis has to proceed in several levels, from global to more detailed questions, and that optimum resolution should be established when applying any quantitative methods in this field. As an example, the ring and

  13. Evaluation of Medium Spatial Resolution BRDF-Adjustment Techniques Using Multi-Angular SPOT4 (Take5) Acquisitions

    OpenAIRE

    Claverie, Martin; Vermote, Eric; Franch, Belen; He, Tao; Hagolle, Olivier; Kadiri, Mohamed; Masek, Jeff

    2015-01-01

    High-resolution sensor Surface Reflectance (SR) data are affected by surface anisotropy but are difficult to adjust because of the low temporal frequency of the acquisitions and the low angular sampling. This paper evaluates five high spatial resolution Bidirectional Reflectance Distribution Function (BRDF) adjustment techniques. The evaluation is based on the noise level of the SR Time Series (TS) corrected to a normalized geometry (nadir view, 45° sun zenith angle) extracted from the multi-...

  14. Constrained principal component analysis and related techniques

    CERN Document Server

    Takane, Yoshio

    2013-01-01

    In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? What kind of benefits are we getting from them? Addressing these questions, Constrained Principal Component Analysis and Related Techniques shows how constrained PCA (CPCA) offers a unified framework for these approaches.The book begins with four concre

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

    International Nuclear Information System (INIS)

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

    1982-05-01

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

  16. The Advantages of an Attenuated Total Internal Reflection Infrared Microspectroscopic Imaging Technique for the Analysis of Polymer Laminates.

    Science.gov (United States)

    Ling, Chen; Sommer, André J

    2015-06-01

    Until recently, the analysis of polymer laminates using infrared microspectroscopy involved the painstaking separation of individual layers by dissection or by obtaining micrometer thin cross-sections. The latter usually requires the expertise of an individual trained in microtomy and even then, the very structure of the laminate could affect the outcome of the spectral results. The recent development of attenuated total internal reflection (ATR) infrared microspectroscopy imaging has provided a new avenue for the analysis of these multilayer structures. This report compares ATR infrared microspectroscopy imaging with conventional transmission infrared microspectroscopy imaging. The results demonstrate that the ATR method offers improved spatial resolution, eliminates a variety of competing optical processes, and requires minimal sample preparation relative to transmission measurements. These advantages were illustrated using a polymer laminate consisting of 11 different layers whose thickness ranged in size from 4-20 μm. The spatial resolution achieved by using an ATR-FTIR (Fourier transform infrared spectroscopy) imaging technique was diffraction limited. Contrast in the ATR images was enhanced by principal component analysis.

  17. Spatial Modeling of Deforestation in FMU of Poigar, North Sulawesi

    OpenAIRE

    Ahmad, Afandi; Saleh, Muhammad Buce; Rusolono, Teddy

    2016-01-01

    Forest is a part of the ecosystem that provides environmental services. Deforestation may decrease forest function in an ecosystem. This study aims to build a spatial model of deforestation in a forest management unit (FMU) of Poigar. Deforestation analysis carried out by analyze the change of forest cover into non-forest cover with post classification comparison technique. Driving forces of deforestation carried out by spatial modeling using binary logistic regression models (LRM). Result of...

  18. Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

    Directory of Open Access Journals (Sweden)

    Stefanović Nebojša

    2017-01-01

    Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

  19. Data for spatial analysis of growth anomaly lesions on Montipora capitata coral colonies using 3D reconstruction techniques

    Directory of Open Access Journals (Sweden)

    John H.R. Burns

    2016-12-01

    Full Text Available Ten annotated 3D reconstructions of Montipora capitata coral colonies contain x,y,z coordinates for all growth anomaly (GA lesions affecting these corals. The 3D reconstructions are available as Virtual Reality Modeling Language (VRML files, and the GA lesions coordinates are in accompanying text files. The VRML models and GA lesion coordinates can be spatially analyzed using Matlab. Matlab scripts are provided for three spatial statistical procedures in order to assess clustering of the GA lesions across the coral colony surfaces in a 3D framework: Ripley׳s K, Moran׳s I, and the Kolmogorov–Smirnov test. Please see the research article, “Investigating the spatial distribution of Growth Anomalies affecting Montipora capitata corals in a 3-dimensional framework” (J.H.R. Burns, T. Alexandrov, E. Ovchinnikova, R.D. Gates, M. Takabayashi, 2016 [1], for further interpretation and discussion of the data.

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

    Science.gov (United States)

    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…

  1. Development of spatial data guidelines and standards: spatial data set documentation to support hydrologic analysis in the U.S. Geological Survey

    Science.gov (United States)

    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

  2. Toward the identification of communities with increased tobacco-associated cancer burden: Application of spatial modeling techniques

    Directory of Open Access Journals (Sweden)

    Noella A Dietz

    2011-01-01

    Full Text Available Introduction: Smoking-attributable risks for lung, esophageal, and head and neck (H/N cancers range from 54% to 90%. Identifying areas with higher than average cancer risk and smoking rates, then targeting those areas for intervention, is one approach to more rapidly lower the overall tobacco disease burden in a given state. Our research team used spatial modeling techniques to identify areas in Florida with higher than expected tobacco-associated cancer incidence clusters. Materials and Methods: Geocoded tobacco-associated incident cancer data from 1998 to 2002 from the Florida Cancer Data System were used. Tobacco-associated cancers included lung, esophageal, and H/N cancers. SaTScan was used to identify geographic areas that had statistically significant (P<0.10 excess age-adjusted rates of tobacco-associated cancers. The Poisson-based spatial scan statistic was used. Phi correlation coefficients were computed to examine associations among block groups with/without overlapping cancer clusters. The logistic regression was used to assess associations between county-level smoking prevalence rates and being diagnosed within versus outside a cancer cluster. Community-level smoking rates were obtained from the 2002 Florida Behavioral Risk Factor Surveillance System (BRFSS. Analyses were repeated using 2007 BRFSS to examine the consistency of associations. Results: Lung cancer clusters were geographically larger for both squamous cell and adenocarcinoma cases in Florida from 1998 to 2002, than esophageal or H/N clusters. There were very few squamous cell and adenocarcinoma esophageal cancer clusters. H/N cancer mapping showed some squamous cell and a very small amount of adenocarcinoma cancer clusters. Phi correlations were generally weak to moderate in strength. The odds of having an invasive lung cancer cluster increased by 12% per increase in the county-level smoking rate. Results were inconsistent for esophageal and H/N cancers, with some

  3. Suitability of the RGB Channels for a Pixel Manipulation in a Spatial Domain Data Hiding Techniques

    Directory of Open Access Journals (Sweden)

    Ante Poljicak

    2010-06-01

    Full Text Available The aim of this research was to determine which channel in rgb color space is the most suitable (regarding perceptibility for a pixel manipulation in a spatial domain data  hiding techniques. For this purpose three custom test targets were generated. The research also shows the behavior of two closely related colors in the ps (Print-Scan process. The results are interpreted using both a quantitative method (statistical comparison and a qualitative method (visual comparison.

  4. Spatial and temporal analysis of mass movement using dendrochronology

    NARCIS (Netherlands)

    Braam, R.R.; Weiss, E.E.J.; Burrough, P.A.

    1987-01-01

    Tree growth and inclination on sloping land is affected by mass movement. Suitable analysis of tree growth and tree form can therefore provide considerable information on mass movement activity. This paper reports a new, automated method for studying the temporal and spatial aspects of mass

  5. Analysis of Spatial Concepts, Spatial Skills and Spatial Representations in New York State Regents Earth Science Examinations

    Science.gov (United States)

    Kastens, Kim A.; Pistolesi, Linda; Passow, Michael J.

    2014-01-01

    Research has shown that spatial thinking is important in science in general, and in Earth Science in particular, and that performance on spatially demanding tasks can be fostered through instruction. Because spatial thinking is rarely taught explicitly in the U.S. education system, improving spatial thinking may be "low-hanging fruit" as…

  6. Technique for evaluation of spatial resolution and microcalcifications in digital and scanned images of a standard breast phantom

    International Nuclear Information System (INIS)

    Santana, Priscila do C.; Gomes, Danielle S.; Oliveira, Marcio A.; Oliveira, Paulo Marcio C. de; Meira-Belo, Luiz C.; Nogueira-Tavares, Maria S.

    2011-01-01

    In this work, an automated methodology to evaluate digital and scanned images of a standard phantom (Phantom Mama) was studied. The Phantom Mama was used as an important tool to check the quality of mammographs. The scanned images were digitized using a ScanMaker 9800XL, with resolution of 900 dpi. The aim of this work is to test an automatic methodology for evaluation of spatial resolution and microcalcifications group of phantom mama images acquired with the same parameters in the same equipment. In order to analyze the images we have used the ImageJ software (in Java) which is public domain. We have used the Fast Fourier transform technique to evaluate the spatial resolution and used the ImageJ function Subtract Background and the Light Background plus Sliding Paraboloid on the evaluation of the five groups of microcalcifications on the breast phantom to assess the viability of using automated methods for both types of images. The methodology was adequate for evaluated the microcalcifications group and the spatial resolution in scanned and digital images, but the Phantom Mama doesn't provide sufficient parameters to evaluate the spatial resolution in this images. (author)

  7. Hot Routes: Developing a New Technique for the Spatial Analysis of Crime

    OpenAIRE

    Tompson, L.; Partridge, H.; Shepherd, N.

    2009-01-01

    The use of hotspot mapping techniques such as KDE to represent the geographical spread of linear events can be problematic. Network-constrained data (for example transport-related crime) require a different approach to visualize concentration. We propose a methodology called Hot Routes, which measures the risk distribution of crime along a linear network by calculating the rate of crimes per section of road. This method has been designed for everyday crime analysts, and requires only a Geogra...

  8. A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making

    Directory of Open Access Journals (Sweden)

    Michael F. Goodchild

    2013-05-01

    Full Text Available Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1 widespread sharing and seamless integration of distributed geospatial data; (2 an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3 the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4 capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations.

  9. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2017-12-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  10. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2018-06-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  11. A Spatially Explicit Approach for Sensitivity and Uncertainty Analysis of GIS-Multicriteria Landslide Susceptibility Mapping. GI_Forum 2013 – Creating the GISociety|

    OpenAIRE

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2016-01-01

    GIS multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping for the prediction of future hazards, decision making, as well as hazard mitigation plans. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are prone to multiple types of uncertainty. In this paper, the spatiality explicitly method is employed to assess the uncertainty associated with two methods of GIS-MCDA namely, Analytical Hierarchi...

  12. Exploratory and spatial data analysis (EDA-SDA) for determining regional background levels and anomalies of potentially toxic elements in soils from Catorce-Matehuala, Mexico

    Science.gov (United States)

    Chiprés, J.A.; Castro-Larragoitia, J.; Monroy, M.G.

    2009-01-01

    The threshold between geochemical background and anomalies can be influenced by the methodology selected for its estimation. Environmental evaluations, particularly those conducted in mineralized areas, must consider this when trying to determinate the natural geochemical status of a study area, quantifying human impacts, or establishing soil restoration values for contaminated sites. Some methods in environmental geochemistry incorporate the premise that anomalies (natural or anthropogenic) and background data are characterized by their own probabilistic distributions. One of these methods uses exploratory data analysis (EDA) on regional geochemical data sets coupled with a geographic information system (GIS) to spatially understand the processes that influence the geochemical landscape in a technique that can be called a spatial data analysis (SDA). This EDA-SDA methodology was used to establish the regional background range from the area of Catorce-Matehuala in north-central Mexico. Probability plots of the data, particularly for those areas affected by human activities, show that the regional geochemical background population is composed of smaller subpopulations associated with factors such as soil type and parent material. This paper demonstrates that the EDA-SDA method offers more certainty in defining thresholds between geochemical background and anomaly than a numeric technique, making it a useful tool for regional geochemical landscape analysis and environmental geochemistry studies.

  13. Digital Elevation Profile: A Complex Tool for the Spatial Analysis of Hiking

    Directory of Open Access Journals (Sweden)

    Laura TÎRLĂ

    2014-11-01

    Full Text Available One of the current attributions of mountain geomorphology is to provide information for tourism purposes, such as the spatial analysis of hiking trails. Therefore, geomorphic tools are indispensable for terrain analyses. Elevation profile is one of the most adequate tools for assessing the morphometric patterns of the hiking trails. In this study we tested several applications in order to manage raw data, create profile graphs and obtain the morphometric parameters of five hiking trails in the Căpățânii Mountains (South Carpathians, Romania. Different data complexity was explored: distance, elevation, cumulative gain or loss, slope etc. Furthermore, a comparative morphometric analysis was performed in order to emphasize the multiple possibilities provided by the elevation profile. Results show that GPS Visualizer, Geocontext and in some manner Google Earth are the most adequate applications that provide high-quality elevation profiles and detailed data, with multiple additional functions, according to user's needs. The applied tools and techniques are very useful for mountain route planning, elaborating mountain guides, enhancing knowledge about specific trails or routes, or assessing the landscape and tourism value of a mountain area.

  14. Positive Analysis of Invasive Species Control as a Dynamic Spatial Process

    OpenAIRE

    Buyuktahtakin, Esra; Feng, Zhuo; Olsson, Aaryn; Frisvold, George B.; Szidarovszky, Ferenc

    2010-01-01

    This paper models control of invasive buffelgrass (Pennisetum ciliare), a fire-prone African bunchgrass spreading rapidly across the southern Arizona desert as a spatial dynamic process. Buffelgrass spreads over a gridded landscape. Weed carrying capacity, treatment costs, and damages vary over grid cells. Damage from buffelgrass depends on its spatial distribution in relation to valued resources. We conduct positive analysis of recommended heuristic strategies for buffelgrass control, evalua...

  15. A new technique for the assessment of the 3D spatial distribution of the calcium/phosphorus ratio in bone apatite.

    Science.gov (United States)

    Hadjipanteli, A; Kourkoumelis, N; Fromme, P; Olivo, A; Huang, J; Speller, R

    2013-11-01

    The value and distribution of calcium/phosphorus (Ca/P) ratio in bone vary between healthy and osteoporotic bone. The purpose of this study was the development of a technique for the assessment of the 3D spatial distribution of Ca/P ratio in bone apatite, which could eventually be implemented through a conventional computed tomography (CT) system. A three-material mass-fraction decomposition CT dual energy analysis was optimized. The technique was validated using ten bone phantoms of different, known Ca/P ratio. Their measured average Ca/P ratio showed a mean/maximum deviation from the expected Ca/P ratio of 0.24/0.35. Additionally, three healthy and three inflammation-mediated osteoporotic (IMO) collagen-free rabbit tibia bone samples were assessed, providing promising preliminary results on real bone tissue. The average Ca/P ratios in all IMO samples (1.64-1.65) were found to be lower than in healthy samples (1.67-1.68). Osteoporotic regions in IMO samples were located using Ca/P ratio colour maps and Ca/P ratio values as low as 1.40 ± 0.26 were found. The low Ca/P ratio volume proportion in IMO samples (12.8%-13.9%) was found to be higher than in healthy (5.8%-8.3%) samples. A region growing technique showed a higher homogeneity of Ca/P ratio in healthy than in IMO bone samples.

  16. New understanding of rhizosphere processes enabled by advances in molecular and spatially resolved techniques

    Energy Technology Data Exchange (ETDEWEB)

    Hess, Nancy J.; Paša-Tolić, Ljiljana; Bailey, Vanessa L.; Dohnalkova, Alice C.

    2017-06-01

    Understanding the role played by microorganisms within soil systems is challenged by the unique intersection of physics, chemistry, mineralogy and biology in fostering habitat for soil microbial communities. To address these challenges will require observations across multiple spatial and temporal scales to capture the dynamics and emergent behavior from complex and interdependent processes. The heterogeneity and complexity of the rhizosphere require advanced techniques that press the simultaneous frontiers of spatial resolution, analyte sensitivity and specificity, reproducibility, large dynamic range, and high throughput. Fortunately many exciting technical advancements are now available to inform and guide the development of new hypotheses. The aim of this Special issue is to provide a holistic view of the rhizosphere in the perspective of modern molecular biology methodologies that enabled a highly-focused, detailed view on the processes in the rhizosphere, including numerous, strong and complex interactions between plant roots, soil constituents and microorganisms. We discuss the current rhizosphere research challenges and knowledge gaps, as well as perspectives and approaches using newly available state-of-the-art toolboxes. These new approaches and methodologies allow the study of rhizosphere processes and properties, and rhizosphere as a central component of ecosystems and biogeochemical cycles.

  17. GHGs and air pollutants embodied in China’s international trade: Temporal and spatial index decomposition analysis

    Science.gov (United States)

    Liu, Zhengyan; Mao, Xianqiang; Song, Peng

    2017-01-01

    Temporal index decomposition analysis and spatial index decomposition analysis were applied to understand the driving forces of the emissions embodied in China’s exports and net exports during 2002–2011, respectively. The accumulated emissions embodied in exports accounted for approximately 30% of the total emissions in China; although the contribution of the sectoral total emissions intensity (technique effect) declined, the scale effect was largely responsible for the mounting emissions associated with export, and the composition effect played a largely insignificant role. Calculations of the emissions embodied in net exports suggest that China is generally in an environmentally inferior position compared with its major trade partners. The differences in the economy-wide emission intensities between China and its major trade partners were the biggest contribution to this reality, and the trade balance effect played a less important role. However, a lower degree of specialization in pollution intensive products in exports than in imports helped to reduce slightly the emissions embodied in net exports. The temporal index decomposition analysis results suggest that China should take effective measures to optimize export and supply-side structure and reduce the total emissions intensity. According to spatial index decomposition analysis, it is suggested that a more aggressive import policy was useful for curbing domestic and global emissions, and the transfer of advanced production technologies and emission control technologies from developed to developing countries should be a compulsory global environmental policy option to mitigate the possible leakage of pollution emissions caused by international trade. PMID:28441399

  18. Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

    Science.gov (United States)

    Moharana, S.; Dutta, S.

    2015-12-01

    Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was

  19. Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

    Science.gov (United States)

    Rupa, Chandra; Mujumdar, Pradeep

    2016-04-01

    In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings

  20. The Structure of Spatial Ability Items: A Faceted Analysis.

    Science.gov (United States)

    Guttman, Ruth; Shoham, Ilana

    1982-01-01

    Eight spatial tests assembled with a mapping sentence of four content facets (rule type, dimensionality, presence or absence of rotation, and test format) were administered to 800 individuals. Smallest Space Analysis of an intercorrelation matrix yielded three facets which formed distinct regions in a two-dimensional projection of a…

  1. Gold analysis by the gamma absorption technique

    International Nuclear Information System (INIS)

    Kurtoglu, Arzu; Tugrul, A.B.

    2003-01-01

    Gold (Au) analyses are generally performed using destructive techniques. In this study, the Gamma Absorption Technique has been employed for gold analysis. A series of different gold alloys of known gold content were analysed and a calibration curve was obtained. This curve was then used for the analysis of unknown samples. Gold analyses can be made non-destructively, easily and quickly by the gamma absorption technique. The mass attenuation coefficients of the alloys were measured around the K-shell absorption edge of Au. Theoretical mass attenuation coefficient values were obtained using the WinXCom program and comparison of the experimental results with the theoretical values showed generally good and acceptable agreement

  2. INTERNAL ENVIRONMENT ANALYSIS TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Caescu Stefan Claudiu

    2011-12-01

    Full Text Available Theme The situation analysis, as a separate component of the strategic planning, involves collecting and analysing relevant types of information on the components of the marketing environment and their evolution on the one hand and also on the organization’s resources and capabilities on the other. Objectives of the Research The main purpose of the study of the analysis techniques of the internal environment is to provide insight on those aspects that are of strategic importance to the organization. Literature Review The marketing environment consists of two distinct components, the internal environment that is made from specific variables within the organization and the external environment that is made from variables external to the organization. Although analysing the external environment is essential for corporate success, it is not enough unless it is backed by a detailed analysis of the internal environment of the organization. The internal environment includes all elements that are endogenous to the organization, which are influenced to a great extent and totally controlled by it. The study of the internal environment must answer all resource related questions, solve all resource management issues and represents the first step in drawing up the marketing strategy. Research Methodology The present paper accomplished a documentary study of the main techniques used for the analysis of the internal environment. Results The special literature emphasizes that the differences in performance from one organization to another is primarily dependant not on the differences between the fields of activity, but especially on the differences between the resources and capabilities and the ways these are capitalized on. The main methods of analysing the internal environment addressed in this paper are: the analysis of the organizational resources, the performance analysis, the value chain analysis and the functional analysis. Implications Basically such

  3. Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy

    Directory of Open Access Journals (Sweden)

    Donato Sollitto

    2012-03-01

    Full Text Available Salinization is one of the most serious problems confronting sustainable agriculture in semi-arid and arid regions. Accurate mapping of soil salinization and the associated risk represent a fundamental step in planning agricultural and remediation activities. Geostatistical analysis is very useful for soil quality assessment because it makes it possible to determine the spatial relationships between selected variables and to produce synthetic maps of spatial variation. The main objective of this paper was to map the soil salinization risk in the Delia-Nivolelli alluvial basin (south-western Sicily, southern Italy, using multivariate geostatistical techniques and a set of topographical, physical and soil hydraulic properties. Elevation data were collected from existing topographic maps and analysed preliminarily to improve the estimate precision of sparsely sampled primary variables. For interpolation multi-collocated cokriging was applied to the dataset, including textural and hydraulic properties and electrical conductivity measurements carried out on 128 collected soil samples, using elevation data as auxiliary variable. Spatial dependence among elevation and physical soil properties was explored with factorial kriging analysis (FKA that could isolate and display the sources of variation acting at different spatial scales. FKA isolated significant regionalised factors which give a concise description of the complex soil physical variability at the different selected spatial scales. These factors mapped, allowed the delineation of zones at different salinisation risk to be managed separately to control and prevent salinization risk. The proposed methodology could be a valid support for land use and soil remediation planning at regional scale.

  4. Spatial Analysis of Depots for Advanced Biomass Processing

    Energy Technology Data Exchange (ETDEWEB)

    Hilliard, Michael R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brandt, Craig C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Webb, Erin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sokhansanj, Shahabaddine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Eaton, Laurence M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Martinez Gonzalez, Maria I. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2014-09-01

    The objective of this work was to perform a spatial analysis of the total feedstock cost at the conversion reactor for biomass supplied by a conventional system and an advanced system with depots to densify biomass into pellets. From these cost estimates, the conditions (feedstock cost and availability) for which advanced processing depots make it possible to achieve cost and volume targets can be identified.

  5. Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012

    Directory of Open Access Journals (Sweden)

    Silvia Carvalho

    2017-08-01

    Full Text Available ABSTRACT OBJECTIVE Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. METHODS Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields “street” and “number” were used. The ArcGis10 program’s Geocoding tool’s automatic process was performed. The spatial analysis was done through the kernel density estimator. RESULTS Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. CONCLUSIONS The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies.

  6. Evidence for fish dispersal from spatial analysis of stream network topology

    Science.gov (United States)

    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.

  7. Geoscience after ITPart G. Familiarization with spatial analysis

    Science.gov (United States)

    Pundt, Hardy; Brinkkötter-Runde, Klaus

    2000-04-01

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

  8. Development of spatial scaling technique of forest health sample point information

    Science.gov (United States)

    Lee, J.; Ryu, J.; Choi, Y. Y.; Chung, H. I.; Kim, S. H.; Jeon, S. W.

    2017-12-01

    Most forest health assessments are limited to monitoring sampling sites. The monitoring of forest health in Britain in Britain was carried out mainly on five species (Norway spruce, Sitka spruce, Scots pine, Oak, Beech) Database construction using Oracle database program with density The Forest Health Assessment in GreatBay in the United States was conducted to identify the characteristics of the ecosystem populations of each area based on the evaluation of forest health by tree species, diameter at breast height, water pipe and density in summer and fall of 200. In the case of Korea, in the first evaluation report on forest health vitality, 1000 sample points were placed in the forests using a systematic method of arranging forests at 4Km × 4Km at regular intervals based on an sample point, and 29 items in four categories such as tree health, vegetation, soil, and atmosphere. As mentioned above, existing researches have been done through the monitoring of the survey sample points, and it is difficult to collect information to support customized policies for the regional survey sites. In the case of special forests such as urban forests and major forests, policy and management appropriate to the forest characteristics are needed. Therefore, it is necessary to expand the survey headquarters for diagnosis and evaluation of customized forest health. For this reason, we have constructed a method of spatial scale through the spatial interpolation according to the characteristics of each index of the main sample point table of 29 index in the four points of diagnosis and evaluation report of the first forest health vitality report, PCA statistical analysis and correlative analysis are conducted to construct the indicators with significance, and then weights are selected for each index, and evaluation of forest health is conducted through statistical grading.

  9. Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.

    Science.gov (United States)

    Sarker, M Mizanur Rahman

    2012-04-01

    Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Applications of neutron activation analysis technique

    International Nuclear Information System (INIS)

    Jonah, S. A.

    2000-07-01

    The technique was developed as far back as 1936 by G. Hevesy and H. Levy for the analysis of Dy using an isotopic source. Approximately 40 elements can be analyzed by instrumental neutron activation analysis (INNA) technique with neutrons from a nuclear reactor. By applying radiochemical separation, the number of elements that can be analysed may be increased to almost 70. Compared with other analytical methods used in environmental and industrial research, NAA has some unique features. These are multi-element capability, rapidity, reproducibility of results, complementarity to other methods, freedom from analytical blank and independency of chemical state of elements. There are several types of neutron sources namely: nuclear reactors, accelerator-based and radioisotope-based sources, but nuclear reactors with high fluxes of neutrons from the fission of 235 U give the most intense irradiation, and hence the highest available sensitivities for NAA. In this paper, the applications of NAA of socio-economic importance are discussed. The benefits of using NAA and related nuclear techniques for on-line applications in industrial process control are highlighted. A brief description of the NAA set-ups at CERT is enumerated. Finally, NAA is compared with other leading analytical techniques

  11. Elemental analysis techniques using proton microbeam

    International Nuclear Information System (INIS)

    Sakai, Takuro; Oikawa, Masakazu; Sato, Takahiro

    2005-01-01

    Proton microbeam is a powerful tool for two-dimensional elemental analysis. The analysis is based on Particle Induced X-ray Emission (PIXE) and Particle Induced Gamma-ray Emission (PIGE) techniques. The paper outlines the principles and instruments, and describes the dental application has been done in JAERI Takasaki. (author)

  12. Spatial correlation analysis of urban traffic state under a perspective of community detection

    Science.gov (United States)

    Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

    2018-05-01

    Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

  13. A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

    Science.gov (United States)

    Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

    2013-04-15

    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. 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. 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". 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 sites through time to track spatio

  14. Development of evaluation method for software safety analysis techniques

    International Nuclear Information System (INIS)

    Huang, H.; Tu, W.; Shih, C.; Chen, C.; Yang, W.; Yih, S.; Kuo, C.; Chen, M.

    2006-01-01

    Full text: Full text: Following the massive adoption of digital Instrumentation and Control (I and C) system for nuclear power plant (NPP), various Software Safety Analysis (SSA) techniques are used to evaluate the NPP safety for adopting appropriate digital I and C system, and then to reduce risk to acceptable level. However, each technique has its specific advantage and disadvantage. If the two or more techniques can be complementarily incorporated, the SSA combination would be more acceptable. As a result, if proper evaluation criteria are available, the analyst can then choose appropriate technique combination to perform analysis on the basis of resources. This research evaluated the applicable software safety analysis techniques nowadays, such as, Preliminary Hazard Analysis (PHA), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Markov chain modeling, Dynamic Flowgraph Methodology (DFM), and simulation-based model analysis; and then determined indexes in view of their characteristics, which include dynamic capability, completeness, achievability, detail, signal/ noise ratio, complexity, and implementation cost. These indexes may help the decision makers and the software safety analysts to choose the best SSA combination arrange their own software safety plan. By this proposed method, the analysts can evaluate various SSA combinations for specific purpose. According to the case study results, the traditional PHA + FMEA + FTA (with failure rate) + Markov chain modeling (without transfer rate) combination is not competitive due to the dilemma for obtaining acceptable software failure rates. However, the systematic architecture of FTA and Markov chain modeling is still valuable for realizing the software fault structure. The system centric techniques, such as DFM and Simulation-based model analysis, show the advantage on dynamic capability, achievability, detail, signal/noise ratio. However, their disadvantage are the completeness complexity

  15. Analysis of archaeological pieces with nuclear techniques

    International Nuclear Information System (INIS)

    Tenorio, D.

    2002-01-01

    In this work nuclear techniques such as Neutron Activation Analysis, PIXE, X-ray fluorescence analysis, Metallography, Uranium series, Rutherford Backscattering for using in analysis of archaeological specimens and materials are described. Also some published works and thesis about analysis of different Mexican and Meso american archaeological sites are referred. (Author)

  16. Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

    Science.gov (United States)

    Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

    1982-01-01

    Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

  17. Spatially-Heterodyned Holography

    Science.gov (United States)

    Thomas, Clarence E [Knoxville, TN; Hanson, Gregory R [Clinton, TN

    2006-02-21

    A method of recording a spatially low-frequency heterodyne hologram, including spatially heterodyne fringes for Fourier analysis, includes: splitting a laser beam into a reference beam and an object beam; interacting the object beam with an object; focusing the reference beam and the object beam at a focal plane of a digital recorder to form a spatially low-frequency heterodyne hologram including spatially heterodyne fringes for Fourier analysis; digital recording the spatially low-frequency heterodyne hologram; Fourier transforming axes of the recorded spatially low-frequency heterodyne hologram including spatially heterodyne fringes in Fourier space to sit on top of a heterodyne carrier frequency defined by an angle between the reference beam and the object beam; cutting off signals around an origin; and performing an inverse Fourier transform.

  18. Regionalizing Aquatic Ecosystems Based on the River Subbasin Taxonomy Concept and Spatial Clustering Techniques

    Directory of Open Access Journals (Sweden)

    Jiahu Zhao

    2011-11-01

    Full Text Available Aquatic ecoregions were increasingly used as spatial units for aquatic ecosystem management at the watershed scale. In this paper, the principle of including land area, comprehensiveness and dominance, conjugation and hierarchy were selected as regionalizing principles. Elevation and drainage density were selected as the regionalizing indicators for the delineation of level I aquatic ecoregions, and percent of construction land area, percent of cultivated land area, soil type and slope for the level II. Under the support of GIS technology, the spatial distribution maps of the two indicators for level I and the four indicators for level II aquatic ecoregion delineation were generated from the raster data based on the 1,107 subwatersheds. River subbasin taxonomy concept, two-step spatial clustering analysis approach and manual-assisted method were used to regionalize aquatic ecosystems in the Taihu Lake watershed. Then the Taihu Lake watershed was divided into two level I aquatic ecoregions, including Ecoregion I1 and Ecoregion I2, and five level II aquatic subecoregions, including Subecoregion II11, Subecoregion II12, Subecoregion II21, Subecoregion II22 and Subecoregion II23. Moreover, the characteristics of the two level I aquatic ecoregions and five level II aquatic subecoregions in the Taihu Lake watershed were summarized, showing that there were significant differences in topography, socio-economic development, water quality and aquatic ecology, etc. The results of quantitative comparison of aquatic life also indicated that the dominant species of fish, benthic density, biomass, dominant species, Shannon-Wiener diversity index, Margalef species richness index, Pielou evenness index and ecological dominance showed great spatial variability between the two level I aquatic ecoregions and five level II aquatic subecoregions. It reflected the spatial heterogeneities and the uneven natures of aquatic ecosystems in the Taihu Lake watershed.

  19. Spatial analysis of the Rio de Janeiro metropolitan area and social and environmental management issues

    DEFF Research Database (Denmark)

    Ribeiro, Gustavo

    2005-01-01

    and infrastructural data. Through these three levels of spatial analysis it is possible to develop and to support a more comprehensible study of urban development of the Rio de Janeiro Metropolitan Area. The aim of this study is (a) to develop an alternative spatial analysis leading to a more comprehensive...... understanding of the urban development process and its correlation not just with political-administrative borders but also to ecological systems: (b) to identify the correlations between infrastructure and socio-economical data in the Rio de Janeiro Metropolitan Area (c) to evaluate urban development dynamics...... in the period between 1990 and 2000, based on the application of the above-mentioned data to the three spatial levels in question. This paper highlights the role of the hydrographical systems of the Rio de Janeiro Metropolitan Area as an important spatial unit of analysis to understand the metropolitan urban...

  20. Explorative analysis of long time series of very high resolution spatial rainfall

    DEFF Research Database (Denmark)

    Thomassen, Emma Dybro; Sørup, Hjalte Jomo Danielsen; Scheibel, Marc

    2017-01-01

    . For each method a set of 17 variables are used to describe the properties of each event, e.g. duration, maximum volumes, spatial coverage and heterogeneity, and movement of cells. A total of 5-9 dimensions can be found in the data, which can be interpreted as a rough indication of how many independent...... simple scaling across the set of variables, i.e. the level of each variable varies signicantly, but not the overall structure of the spatial precipitation. The analysis show that there is a good potential for making a spatial weather generator for high spatio-temporal precipitation for precipitation...

  1. Spatial distribution of enzyme activities in the rhizosphere

    Science.gov (United States)

    Razavi, Bahar S.; Zarebanadkouki, Mohsen; Blagodatskaya, Evgenia; Kuzyakov, Yakov

    2015-04-01

    The rhizosphere, the tiny zone of soil surrounding roots, certainly represents one of the most dynamic habitat and interfaces on Earth. Activities of enzymes produced by both plant roots and microbes are the primary biological drivers of organic matter decomposition and nutrient cycling. That is why there is an urgent need in spatially explicit methods for the determination of the rhizosphere extension and enzyme distribution. Recently, zymography as a new technique based on diffusion of enzymes through the 1 mm gel plate for analysis has been introduced (Spohn & Kuzyakov, 2013). We developed the zymography technique to visualize the enzyme activities with a higher spatial resolution. For the first time, we aimed at quantitative imaging of enzyme activities as a function of distance from the root tip and the root surface in the soil. We visualized the two dimensional distribution of the activity of three enzymes: β-glucosidase, phosphatase and leucine amino peptidase in the rhizosphere of maize using fluorogenically labelled substrates. Spatial-resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. The newly-developed direct zymography visualized heterogeneity of enzyme activities along the roots. The activity of all enzymes was the highest at the apical parts of individual roots. Across the roots, the enzyme activities were higher at immediate vicinity of the roots (1.5 mm) and gradually decreased towards the bulk soil. Spatial patterns of enzyme activities as a function of distance from the root surface were enzyme specific, with highest extension for phosphatase. We conclude that improved zymography is promising in situ technique to analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere hotspots. References Spohn, M., Kuzyakov, Y., 2013. Phosphorus mineralization can be driven by microbial need for carbon. Soil Biology & Biochemistry 61: 69-75

  2. Spatial mode discrimination using second harmonic generation

    DEFF Research Database (Denmark)

    Delaubert, Vincent; Lassen, Mikael Østergaard; Pulford, David

    2007-01-01

    Second harmonic generation can be used as a technique for controlling the spatial mode structure of optical beams. We demonstrate experimentally the generation of higher order spatial modes, and that it is possible to use nonlinear phase matching as a predictable and robust technique for the conv...

  3. SRXRF analysis with spatial resolution of dental calculus

    International Nuclear Information System (INIS)

    Sanchez, Hector Jorge; Perez, Carlos Alberto; Grenon, Miriam

    2000-01-01

    This work presents elemental-composition studies of dental calculus by X-ray fluorescence analysis using synchrotron radiation. The intrinsic characteristics of synchrotron light allow for a semi-quantitative analysis with spatial resolution. The experiments were carried out in the high-vacuum station of the XRF beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). All the measurements were performed in conventional geometry (45 deg. + 45 deg.) and the micro-collimation was attained via a pair of orthogonal slits mounted in the beamline. In this way, pixels of 50 μmx50 μm were obtained keeping a high flux of photons on the sample. Samples of human dental calculus were measured in different positions along their growing axis, in order to determine variations of the compositions in the pattern of deposit. Intensity ratios of minor elements and traces were obtained, and linear profiles and surface distributions were determined. As a general summary, we can conclude that μXRF experiments with spatial resolution on dental calculus are feasible with simple collimation and adequate positioning systems, keeping a high flux of photon. These results open interesting perspectives for the future station of the line, devoted to μXRF, which will reach resolutions of the order of 10 μm

  4. SRXRF analysis with spatial resolution of dental calculus

    Science.gov (United States)

    Sánchez, Héctor Jorge; Pérez, Carlos Alberto; Grenón, Miriam

    2000-09-01

    This work presents elemental-composition studies of dental calculus by X-ray fluorescence analysis using synchrotron radiation. The intrinsic characteristics of synchrotron light allow for a semi-quantitative analysis with spatial resolution. The experiments were carried out in the high-vacuum station of the XRF beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). All the measurements were performed in conventional geometry (45°+45°) and the micro-collimation was attained via a pair of orthogonal slits mounted in the beamline. In this way, pixels of 50 μm×50 μm were obtained keeping a high flux of photons on the sample. Samples of human dental calculus were measured in different positions along their growing axis, in order to determine variations of the compositions in the pattern of deposit. Intensity ratios of minor elements and traces were obtained, and linear profiles and surface distributions were determined. As a general summary, we can conclude that μXRF experiments with spatial resolution on dental calculus are feasible with simple collimation and adequate positioning systems, keeping a high flux of photon. These results open interesting perspectives for the future station of the line, devoted to μXRF, which will reach resolutions of the order of 10 μm.

  5. Advanced Techniques of Stress Analysis

    Directory of Open Access Journals (Sweden)

    Simion TATARU

    2013-12-01

    Full Text Available This article aims to check the stress analysis technique based on 3D models also making a comparison with the traditional technique which utilizes a model built directly into the stress analysis program. This comparison of the two methods will be made with reference to the rear fuselage of IAR-99 aircraft, structure with a high degree of complexity which allows a meaningful evaluation of both approaches. Three updated databases are envisaged: the database having the idealized model obtained using ANSYS and working directly on documentation, without automatic generation of nodes and elements (with few exceptions, the rear fuselage database (performed at this stage obtained with Pro/ ENGINEER and the one obtained by using ANSYS with the second database. Then, each of the three databases will be used according to arising necessities.The main objective is to develop the parameterized model of the rear fuselage using the computer aided design software Pro/ ENGINEER. A review of research regarding the use of virtual reality with the interactive analysis performed by the finite element method is made to show the state- of- the-art achieved in this field.

  6. Spectral analysis and compositing techniques for the Near Earth Asteroid Rendezvous (NEAR Shoemaker), X-ray and Gamma-Ray Spectrometers (XGRS)

    CERN Document Server

    McClanahan, T P; Nittler, L R; Boynton, W V; Bruckner, J; Squyres, S W; Evans, L G; Bhangoo, J S; Clark, P E; Floyd, S R; McCartney, E; Mikheeva, I; Starr, R D

    2001-01-01

    An X-ray and Gamma-Ray Spectrometer (XGRS) is on board the Near Earth Asteroid Rendezvous (NEAR) spacecraft to determine the elemental composition of the surface of the asteroid 433 Eros. The Eros asteroid is highly oblate and irregular in shape. As a result, analysis methodologies are in many ways a divergence from comparable techniques. Complex temporal, spatial and instrument performance relationships must be accounted for during the analysis process. Field of view and asteroid surface geometry measurements must be modeled and then combined with real measurements of solar, spectral and instrument calibration information to derive scientific results. NEAR is currently orbiting 433 Eros and is in the initial phases of its primary data integration and mapping phases. Initial results have been obtained and bulk chemistry assessments have been obtained through specialized background assessment and data reduction techniques.

  7. Spatial channel theory: A technique for determining the directional flow of radiation through reactor systems

    International Nuclear Information System (INIS)

    Williams, M.L.; Engle, W.W.

    1977-01-01

    A method is introduced for determining streaming paths through a non-multiplying medium. The concepts of a ''response continuum'' and a pseudo-particle called a contribution are developed to describe the spatial channels through which response flows from a source to a detector. An example application of channel theory to complex shield analysis is cited

  8. Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

    Science.gov (United States)

    Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

    2008-11-07

    SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

  9. Spatial pattern of Amazonian timber species using cartesian and spatial coordinates method

    Directory of Open Access Journals (Sweden)

    Tiago Monteiro Condé

    2016-06-01

    Full Text Available Geographic information system (GIS applied to forest analysis permit the recognition and analysis of spatial patterns of species in two and three dimensional. The aim of this study to demonstrate the efficiency of cartesian and spatial coordinates method (MCCE, method of correcting UTM coordinates of trees location in accordance with the location of field or Cartesian (X ,Y, combined with natural neighbor index (ANND in recognition and analysis of spatial distribution patterns of four commercial timber species in forest management in Caracaraí, Roraima State, Brazil. Simulations were performed on 9 ha, divided into 100 plots of 100 m2 each. Collected data were DBH > 10 cm, commercial and total heights, cartesian coordinates (X,Y and spatial coordinates (UTM. Random spatial patterns were observed in Eschweilera bracteosa and Manilkara huberi. The dispersed and rare spatial patterns were observed in Dinizia excelsa and Cedrelinga cateniformis. MCCE proved to be an efficient method in the recognition and analysis of spatial patterns of native species from Amazon rain forest, as forest planning becomes easier by 2D and 3D simulations.

  10. Spatial Analysis of Political Capital Citation Using Remote Sensing ...

    African Journals Online (AJOL)

    Spatial Analysis of Political Capital Citation Using Remote Sensing and GIS; A Case Study of Lokoja. ... The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader). If you would like more information about how to print, save, ...

  11. Chemical imaging techniques for the analysis of complex mixtures: New application to the characterization of ritual matters on African wooden statuettes

    International Nuclear Information System (INIS)

    Mazel, Vincent; Richardin, Pascale; Touboul, David; Brunelle, Alain; Walter, Philippe; Laprevote, Olivier

    2006-01-01

    Chemical imaging techniques, based on the combination of microscopy and spectroscopy, are well suited to study both the composition and the spatial organization of heterogeneous complex mixtures of organic and mineral matter. Time-of-flight secondary ion mass spectrometry (ToF-SIMS), followed by scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX) and Fourier transform infrared microscopy (FTIR microscopy) have been applied to non-destructive analysis of micro-samplings of ritual matters deposited on the surface of African wooden statuettes. With a very careful preparation, using ultramicrotomy on embedded samples, it was possible to perform successively all the measurements on a single fragment. Comparison and superposition of the different chemical images, obtained on a sample from a significant actual artefact, have allowed us to identify minerals (clays, quartz and calcium carbonate), proteins, starch, urate salts and lipids and to map their spatial distribution

  12. TEMPORAL AND SPATIAL ANALYSIS OF EXTREME RAINFALL ON THE SLOPE AREA OF MT. MERAPI

    Directory of Open Access Journals (Sweden)

    Dhian Dharma Prayuda

    2015-02-01

    Full Text Available Rainfall has temporal and spatial characteristics with certain pattern which are affected by topographic variations and climatology of an area. The intensity of extreme rainfall is one of important characteristics related to the trigger factors for debris flow. This research will discuss the result of analysis on short duration rainfall data in the south and west slope of Mt. Merapi. Measured hourly rainfall data in 14 rainfall stations for the last 27 years were used as analysis input. The rainfall intensity-duration-frequency relationship (IDF was derived using empirical formula of Sherman, Kimijima, Haspers, and Mononobe method. The analysis on the characteristics of extreme rainfall intensity was performed by conducting spatial interpolation using Inverse Distance Weighted (IDW method. Result of analysis shows that IDF of rainfall in the research area fits to Sherman’s formula. Besides, the spatial distribution pattern of maximum rainfall intensity was assessed on the basis of area rainfall. Furthermore, the difference on the result of spatial map for one hour extreme rainfall based on isolated event and non-isolated event method can be evaluated. The result of this preliminary research is expected to be inputs in the establishment of debris flow early warning in Mt. Merapi slope area.

  13. Decoding auditory spatial and emotional information encoding using multivariate versus univariate techniques.

    Science.gov (United States)

    Kryklywy, James H; Macpherson, Ewan A; Mitchell, Derek G V

    2018-04-01

    Emotion can have diverse effects on behaviour and perception, modulating function in some circumstances, and sometimes having little effect. Recently, it was identified that part of the heterogeneity of emotional effects could be due to a dissociable representation of emotion in dual pathway models of sensory processing. Our previous fMRI experiment using traditional univariate analyses showed that emotion modulated processing in the auditory 'what' but not 'where' processing pathway. The current study aims to further investigate this dissociation using a more recently emerging multi-voxel pattern analysis searchlight approach. While undergoing fMRI, participants localized sounds of varying emotional content. A searchlight multi-voxel pattern analysis was conducted to identify activity patterns predictive of sound location and/or emotion. Relative to the prior univariate analysis, MVPA indicated larger overlapping spatial and emotional representations of sound within early secondary regions associated with auditory localization. However, consistent with the univariate analysis, these two dimensions were increasingly segregated in late secondary and tertiary regions of the auditory processing streams. These results, while complimentary to our original univariate analyses, highlight the utility of multiple analytic approaches for neuroimaging, particularly for neural processes with known representations dependent on population coding.

  14. Bovine spongiform encephalopathy and spatial analysis of the feed industry.

    Science.gov (United States)

    Paul, Mathilde; Abrial, David; Jarrige, Nathalie; Rican, Stéphane; Garrido, Myriam; Calavas, Didier; Ducrot, Christian

    2007-06-01

    In France, despite the ban of meat-and-bone meal (MBM) in cattle feed, bovine spongiform encephalopathy (BSE) was detected in hundreds of cattle born after the ban. To study the role of MBM, animal fat, and dicalcium phosphate on the risk for BSE after the feed ban, we conducted a spatial analysis of the feed industry. We used data from 629 BSE cases as well as data on use of each byproduct and market area of the feed factories. We mapped risk for BSE in 951 areas supplied by the same factories and connection with use of byproducts. A disease map of BSE with covariates was built with the hierarchical Bayesian modeling methods, based on Poisson distribution with spatial smoothing. Only use of MBM was spatially linked to risk for BSE, which highlights cross-contamination as the most probable source of infection after the feed ban.

  15. Strategic Placing of Field Hospitals Using Spatial Analysis

    OpenAIRE

    Rydén, Magnus

    2011-01-01

    Humanitarian help organisations today may benefit on improving their location analysis when placing field hospitals in countries hit by a disasters or catastrophe. The main objective of this thesis is to develop and evaluate a spatial decision support method for strategic placing of field hospitals for two time perspectives, long term (months) and short term (weeks). Specifically, the possibility of combining existing infrastructure and satellite data is examined to derive a suitability map f...

  16. A new analysis technique for microsamples

    International Nuclear Information System (INIS)

    Boyer, R.; Journoux, J.P.; Duval, C.

    1989-01-01

    For many decades, isotopic analysis of Uranium or Plutonium has been performed by mass spectrometry. The most recent analytical techniques, using the counting method or a plasma torch combined with a mass spectrometer (ICP.MS) have not yet to reach a greater degree of precision than the older methods in this field. The two means of ionization for isotopic analysis - by electronic bombardment of atoms or molecules (source of gas ions) and - by thermal effect (thermoionic source) are compared revealing some inconsistency between the quantity of sample necessary for analysis and the luminosity. In fact, the quantity of sample necessary for the gas source mass spectrometer is 10 to 20 times greater than that for the thermoionization spectrometer, while the sample consumption is between 10 5 to 10 6 times greater. This proves that almost the entire sample is not necessary for the measurement; it is only required because of the system of introduction for the gas spectrometer. The new analysis technique referred to as ''Microfluorination'' corrects this anomaly and exploits the advantages of the electron bombardment method of ionization

  17. Handbook of Qualitative Research Techniques and Analysis in Entrepreneurship

    DEFF Research Database (Denmark)

    One of the most challenging tasks in the research design process is choosing the most appropriate data collection and analysis techniques. This Handbook provides a detailed introduction to five qualitative data collection and analysis techniques pertinent to exploring entreprneurial phenomena....

  18. A novel image encryption scheme based on spatial chaos map

    International Nuclear Information System (INIS)

    Sun Fuyan; Liu Shutang; Li Zhongqin; Lue Zongwang

    2008-01-01

    In recent years, the chaos-based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. In this paper, spatial chaos system are used for high degree security image encryption while its speed is acceptable. The proposed algorithm is described in detail. The basic idea is to encrypt the image in space with spatial chaos map pixel by pixel, and then the pixels are confused in multiple directions of space. Using this method one cycle, the image becomes indistinguishable in space due to inherent properties of spatial chaotic systems. Several experimental results, key sensitivity tests, key space analysis, and statistical analysis show that the approach for image cryptosystems provides an efficient and secure way for real time image encryption and transmission from the cryptographic viewpoint

  19. SPATIAL ANALYSIS TO SUPPORT GEOGRAPHIC TARGETING OF GENOTYPES TO ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    Glenn eHyman

    2013-03-01

    Full Text Available 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 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 five or ten 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.

  20. Quality assurance techniques for activation analysis

    International Nuclear Information System (INIS)

    Becker, D.A.

    1984-01-01

    The principles and techniques of quality assurance are applied to the measurement method of activation analysis. Quality assurance is defined to include quality control and quality assessment. Plans for quality assurance include consideration of: personnel; facilities; analytical design; sampling and sample preparation; the measurement process; standards; and documentation. Activation analysis concerns include: irradiation; chemical separation; counting/detection; data collection, and analysis; and calibration. Types of standards discussed include calibration materials and quality assessment materials

  1. Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada.

    Science.gov (United States)

    Bertazzon, Stefania; Shahid, Rizwan

    2017-07-25

    An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children.

  2. Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada

    Science.gov (United States)

    Bertazzon, Stefania; Shahid, Rizwan

    2017-01-01

    An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children. PMID:28757577

  3. Spatial and temporal mapping of 10B distrubtion in vivo using nuclear reactor-based prompt gamma neutron activation analysis and image reconstruction techniques. Final Report

    International Nuclear Information System (INIS)

    Jacquelyn Yanch

    2006-01-01

    This project involved the development of a method for in vivo prompt gamma neutron activation analysis for the investigation of Boron-10 distribution in a rabbit knee. The overall objective of this work was a robust approach for rapid screening of new 10 B-labelled compounds to determine their suitability for use in the treatment of rheumatoid arthritis via Boron Neutron Capture Synovectomy (BNCS). For BNCS it is essential to obtain a compound showing high uptake levels in the synovium and long residence time in the joints. Previously the in vivo uptake behavior of potential compounds was evaluated in the arthritic knee joints of rabbits via extensive dissection studies. These studies are very labor-intensive and involve sacrificing large numbers of animals. An in vivo 10 B screening approach was developed to provide initial evaluation of potential compounds. Only those compounds showing positive uptake and retention characteristics will be evaluated further via dissection studies. No further studies will be performed with compounds showing rapid clearance and/or low synovial uptake. Two approaches to in vivo screening were investigated using both simulation methods and experimentation. Both make use of neutron beams generated at the MIT Research Reactor. The first, Transmission Computed Tomography (TCT) was developed and tested but was eventually rejected due to very limited spatial resolution using existing reactor beams. The second, in vivo prompt gamma neutron activation analysis (IVPGNAA) was much more promising. IVPGNAA was developed using computer simulation and physical measurement coupled with image reconstruction techniques. The method was tested in arthritic New Zealand rabbits previously injected intra-articularly with three boron labeled compounds and shown to be effective in providing information regarding uptake level and residence time of 10 B in the joint

  4. Spatial heterogeneity analysis of brain activation in fMRI

    Directory of Open Access Journals (Sweden)

    Lalit Gupta

    2014-01-01

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

  5. Aspects of the incorporation of spatial data into radioecological and restoration analysis

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.; Arkhipov, A.; Voigt, G.

    2002-01-01

    In the last decade geographical information systems have been increasingly used to incorporate spatial data into radioecological analysis. This has allowed the development of models with spatially variable outputs. Two main approaches have been adopted in the development of spatial models. Empirical Tag based models applied across a range of spatial scales utilize underlying soil type maps and readily available radioecological data. Soil processes can also be modelled to allow the dynamic prediction of radionuclide soil to plant transfer. We discuss a dynamic semi-mechanistic radiocaesium soil to plant-transfer model, which utilizes readily available spatially variable soil parameters. Both approaches allow the identification of areas that may be vulnerable to radionuclide deposition, therefore enabling the targeting of intervention measures. Improved estimates of radionuclide fluxes and ingestion doses can be achieved by incorporating spatially varying inputs such as agricultural production and dietary habits in to these models. In this paper, aspects of such models, including data requirements, implementation and outputs are discussed and critically evaluated. The relative merits and disadvantages of the two spatial model approaches adopted within radioecology are discussed. We consider the usefulness of such models to aid decision-makers and access the requirements and potential of further application within radiological protection. (author)

  6. Spatial Distribution Analysis of Soil Properties in Varzaneh Region of Isfahan Using Image Processing Techniques

    Directory of Open Access Journals (Sweden)

    F. Mahmoodi

    2016-02-01

    annual evaporation rate is 3265 mm. In this study, image processing techniquess including band combinations, Principal Component Analysis (PC1, PC2 and PC3, and classification were applied to a TM image to map different soil properties. In order to prepare the satellite image, geometric correction was performed. A 1:25,000 map (UTM 39 was used as a base to georegister the Landsat image. 40 Ground Control Points (GCPs were selected throughout the map and image. Road intersections or other man-made features were appropriate targets for this purpose. The raw image was transformed to the georectified image using a first order polynomial, and then resampled using the nearest neighbour method to preserve radiometry. The final Root Mean Square (RMS error for the selected points was 0.3 pixels. To establish relationships between image and field data, stratified random sampling techniques were used to collect 53 soil samples at the GPS (Global Positioning System points. The continuous map of soil properties was achieved using simple and multiple linear regression models by averaging 9 image pixels around sampling sites. Different image spectral indices were used as independent variables and the dependent variables were field- based data. Results and Discussion: The results of multiple regression analysis showed that the strongest relationships was between sandy soil and TM bands 1, 2, 3, 4, and 5, explaining up to 83% of variation in this component. The weakest relationship was found between CaCo3 and 3, 5, and 7 TM bands. In some cases, the multiple regressions was not an appropriate predicting model of soil properties, therefore, the TM and PC bands that had the highest relationship with field data (confidence level, 99% based on simple regression were classified by the maximum likelihood algorithm. According to error matrix, the overall accuracy of classified maps was between 85 and 93% for chlorine (Cl and silt componets, repectively. Conclusions: The results indicated that

  7. Visuo-Spatial Performance in Autism: A Meta-analysis

    OpenAIRE

    Muth, Anne; Honekopp, Johannes; Falter, Christine

    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 heterogeneity that is unaccounted for. No clear differences were found for Mental Rotation. ASD samples showed a stronger local processing preference for...

  8. Techniques for the thermal/hydraulic analysis of LMFBR check valves

    International Nuclear Information System (INIS)

    Cho, S.M.; Kane, R.S.

    1979-01-01

    A thermal/hydraulic analysis of the check valves in liquid sodium service for LMFBR plants is required to provide temperature data for thermal stress analysis of the valves for specified transient conditions. Because of the complex three-dimensional flow pattern within the valve, the heat transfer analysis techniques for less complicated shapes could not be used. This paper discusses the thermal analysis techniques used to assure that the valve stress analysis is conservative. These techniques include a method for evaluating the recirculating flow patterns and for selecting appropriately conservative heat transfer correlations in various regions of the valve

  9. Small area analysis using micro-diffraction techniques

    International Nuclear Information System (INIS)

    Goehner, Raymond P.; Tissot, Ralph G. Jr.; Michael, Joseph R.

    2000-01-01

    An overall trend toward smaller electronic packages and devices makes it increasingly important and difficult to obtain meaningful diffraction information from small areas. X-ray micro-diffraction, electron back-scattered diffraction (EBSD) and Kossel are micro-diffraction techniques used for crystallographic analysis including texture, phase identification and strain measurements. X-ray micro-diffraction primarily is used for phase analysis and residual strain measurements. X-ray micro-diffraction primarily is used for phase analysis and residual strain measurements of areas between 10 microm to 100 microm. For areas this small glass capillary optics are used for producing a usable collimated x-ray beam. These optics are designed to reflect x-rays below the critical angle therefore allowing for larger solid acceptance angle at the x-ray source resulting in brighter smaller x-ray beams. The determination of residual strain using micro-diffraction techniques is very important to the semiconductor industry. Residual stresses have caused voiding of the interconnect metal which then destroys electrical continuity. Being able to determine the residual stress helps industry to predict failures from the aging effects of interconnects due to this stress voiding. Stress measurements would be impossible using a conventional x-ray diffractometer; however, utilizing a 30 microm glass capillary these small areas are readily assessable for analysis. Kossel produces a wide angle diffraction pattern from fluorescent x-rays generated in the sample by an e-beam in a SEM. This technique can yield very precise lattice parameters for determining strain. Fig. 2 shows a Kossel pattern from a Ni specimen. Phase analysis on small areas is also possible using an energy dispersive spectrometer (EBSD) and x-ray micro-diffraction techniques. EBSD has the advantage of allowing the user to observe the area of interest using the excellent imaging capabilities of the SEM. An EDS detector has been

  10. Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

    Science.gov (United States)

    Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

    2018-03-01

    GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

  11. A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002.

    Directory of Open Access Journals (Sweden)

    Daniel M Saman

    Full Text Available 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.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.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.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.

  12. Spatial analysis of digital technologies and impact on socio - cultural ...

    African Journals Online (AJOL)

    The objective of this study was to determine the spatial distribution of digital technologies and ascertain whether digital technologies have significant impact on socio - cultural values or not. Moran's index and Getis and Ord's statistic were used for cluster and hotspots analysis. The unique locations of digital technologies ...

  13. A robust spatial filtering technique for multisource localization and geoacoustic inversion.

    Science.gov (United States)

    Stotts, S A

    2005-07-01

    Geoacoustic inversion and source localization using beamformed data from a ship of opportunity has been demonstrated with a bottom-mounted array. An alternative approach, which lies within a class referred to as spatial filtering, transforms element level data into beam data, applies a bearing filter, and transforms back to element level data prior to performing inversions. Automation of this filtering approach is facilitated for broadband applications by restricting the inverse transform to the degrees of freedom of the array, i.e., the effective number of elements, for frequencies near or below the design frequency. A procedure is described for nonuniformly spaced elements that guarantees filter stability well above the design frequency. Monitoring energy conservation with respect to filter output confirms filter stability. Filter performance with both uniformly spaced and nonuniformly spaced array elements is discussed. Vertical (range and depth) and horizontal (range and bearing) ambiguity surfaces are constructed to examine filter performance. Examples that demonstrate this filtering technique with both synthetic data and real data are presented along with comparisons to inversion results using beamformed data. Examinations of cost functions calculated within a simulated annealing algorithm reveal the efficacy of the approach.

  14. The spatial kinetic analysis of accelerator-driven subcritical reactor

    International Nuclear Information System (INIS)

    Takahashi, H.; An, Y.; Chen, X.

    1998-02-01

    The operation of the accelerator driven reactor with subcritical condition provides a more flexible choice of the reactor materials and of design parameters. A deep subcriticality is chosen sometime from the analysis of point kinetics. When a large reactor is operated in deep subcritical condition by using a localized spallation source, the power distribution has strong spatial dependence, and point kinetics does not provide proper analysis for reactor safety. In order to analyze the spatial and energy dependent kinetic behavior in the subcritical reactor, the authors developed a computation code which is composed of two parts, the first one is for creating the group cross section and the second part solves the multi-group kinetic diffusion equations. The reactor parameters such as the cross section of fission, scattering, and energy transfer among the several energy groups and regions are calculated by using a code modified from the Monte Carlo codes MCNPA and LAHET instead of the usual analytical method of ANISN, TWOTRAN codes. Thus the complicated geometry of the accelerator driven reactor core can be precisely taken into account. The authors analyzed the subcritical minor actinide transmutor studied by Japan Atomic Energy Research Institute (JAERI) using the code

  15. Characterization of electrically-active defects in ultraviolet light-emitting diodes with laser-based failure analysis techniques

    International Nuclear Information System (INIS)

    Miller, Mary A.; Tangyunyong, Paiboon; Cole, Edward I.

    2016-01-01

    Laser-based failure analysis techniques demonstrate the ability to quickly and non-intrusively screen deep ultraviolet light-emitting diodes (LEDs) for electrically-active defects. In particular, two laser-based techniques, light-induced voltage alteration and thermally-induced voltage alteration, generate applied voltage maps (AVMs) that provide information on electrically-active defect behavior including turn-on bias, density, and spatial location. Here, multiple commercial LEDs were examined and found to have dark defect signals in the AVM indicating a site of reduced resistance or leakage through the diode. The existence of the dark defect signals in the AVM correlates strongly with an increased forward-bias leakage current. This increased leakage is not present in devices without AVM signals. Transmission electron microscopy analysis of a dark defect signal site revealed a dislocation cluster through the pn junction. The cluster included an open core dislocation. Even though LEDs with few dark AVM defect signals did not correlate strongly with power loss, direct association between increased open core dislocation densities and reduced LED device performance has been presented elsewhere [M. W. Moseley et al., J. Appl. Phys. 117, 095301 (2015)

  16. Characterization of electrically-active defects in ultraviolet light-emitting diodes with laser-based failure analysis techniques

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Mary A.; Tangyunyong, Paiboon; Cole, Edward I. [Sandia National Laboratories, Albuquerque, New Mexico 87185-1086 (United States)

    2016-01-14

    Laser-based failure analysis techniques demonstrate the ability to quickly and non-intrusively screen deep ultraviolet light-emitting diodes (LEDs) for electrically-active defects. In particular, two laser-based techniques, light-induced voltage alteration and thermally-induced voltage alteration, generate applied voltage maps (AVMs) that provide information on electrically-active defect behavior including turn-on bias, density, and spatial location. Here, multiple commercial LEDs were examined and found to have dark defect signals in the AVM indicating a site of reduced resistance or leakage through the diode. The existence of the dark defect signals in the AVM correlates strongly with an increased forward-bias leakage current. This increased leakage is not present in devices without AVM signals. Transmission electron microscopy analysis of a dark defect signal site revealed a dislocation cluster through the pn junction. The cluster included an open core dislocation. Even though LEDs with few dark AVM defect signals did not correlate strongly with power loss, direct association between increased open core dislocation densities and reduced LED device performance has been presented elsewhere [M. W. Moseley et al., J. Appl. Phys. 117, 095301 (2015)].

  17. Using Spatial Multi-Criteria Analysis and Ranking Tool (SMART in earthquake risk assessment: a case study of Delhi region, India

    Directory of Open Access Journals (Sweden)

    Nishant Sinha

    2016-03-01

    Full Text Available This article is aimed at earthquake hazard, vulnerability and risk assessment as a case study to demonstrate the applicability of Spatial Multi-Criteria Analysis and Ranking Tool (SMART, which is based on Saaty's multi-criteria decision analysis (MCDA technique. The three specific study sites of Delhi were chosen for research as it corresponds to a typical patch of the urban environs, completely engrossed with residential, commercial and industrial units. The earthquake hazard affecting components are established in the form of geographic information system data-set layers including seismic zone, peak ground acceleration (PGA, soil characteristics, liquefaction potential, geological characteristics, land use, proximity to fault and epicentre. The physical vulnerability layers comprising building information, namely number of stories, year-built range, area, occupancy and construction type, derived from remote sensing imagery, were only considered for the current research. SMART was developed for earthquake risk assessment, and weights were derived both at component and its element level. Based on weighted overlay techniques, the earthquake hazard and vulnerability layers were created from which the risk maps were derived through multiplicative analysis. The developed risk maps may prove useful in decision-making process and formulating risk mitigation measures.

  18. Biokinematic structure of techniques wrestlers during pre-basic training

    Directory of Open Access Journals (Sweden)

    S.V. Sinіgovets

    2013-07-01

    Full Text Available The theoretical aspects of freestyle wrestlers. Experimentally investigated the structural elements of techniques during pre-basic training. The study involved 28 young fighters. Held video computer analysis techniques. Identified biomechanical characteristics defined kinematic structure of the temporal and spatial-temporal characteristics of the basic techniques. Shown variability of the individual phases of the basic techniques. Structural dynamics of the resulting velocities of the individual body bioelement fighters showed characteristic changes depending on the mode and direction of the motor action. Found that the predominant contribution to the biokinematic structure of technical actions were resulting velocities torso of young fighters.

  19. Analysis of spatial pattern of settlements in the federal capital ...

    African Journals Online (AJOL)

    Human settlements are important, seemingly static but dynamic, features of the cultural landscape that have attracted several studies due to the important role they play in human life. This paper examined the spatial distribution of settlements in the Federal Capital Territory (FCT) of Nigeria. The analysis uses vector based ...

  20. Spatial mapping and analysis of aerosols during a forest fire using computational mobile microscopy

    Science.gov (United States)

    Wu, Yichen; Shiledar, Ashutosh; Luo, Yi; Wong, Jeffrey; Chen, Cheng; Bai, Bijie; Zhang, Yibo; Tamamitsu, Miu; Ozcan, Aydogan

    2018-02-01

    Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address this and similar field test challenges, we developed a mobilemicroscopy- and machine-learning-based air quality monitoring platform called c-Air, which can perform air sampling and microscopic analysis of aerosols in an integrated portable device. We tested its performance for PM sizing and morphological analysis during a recent forest fire event in La Tuna Canyon Park by spatially mapping the PM. The result shows that with decreasing distance to the fire site, the PM concentration increases dramatically, especially for particles smaller than 2 µm. Image analysis from the c-Air portable device also shows that the increased PM is comparatively strongly absorbing and asymmetric, with an aspect ratio of 0.5-0.7. These PM features indicate that a major portion of the PM may be open-flame-combustion-generated element carbon soot-type particles. This initial small-scale experiment shows that c-Air has some potential for forest fire monitoring.

  1. Microextraction sample preparation techniques in biomedical analysis.

    Science.gov (United States)

    Szultka, Malgorzata; Pomastowski, Pawel; Railean-Plugaru, Viorica; Buszewski, Boguslaw

    2014-11-01

    Biologically active compounds are found in biological samples at relatively low concentration levels. The sample preparation of target compounds from biological, pharmaceutical, environmental, and food matrices is one of the most time-consuming steps in the analytical procedure. The microextraction techniques are dominant. Metabolomic studies also require application of proper analytical technique for the determination of endogenic metabolites present in biological matrix on trace concentration levels. Due to the reproducibility of data, precision, relatively low cost of the appropriate analysis, simplicity of the determination, and the possibility of direct combination of those techniques with other methods (combination types on-line and off-line), they have become the most widespread in routine determinations. Additionally, sample pretreatment procedures have to be more selective, cheap, quick, and environmentally friendly. This review summarizes the current achievements and applications of microextraction techniques. The main aim is to deal with the utilization of different types of sorbents for microextraction and emphasize the use of new synthesized sorbents as well as to bring together studies concerning the systematic approach to method development. This review is dedicated to the description of microextraction techniques and their application in biomedical analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Spatial interpolation

    NARCIS (Netherlands)

    Stein, A.

    1991-01-01

    The theory and practical application of techniques of statistical interpolation are studied in this thesis, and new developments in multivariate spatial interpolation and the design of sampling plans are discussed. Several applications to studies in soil science are

  3. Reliability Analysis of 6-Component Star Markov Repairable System with Spatial Dependence

    Directory of Open Access Journals (Sweden)

    Liying Wang

    2017-01-01

    Full Text Available Star repairable systems with spatial dependence consist of a center component and several peripheral components. The peripheral components are arranged around the center component, and the performance of each component depends on its spatial “neighbors.” Vector-Markov process is adapted to describe the performance of the system. The state space and transition rate matrix corresponding to the 6-component star Markov repairable system with spatial dependence are presented via probability analysis method. Several reliability indices, such as the availability, the probabilities of visiting the safety, the degradation, the alert, and the failed state sets, are obtained by Laplace transform method and a numerical example is provided to illustrate the results.

  4. A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of ...

    African Journals Online (AJOL)

    A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of household ... conducted by the National Institute of Statistics of Rwanda in 2000-2001. ... The third region of low poverty incident has between 4-12% of its population poor.

  5. Methods for magnetic resonance analysis using magic angle technique

    Science.gov (United States)

    Hu, Jian Zhi [Richland, WA; Wind, Robert A [Kennewick, WA; Minard, Kevin R [Kennewick, WA; Majors, Paul D [Kennewick, WA

    2011-11-22

    Methods of performing a magnetic resonance analysis of a biological object are disclosed that include placing the object in a main magnetic field (that has a static field direction) and in a radio frequency field; rotating the object at a frequency of less than about 100 Hz around an axis positioned at an angle of about 54.degree.44' relative to the main magnetic static field direction; pulsing the radio frequency to provide a sequence that includes a phase-corrected magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. In particular embodiments the method includes pulsing the radio frequency to provide at least two of a spatially selective read pulse, a spatially selective phase pulse, and a spatially selective storage pulse. Further disclosed methods provide pulse sequences that provide extended imaging capabilities, such as chemical shift imaging or multiple-voxel data acquisition.

  6. Analysis of Participatory Processes in the Formulation of Spatial Plan for Nature Park Medvednica

    Directory of Open Access Journals (Sweden)

    Nataša Lovrić

    2011-12-01

    Full Text Available Background and Purpose: This research aims to assess the stakeholders influence on spatial planning of Nature Park Medvednica, a mountainous protected area adjacent to Zagreb, the capital city of Croatia, which tries to hold on to the pressure of the urbanization. Because of the inexistence of spatial plan which is required with the Croatian laws, its area was significantly decreased in 2009. This kind of research has not been done yet for NP Medvednica, and it will provide a contribution to the process of developing a spatial Plan for NP Medvednica. Material and Methods: The study was conducted in the framework of stakeholder analysis, for which a series of in-depth interviews with - stakeholders were performed, and documents concerning the spatial plan were analysed. The data gained was processed in MAXQDA software for qualitative analysis. Results and Conclusion: The gathered data explains which are the disadvantages of the tree processes of the formulation of the spatial plan and is giving a possible theoretical explanation or a model which can be implied in any decision making process involving stakeholders in natural resources management in within a given political and cultural context. Description of the past and current spatial planning situation of the NP Medvednica was specified and issues and stakeholders concerning the creation of the spatial plan where identified. The key conflict areas that affect the formulation of spatial plan were detected and examined. The level of participation of stakeholders in the context of fulfilment of their own interests was assessed as well as the influence on participation processes of different stakeholder groups on the formulation of the spatial plan. In order to have proper citizens and stakeholders participation some changes in the legislation should take place.

  7. Kinematics analysis technique fouettes 720° classic ballet.

    Directory of Open Access Journals (Sweden)

    Li Bo

    2011-07-01

    Full Text Available Athletics practice proved that the more complex the item, the more difficult technique of the exercises. Fouettes at 720° one of the most difficult types of the fouettes. Its implementation is based on high technology during rotation of the performer. To perform this element not only requires good physical condition of the dancer, but also requires possession correct technique dancer. On the basis corresponding kinematic theory in this study, qualitative analysis and quantitative assessment of fouettes at 720 by the best Chinese dancers. For analysis, was taken the method of stereoscopic images and the theoretical analysis.

  8. Spatial Analysis of Large Woody Debris Arrangement in a Midwestern U.S. River System: Geomorphic Implications and Influences

    Science.gov (United States)

    Martin, D. J.

    2013-12-01

    Large woody debris (LWD) is universally recognized as a key component of the geomorphological and ecological function of fluvial systems and has been increasingly incorporated into stream restoration and watershed management projects. However, 'natural' processes of recruitment and the subsequent arrangement of LWD within the river network are poorly understood and are thus, rarely a management consideration. Additionally, LWD research tends to be regionally biased toward mountainous regions, and scale biased toward the micro-scale. In many locations, the lack of understanding has led to the failure of restoration/rehabilitation projects that involved the use of LWD. This research uses geographic information systems and spatial analysis techniques to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. A large-scale GPS inventory of LWD was performed on the Big River, located in the eastern Missouri Ozarks resulting in over 5,000 logged positions of LWD along seven river segments covering nearly 100 km of the 237 km river system. A time series analysis framework was used to statistically identify longitudinal spatial patterns of LWD arrangement along the main stem of the river, and correlation analyses were performed to help identify physical controls of those patterns. Results indicate that upstream segments have slightly lower densities than downstream segments, with the exception of the farthest upstream segment. Results also show lack of an overall longitudinal trend in LWD density; however, periodogram analysis revealed an inherent periodicity in LWD arrangement. Periodicities were most evident in the downstream segments with frequencies ranging from 3 km to 7 km. Additionally, Pearson correlation analysis, performed within the segment displaying the strongest periodic behavior, show that LWD densities are correlated with channel sinuosity (r=0.25). Ongoing research is investigating further relationships between arrangement

  9. Nuclear techniques for bulk and surface analysis of materials

    International Nuclear Information System (INIS)

    D'Agostino, M.D.; Kamykowski, E.A.; Kuehne, F.J.; Padawer, G.M.; Schneid, E.J.; Schulte, R.L.; Stauber, M.C.; Swanson, F.R.

    1978-01-01

    A review is presented summarizing several nondestructive bulk and surface analysis nuclear techniques developed in the Grumman Research Laboratories. Bulk analysis techniques include 14-MeV-neutron activation analysis and accelerator-based neutron radiography. The surface analysis techniques include resonant and non-resonant nuclear microprobes for the depth profile analysis of light elements (H, He, Li, Be, C, N, O and F) in the surface of materials. Emphasis is placed on the description and discussion of the unique nuclear microprobe analytical capacibilities of immediate importance to a number of current problems facing materials specialists. The resolution and contrast of neutron radiography was illustrated with an operating heat pipe system. The figure shows that the neutron radiograph has a resolution of better than 0.04 cm with sufficient contrast to indicate Freon 21 on the inner capillaries of the heat pipe and pooling of the liquid at the bottom. (T.G.)

  10. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs

  11. [Spatial analysis of childhood obesity and overweight in Peru, 2014].

    Science.gov (United States)

    Hernández-Vásquez, Akram; Bendezú-Quispe, Guido; Díaz-Seijas, Deysi; Santero, Marilina; Minckas, Nicole; Azañedo, Diego; Antiporta, Daniel A

    2016-01-01

    To estimate regional prevalence and identify the spatial patterns of the degree of overweight and obesity by districts in under five years children in Peru during 2014. Analysis of the information reported by the Information System Nutritional Status (SIEN) of the number of cases of overweight and obesity in children under five years recorded during 2014. Regional prevalence for overweight and obesity, and their respective confidence intervals to 95% were calculated. Moran index was used to determine patterns of grouping districts with high prevalence of overweight and/or obesity. Data from 1834 districts and 2,318,980 children under five years were analyzed. 158,738 cases (6.84%; CI 95%: 6.81 to 6.87) were overweight, while 56,125 (2.42%; CI 95%: 2.40 to 2.44) obesity. The highest prevalence of overweight were identified in the regions of Tacna (13.9%), Moquegua (11.8%), Callao (10.4%), Lima (10.2%) and Ica (9.3%), and in the same regions for obesity with 5.3%; 4.3%; 4.0%; 4.0% and 3.8% respectively. The spatial analysis found grouping districts of high prevalence in 10% of all districts for both overweight and obesity, identifying 199 districts for overweight (126 urban and 73 rural), and 184 for obesity (136 urban and 48 rural). The highest prevalence of overweight and obesity were identified in the Peruvian coast regions. Moreover, these regions are predominantly exhibited a spatial clustering of districts with high prevalence of overweight and obesity.

  12. Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

    Energy Technology Data Exchange (ETDEWEB)

    Siljander, M.

    2010-07-01

    This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Aaland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics

  13. REMOTE SENSING-BASED DETECTION AND SPATIAL PATTERN ANALYSIS FOR GEO-ECOLOGICAL NICHE MODELING OF TILLANDSIA SPP. IN THE ATACAMA, CHILE

    Directory of Open Access Journals (Sweden)

    N. Wolf

    2016-06-01

    Full Text Available In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called ‘fog oases’ dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

  14. Remote Sensing-Based Detection and Spatial Pattern Analysis for Geo-Ecological Niche Modeling of Tillandsia SPP. In the Atacama, Chile

    Science.gov (United States)

    Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.

    2016-06-01

    In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

  15. The development of human behavior analysis techniques

    International Nuclear Information System (INIS)

    Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang.

    1997-07-01

    In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator's physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs

  16. The development of human behavior analysis techniques

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang

    1997-07-01

    In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator`s physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs.

  17. Research on spatial Model and analysis algorithm for nuclear weapons' damage effects

    International Nuclear Information System (INIS)

    Liu Xiaohong; Meng Tao; Du Maohua; Wang Weili; Ji Wanfeng

    2011-01-01

    In order to realize the three dimension visualization of nuclear weapons' damage effects. Aiming at the characteristics of the damage effects data, a new model-MRPCT model is proposed, and this model can carry out the modeling of the three dimension spatial data of the nuclear weapons' damage effects. For the sake of saving on the memory, linear coding method is used to store the MRPCT model. On the basis of Morton code, spatial analysis of the damage effects is completed. (authors)

  18. Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

    Science.gov (United States)

    Maksimova, L. A.; Ryabukho, P. V.; Mysina, N. Yu.; Lyakin, D. V.; Ryabukho, V. P.

    2018-04-01

    We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

  19. Spectroscopic analysis technique for arc-welding process control

    Science.gov (United States)

    Mirapeix, Jesús; Cobo, Adolfo; Conde, Olga; Quintela, María Ángeles; López-Higuera, José-Miguel

    2005-09-01

    The spectroscopic analysis of the light emitted by thermal plasmas has found many applications, from chemical analysis to monitoring and control of industrial processes. Particularly, it has been demonstrated that the analysis of the thermal plasma generated during arc or laser welding can supply information about the process and, thus, about the quality of the weld. In some critical applications (e.g. the aerospace sector), an early, real-time detection of defects in the weld seam (oxidation, porosity, lack of penetration, ...) is highly desirable as it can reduce expensive non-destructive testing (NDT). Among others techniques, full spectroscopic analysis of the plasma emission is known to offer rich information about the process itself, but it is also very demanding in terms of real-time implementations. In this paper, we proposed a technique for the analysis of the plasma emission spectrum that is able to detect, in real-time, changes in the process parameters that could lead to the formation of defects in the weld seam. It is based on the estimation of the electronic temperature of the plasma through the analysis of the emission peaks from multiple atomic species. Unlike traditional techniques, which usually involve peak fitting to Voigt functions using the Levenberg-Marquardt recursive method, we employ the LPO (Linear Phase Operator) sub-pixel algorithm to accurately estimate the central wavelength of the peaks (allowing an automatic identification of each atomic species) and cubic-spline interpolation of the noisy data to obtain the intensity and width of the peaks. Experimental tests on TIG-welding using fiber-optic capture of light and a low-cost CCD-based spectrometer, show that some typical defects can be easily detected and identified with this technique, whose typical processing time for multiple peak analysis is less than 20msec. running in a conventional PC.

  20. The spatial evaluation of neighborhood clusters of birth defects

    Energy Technology Data Exchange (ETDEWEB)

    Frisch, J.D.

    1990-04-16

    Spatial statistics have recently been applied in epidemiology to evaluate clusters of cancer and birth defects. Their use requires a comparison population, drawn from the population at risk for disease, that may not always be readily available. In this dissertation the plausibility of using data on all birth defects, available from birth defects registries, as a surrogate for the spatial distribution of all live births in the analysis of clusters is assessed. Three spatial statistics that have been applied in epidemiologic investigations of clusters, nearest neighbor distance, average interpoint distance, and average distance to a fixed point, were evaluated by computer simulation for their properties in a unit square, and in a zip code region. Comparison of spatial distributions of live births and birth defects was performed by drawing samples of live births and birth defects from Santa Clara County, determining the street address at birth, geocoding this address and evaluating the resultant maps using various statistical techniques. The proposed method was then demonstrated on a previously confirmed cluster of oral cleft cases. All live births for the neighborhood were geocoded, as were all birth defects. Evaluation of this cluster using the nearest neighbor and average interpoint distance statistics was performed using randomization techniques with both the live births population and the birth defect population as comparison groups. 113 refs., 36 figs., 16 tabs.

  1. Contouring a guide to the analysis and display of spatial data

    CERN Document Server

    Watson, Debbie

    2013-01-01

    This unique book is the key to computer contouring, exploring in detail the practice and principles using a personal computer. Contouring allows a three dimensional view in two dimensions and is a fundamental technique to represent spatial data. All aspects of this type of representation are covered including data preparation, selecting contour intervals, interpolation and griding, computing volumes and output and display. Formulated for both the novice and the experienced user, this book initially conducts the reader through a step by step explanation of PC software and its application to per

  2. Toward seamless hydrologic predictions across spatial scales

    Directory of Open Access Journals (Sweden)

    L. Samaniego

    2017-09-01

    Full Text Available Land surface and hydrologic models (LSMs/HMs are used at diverse spatial resolutions ranging from catchment-scale (1–10 km to global-scale (over 50 km applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR technique offers a practical and robust method that provides consistent (seamless parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

  3. Toward seamless hydrologic predictions across spatial scales

    Science.gov (United States)

    Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

    2017-09-01

    Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

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

    Science.gov (United States)

    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.

  5. Analysis of initial prestress force of spatial tendon prestressed concrete containment structures

    International Nuclear Information System (INIS)

    Shiau, H.-S.

    1975-01-01

    A theoretical investigation is presented of the initial stage of prestressed tendon and prestressed concrete before and after jacking force of tendon anchorage released. A method is developed that is applicable to any kind of spatial tendon considering frictional loss due to length and curvature effects. A triple integral equation of one independent variable and jacking force is derived to represent an exact solution of tendon force along the whole tendon which may have reverse curvatures. In order to analyze the stress response of concrete due to this prestress force by using existing finite element computer program or any other kind of computer program, a systematic method is suggested to obtain tendon force components, which are represented by a series of equations of one independent variable, in any coordinate system as external force applied on the concrete. The resulting systems of the equations are then solved by numerical mathematic and computer techniques. Two numerical examples are represented. The first example is, dome prestress analysis of containment building by the proposed method and Kalnins' computer program for shell of revolution. Results are discussed. The second example is picked from prestress analysis for personnel air lock of containment building by using proposed method and FELAP finite element Computer program. It includes two different tendon arrangements around the opening. The results of these two different arrangements are compared and discussed

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

    Science.gov (United States)

    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

  7. WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Y; Mutic, S; Du, D; Green, O [Washington University School of Medicine, Saint Louis, MO (United States); Zeng, Q; Nana, R; Patrick, J; Shvartsman, S; Dempsey, J [ViewRay Incorporated, Oakwood Village, OH (United States)

    2014-06-15

    Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported into the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green

  8. WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

    International Nuclear Information System (INIS)

    Hu, Y; Mutic, S; Du, D; Green, O; Zeng, Q; Nana, R; Patrick, J; Shvartsman, S; Dempsey, J

    2014-01-01

    Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported into the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green

  9. Determining the Number of Factors in P-Technique Factor Analysis

    Science.gov (United States)

    Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

    2017-01-01

    Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

  10. ANALYSIS OF PRO-POOR GROWTH AMONG THE MUNICIPAL DISTRICTS OF THE STATE OF CEARÁ - BRAZIL: SPATIAL APPROACH

    Directory of Open Access Journals (Sweden)

    Wellington Ribeiro Justo

    2014-04-01

    Full Text Available This article investigates the for-poor growth among the municipal districts of the State of Ceará in 2003. Initially it explores the recent literature of the theme as well as of the spatial econometric. Soon after it makes the spatial analysis of the variables through maps and in more robust way through the Exploratory Analysis of Given Spatial (AEDE being used the LISA methodology (Local Indicators of Spatial Association and the statistics I of Moran. Estimates the elasticity income-poverty and elasticity inequality-poverty. The tests indicated the need to incorporate variables in the estimates that learn the spatial externalities. The results suggest for-poor growth in the municipal districts from Ceará in agreement with results aggregate for the Ceará state appointed in recent literature.

  11. Optical encryption using pseudorandom complex spatial modulation.

    Science.gov (United States)

    Sarkadi, Tamás; Koppa, Pál

    2012-12-01

    In this paper we propose a new (to our knowledge) complex spatial modulation method to encode data pages applicable in double random phase encryption (DRPE) to make the system more resistant to brute-force attack. The proposed modulation method uses data page pixels with random phase and amplitude values with the condition that the intensity of the interference of light from two adjacent pixels should correspond to the encoded information. A differential phase contrast technique is applied to recover the data page at the output of the system. We show that the proposed modulation method can enhance the robustness of the DRPE technique using point spread function analysis. Key space expansion is determined by numeric model calculations.

  12. 10th Australian conference on nuclear techniques of analysis. Proceedings

    International Nuclear Information System (INIS)

    1998-01-01

    These proceedings contains abstracts and extended abstracts of 80 lectures and posters presented at the 10th Australian conference on nuclear techniques of analysis hosted by the Australian National University in Canberra, Australia from 24-26 of November 1997. The conference was divided into sessions on the following topics : ion beam analysis and its applications; surface science; novel nuclear techniques of analysis, characterization of thin films, electronic and optoelectronic material formed by ion implantation, nanometre science and technology, plasma science and technology. A special session was dedicated to new nuclear techniques of analysis, future trends and developments. Separate abstracts were prepared for the individual presentation included in this volume

  13. 10th Australian conference on nuclear techniques of analysis. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-06-01

    These proceedings contains abstracts and extended abstracts of 80 lectures and posters presented at the 10th Australian conference on nuclear techniques of analysis hosted by the Australian National University in Canberra, Australia from 24-26 of November 1997. The conference was divided into sessions on the following topics : ion beam analysis and its applications; surface science; novel nuclear techniques of analysis, characterization of thin films, electronic and optoelectronic material formed by ion implantation, nanometre science and technology, plasma science and technology. A special session was dedicated to new nuclear techniques of analysis, future trends and developments. Separate abstracts were prepared for the individual presentation included in this volume.

  14. RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

    Science.gov (United States)

    Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

    2005-10-01

    Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and

  15. Cluster: A New Application for Spatial Analysis of Pixelated Data for Epiphytotics.

    Science.gov (United States)

    Nelson, Scot C; Corcoja, Iulian; Pethybridge, Sarah J

    2017-12-01

    Spatial analysis of epiphytotics is essential to develop and test hypotheses about pathogen ecology, disease dynamics, and to optimize plant disease management strategies. Data collection for spatial analysis requires substantial investment in time to depict patterns in various frames and hierarchies. We developed a new approach for spatial analysis of pixelated data in digital imagery and incorporated the method in a stand-alone desktop application called Cluster. The user isolates target entities (clusters) by designating up to 24 pixel colors as nontargets and moves a threshold slider to visualize the targets. The app calculates the percent area occupied by targeted pixels, identifies the centroids of targeted clusters, and computes the relative compass angle of orientation for each cluster. Users can deselect anomalous clusters manually and/or automatically by specifying a size threshold value to exclude smaller targets from the analysis. Up to 1,000 stochastic simulations randomly place the centroids of each cluster in ranked order of size (largest to smallest) within each matrix while preserving their calculated angles of orientation for the long axes. A two-tailed probability t test compares the mean inter-cluster distances for the observed versus the values derived from randomly simulated maps. This is the basis for statistical testing of the null hypothesis that the clusters are randomly distributed within the frame of interest. These frames can assume any shape, from natural (e.g., leaf) to arbitrary (e.g., a rectangular or polygonal field). Cluster summarizes normalized attributes of clusters, including pixel number, axis length, axis width, compass orientation, and the length/width ratio, available to the user as a downloadable spreadsheet. Each simulated map may be saved as an image and inspected. Provided examples demonstrate the utility of Cluster to analyze patterns at various spatial scales in plant pathology and ecology and highlight the

  16. Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis

    Directory of Open Access Journals (Sweden)

    Jianmin Liu

    2017-01-01

    Full Text Available This paper studies the environmental pollution and its impacts in China using prefecture-level cities and municipalities data. Moran’s I, the widely used spatial autocorrelation index, provides a fairly strong pattern of spatial clustering of environmental pollution and suggests a fairly high stability of the positive spatial correlation. To investigate the driving forces of environmental pollution and explore the relationship between fiscal decentralization, economic growth, and environmental pollution, spatial Durbin model is used for this analysis. The result shows that fiscal decentralization of local unit plays a significant role in promoting the environmental pollution and the feedback effect of fiscal decentralization on environmental pollution is also positive, though it is not significant. The relationship of GDP per capita and environmental pollution shows inverted U-shaped curve. Due to the scale effect of secondary industry, the higher the level of secondary industry development in a unit is, the easier it is to attract the secondary industry in adjacent units, which mitigates the environmental pollution in adjacent units. Densely populated areas tend to deteriorate local environment, but environmental regulation in densely populated areas is often tighter than other areas, which reduces environmental pollution to a certain extent.

  17. A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.

    Science.gov (United States)

    Euler, André; Solomon, Justin; Marin, Daniele; Nelson, Rendon C; Samei, Ehsan

    2018-06-01

    The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1.25-10 mGy). Images were reconstructed with filtered back projection (FBP), ASIR-V with 50% blending with FBP (ASIR-V 50%), and ASIR-V without blending (ASIR-V 100%). In the first phantom, noise properties were assessed by noise power spectrum analysis. Spatial resolution properties were measured by use of task transfer functions for objects of different contrasts. Noise magnitude, noise texture, and resolution were compared between the three groups. In the second phantom, low-contrast detectability was assessed by nine human readers independently for each condition. The dose reduction potential of ASIR-V was estimated on the basis of a generalized linear statistical regression model. On average, image noise was reduced 37.3% with ASIR-V 50% and 71.5% with ASIR-V 100% compared with FBP. ASIR-V shifted the noise power spectrum toward lower frequencies compared with FBP. The spatial resolution of ASIR-V was equivalent or slightly superior to that of FBP, except for the low-contrast object, which had lower resolution. Lesion detection significantly increased with both ASIR-V levels (p = 0.001), with an estimated radiation dose reduction potential of 15% ± 5% (SD) for ASIR-V 50% and 31% ± 9% for ASIR-V 100%. ASIR-V reduced image noise and improved lesion detection compared with FBP and had potential for radiation dose reduction while preserving low-contrast detectability.

  18. Spatial-Frequency Azimuthally Stable Cartography of Biological Polycrystalline Networks

    Directory of Open Access Journals (Sweden)

    V. A. Ushenko

    2013-01-01

    Full Text Available A new azimuthally stable polarimetric technique processing microscopic images of optically anisotropic structures of biological tissues histological sections is proposed. It has been used as a generalized model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity. The matrix element M44 has been chosen as the main information parameter, whose value is independent of the rotation angle of both sample and probing beam polarization plane. For the first time, the technique of concerted spatial-frequency filtration has been used in order to separate the manifestation of linear birefringence and optical activity. Thereupon, the method of azimuthally stable spatial-frequency cartography of biological tissues histological sections has been elaborated. As the analyzing tool, complex statistic, correlation, and fractal analysis of coordinate distributions of M44 element has been performed. The possibility of using the biopsy of the uterine wall tissue in order to differentiate benign (fibromyoma and malignant (adenocarcinoma conditions has been estimated.

  19. Evaluation of Medium Spatial Resolution BRDF-Adjustment Techniques Using Multi-Angular SPOT4 (Take5 Acquisitions

    Directory of Open Access Journals (Sweden)

    Martin Claverie

    2015-09-01

    Full Text Available High-resolution sensor Surface Reflectance (SR data are affected by surface anisotropy but are difficult to adjust because of the low temporal frequency of the acquisitions and the low angular sampling. This paper evaluates five high spatial resolution Bidirectional Reflectance Distribution Function (BRDF adjustment techniques. The evaluation is based on the noise level of the SR Time Series (TS corrected to a normalized geometry (nadir view, 45° sun zenith angle extracted from the multi-angular acquisitions of SPOT4 over three study areas (one in Arizona, two in France during the five-month SPOT4 (Take5 experiment. Two uniform techniques (Cst, for Constant, and Av, for Average, relying on the Vermote–Justice–Bréon (VJB BRDF method, assume no variation in space of the BRDF shape. Two methods (VI-dis, for NDVI-based disaggregation and LC-dis, for Land-Cover based disaggregation are based on disaggregation of the MODIS-derived BRDF VJB parameters using vegetation index and land cover, respectively. The last technique (LUM, for Look-Up Map relies on the MCD43 MODIS BRDF products and a crop type data layer. The VI-dis technique produced the lowest level of noise corresponding to the most effective adjustment: reduction from directional to normalized SR TS noises by 40% and 50% on average, for red and near-infrared bands, respectively. The uniform techniques displayed very good results, suggesting that a simple and uniform BRDF-shape assumption is good enough to adjust the BRDF in such geometric configuration (the view zenith angle varies from nadir to 25°. The most complex techniques relying on land cover (LC-dis and LUM displayed contrasting results depending on the land cover.

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

    Science.gov (United States)

    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

  1. High Resolution Spatio Temporal Moments Analysis of Solute Migration Captured using Pre-clinical Medical Imaging Techniques

    Science.gov (United States)

    Dogan, M.; Moysey, S. M.; Powell, B. A.; DeVol, T. A.

    2016-12-01

    Advances in medical imaging technologies are continuously expanding the range of applications enabled within the earth sciences. While computed x-ray tomography (CT) scans have traditionally been used for investigating the structure of geologic materials, it is now possible to perform 3D time-lapse imaging of dynamic processes, such as monitoring the infiltration of water into a soil, with sub-millimeter resolution. Likewise, single photon emission computed tomography (SPECT) can provide information on the evolution of solute transport with spatial resolution on the order of a millimeter by tracking the migration of gamma-ray emitting isotopes like 99mTc and 111In. While these imaging techniques are revolutionizing our ability to look within porous media, techniques for the analysis of such rich and large data sets are limited. The spatial and temporal moments of a plume have long been used to provide quantitative measures to describe plume movement in a wide range of settings from the lab to field. Moment analysis can also be used to estimate the hydrologic properties of the porous media. In this research, we investigate the use of moments for analyzing a high resolution 4D SPECT data set collected during a 99mTc transport experiment performed in a heterogeneous column. The 4D nature of the data set makes it amenable to the use of data mining and pattern recognition methods, such as cluster analysis, to identify regions or zones within the data that exhibit abnormal or unexpected behaviors. We then compare anomalous features within the SPECT data to similar features identified within the CT image to relate the flow behavior to pore-scale structures, such as porosity differences and macropores. Such comparisons help to identify whether these features are good predictors of preferential transport. Likewise, we evaluate whether local analysis of moments can be used to infer apparent parameters governing non-conservative transport in a heterogeneous porous media, such

  2. Review and classification of variability analysis techniques with clinical applications

    Science.gov (United States)

    2011-01-01

    Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis. PMID:21985357

  3. Review and classification of variability analysis techniques with clinical applications.

    Science.gov (United States)

    Bravi, Andrea; Longtin, André; Seely, Andrew J E

    2011-10-10

    Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

  4. Obtaining absolute spatial flux measurements with a time-resolved pinhole camera

    International Nuclear Information System (INIS)

    Baker, K.L.; Porter, J.L.; Ruggles, L.E.; Fehl, D.L.; Chandler, G.A.; Vargas, M.; Mix, L.P.; Simpson, W.W.; Deeney, C.; Chrien, R.E.; Idzorek, G.C.

    1999-01-01

    A technique is described to determine the spatial x-ray flux emitted from a hohlraum wall and subsequently transmitted through a diagnostic hole. This technique uses x-ray diodes, bolometers, and a time-resolved pinhole camera to determine the spatial flux of x rays emitted through a hohlraum close-quote s diagnostic hole. The primary motivation for this analysis was the relatively long duration, nearly 100 ns, of the x-ray drive present in z-pinch driven hohlraums. This radiation causes plasma to ablate from the hohlraum walls surrounding the diagnostic hole and results in a partial obscuration that reduces the effective area over which diagnostics view the radiation. The effective change in area leads to an underestimation of the wall temperature when nonimaging diagnostics such as x-ray diodes and bolometers are used to determine power and later to infer a wall temperature. An analysis similar to the one described below is then necessary to understand the radiation environment present in x-ray driven hohlraums when these diagnostics are used and hole closure is important. copyright 1999 American Institute of Physics

  5. Spatial filtering with photonic crystals

    Energy Technology Data Exchange (ETDEWEB)

    Maigyte, Lina [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Rambla Sant Nebridi 22, Terrassa 08222 (Spain); Staliunas, Kestutis [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Rambla Sant Nebridi 22, Terrassa 08222 (Spain); Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluís Companys 23, Barcelona 08010 (Spain)

    2015-03-15

    Photonic crystals are well known for their celebrated photonic band-gaps—the forbidden frequency ranges, for which the light waves cannot propagate through the structure. The frequency (or chromatic) band-gaps of photonic crystals can be utilized for frequency filtering. In analogy to the chromatic band-gaps and the frequency filtering, the angular band-gaps and the angular (spatial) filtering are also possible in photonic crystals. In this article, we review the recent advances of the spatial filtering using the photonic crystals in different propagation regimes and for different geometries. We review the most evident configuration of filtering in Bragg regime (with the back-reflection—i.e., in the configuration with band-gaps) as well as in Laue regime (with forward deflection—i.e., in the configuration without band-gaps). We explore the spatial filtering in crystals with different symmetries, including axisymmetric crystals; we discuss the role of chirping, i.e., the dependence of the longitudinal period along the structure. We also review the experimental techniques to fabricate the photonic crystals and numerical techniques to explore the spatial filtering. Finally, we discuss several implementations of such filters for intracavity spatial filtering.

  6. A numerical technique for reactor subchannel analysis

    International Nuclear Information System (INIS)

    Fath, Hassan E.S.

    1983-01-01

    A numerical technique is developed for the solution of the transient boundary layer equations with a moving liquid-vapour interface boundary. The technique uses the finite difference method with the velocity components defined over an Eulerian mesh. A system of interface massless markers is defined where the markers move with the flow field according to a simple kinematic relation between the interface geometry and the fluid velocity. Different applications of nuclear engineering interest are reported with some available results. The present technique is capable of predicting the interface profile near the wall which is important in the reactor subchannel analysis

  7. Spatially resolved characterization in thin-film photovoltaics

    CERN Document Server

    Bokalic, Matevz

    2015-01-01

    The book is devoted to the spatial characterization of solar cells and PV modules. It is written both as a monograph as well as a succinct guide for the state-of-the-art spatial characterization techniques and approaches. Amongst the approaches discussed are visual imaging, electro- and photo-luminescence imaging, thermography, and light beam induced mapping techniques. Emphasis is given on the luminescence image acquisition and interpretation due to its great potential. Characterization techniques are accompanied by simulation tools. The contents are aimed at a readership of students and s

  8. Spatial Analysis Of Human Capital Structures

    Directory of Open Access Journals (Sweden)

    Gajdos Artur

    2014-12-01

    Full Text Available The main purpose of this paper is to analyse the interdependence between labour productivity and the occupational structure of human capital in a spatial cross-section. Research indicates (see Fischer 2009 the possibility to assess the impact of the quality of human capital (measured by means of the level of education on labour productivity in a spatial cross-section.

  9. Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

    Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

  10. An operational modal analysis method in frequency and spatial domain

    Science.gov (United States)

    Wang, Tong; Zhang, Lingmi; Tamura, Yukio

    2005-12-01

    A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified. Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

  11. A methodological comparison of customer service analysis techniques

    Science.gov (United States)

    James Absher; Alan Graefe; Robert Burns

    2003-01-01

    Techniques used to analyze customer service data need to be studied. Two primary analysis protocols, importance-performance analysis (IP) and gap score analysis (GA), are compared in a side-by-side comparison using data from two major customer service research projects. A central concern is what, if any, conclusion might be different due solely to the analysis...

  12. Spatial arrangement of faults and opening-mode fractures

    Science.gov (United States)

    Laubach, S. E.; Lamarche, J.; Gauthier, B. D. M.; Dunne, W. M.; Sanderson, David J.

    2018-03-01

    Spatial arrangement is a fundamental characteristic of fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings. Five papers describe new methods and improvements of existing techniques to quantify spatial arrangement. One study unravels the time evolution of opening-mode fracture spatial arrangement, which are data needed to compare natural patterns with progressive fracture growth in kinematic and mechanical models. Three papers investigate the role of evolving diagenesis in localizing fractures by mechanical stratigraphy and nine discuss opening-mode fracture spatial arrangement. Two papers show the relevance of complex cluster patterns to unconventional reservoirs through examples of fractures in tight gas sandstone horizontal wells, and a study of fracture arrangement in shale. Four papers demonstrate the roles of folds in fracture localization and the development spatial patterns. One paper models along-fault friction and fluid pressure and their effects on fault-related fracture arrangement. Contributions address deformation band patterns in carbonate rocks and fault size and arrangement above a detachment fault. Three papers describe fault and fracture arrangements in basement terrains, and three document fracture patterns in shale. This collection of papers points toward improvement in field methods, continuing improvements in computer-based data analysis and creation of synthetic fracture patterns, and opportunities for further understanding fault and fracture attributes in

  13. Radar-raingauge data combination techniques: a revision and analysis of their suitability for urban hydrology.

    Science.gov (United States)

    Wang, Li-Pen; Ochoa-Rodríguez, Susana; Simões, Nuno Eduardo; Onof, Christian; Maksimović, Cedo

    2013-01-01

    The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar measurements using raingauge data, which provide accurate point rainfall information. Several gauge-based radar rainfall adjustment techniques have been developed and mainly applied at coarser spatial and temporal scales; however, their suitability for small-scale urban hydrology is seldom explored. In this paper a review of gauge-based adjustment techniques is first provided. After that, two techniques, respectively based upon the ideas of mean bias reduction and error variance minimisation, were selected and tested using as case study an urban catchment (∼8.65 km(2)) in North-East London. The radar rainfall estimates of four historical events (2010-2012) were adjusted using in situ raingauge estimates and the adjusted rainfall fields were applied to the hydraulic model of the study area. The results show that both techniques can effectively reduce mean bias; however, the technique based upon error variance minimisation can in general better reproduce the spatial and temporal variability of rainfall, which proved to have a significant impact on the subsequent hydraulic outputs. This suggests that error variance minimisation based methods may be more appropriate for urban-scale hydrological applications.

  14. Analysis of the impact of immigration on labour market using spatial models

    Science.gov (United States)

    Polonyankina, Tatiana

    2017-07-01

    This paper investigates the impact of immigration on employment and unemployment of a host country. The question to answer is: How does employment/unemployment in the host country change after an increase in number of immigrants? The analysis is taking into account only legal immigrants in recession period. The model is combining classical regression of cross-sectional data with spatial econometrics models where cross-section dependencies are captured by a spatial matrix. The intention is by using spatial models analyse the sensitivity of employment/unemployment rate on change in a share of immigration in a region. The used panel data are based on the Labour force survey and on available macro data in Eurostat for 3 European countries (Germany, Austria and Czech Republic) grouped into cells by NUTS regions in a recession period.

  15. Automated thermal mapping techniques using chromatic image analysis

    Science.gov (United States)

    Buck, Gregory M.

    1989-01-01

    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  16. Modular techniques for dynamic fault-tree analysis

    Science.gov (United States)

    Patterson-Hine, F. A.; Dugan, Joanne B.

    1992-01-01

    It is noted that current approaches used to assess the dependability of complex systems such as Space Station Freedom and the Air Traffic Control System are incapable of handling the size and complexity of these highly integrated designs. A novel technique for modeling such systems which is built upon current techniques in Markov theory and combinatorial analysis is described. It enables the development of a hierarchical representation of system behavior which is more flexible than either technique alone. A solution strategy which is based on an object-oriented approach to model representation and evaluation is discussed. The technique is virtually transparent to the user since the fault tree models can be built graphically and the objects defined automatically. The tree modularization procedure allows the two model types, Markov and combinatoric, to coexist and does not require that the entire fault tree be translated to a Markov chain for evaluation. This effectively reduces the size of the Markov chain required and enables solutions with less truncation, making analysis of longer mission times possible. Using the fault-tolerant parallel processor as an example, a model is built and solved for a specific mission scenario and the solution approach is illustrated in detail.

  17. Spatial econometric analysis of factors influencing regional energy efficiency in China.

    Science.gov (United States)

    Song, Malin; Chen, Yu; An, Qingxian

    2018-05-01

    Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

  18. Spatially variant periodic structures in electromagnetics

    Science.gov (United States)

    Rumpf, Raymond C.; Pazos, Javier J.; Digaum, Jennefir L.; Kuebler, Stephen M.

    2015-01-01

    Spatial transforms are a popular technique for designing periodic structures that are macroscopically inhomogeneous. The structures are often required to be anisotropic, provide a magnetic response, and to have extreme values for the constitutive parameters in Maxwell's equations. Metamaterials and photonic crystals are capable of providing these, although sometimes only approximately. The problem still remains about how to generate the geometry of the final lattice when it is functionally graded, or spatially varied. This paper describes a simple numerical technique to spatially vary any periodic structure while minimizing deformations to the unit cells that would weaken or destroy the electromagnetic properties. New developments in this algorithm are disclosed that increase efficiency, improve the quality of the lattices and provide the ability to design aplanatic metasurfaces. The ability to spatially vary a lattice in this manner enables new design paradigms that are not possible using spatial transforms, three of which are discussed here. First, spatially variant self-collimating photonic crystals are shown to flow unguided waves around very tight bends using ordinary materials with low refractive index. Second, multi-mode waveguides in spatially variant band gap materials are shown to guide waves around bends without mixing power between the modes. Third, spatially variant anisotropic materials are shown to sculpt the near-field around electric components. This can be used to improve electromagnetic compatibility between components in close proximity. PMID:26217058

  19. Key-space analysis of double random phase encryption technique

    Science.gov (United States)

    Monaghan, David S.; Gopinathan, Unnikrishnan; Naughton, Thomas J.; Sheridan, John T.

    2007-09-01

    We perform a numerical analysis on the double random phase encryption/decryption technique. The key-space of an encryption technique is the set of possible keys that can be used to encode data using that technique. In the case of a strong encryption scheme, many keys must be tried in any brute-force attack on that technique. Traditionally, designers of optical image encryption systems demonstrate only how a small number of arbitrary keys cannot decrypt a chosen encrypted image in their system. However, this type of demonstration does not discuss the properties of the key-space nor refute the feasibility of an efficient brute-force attack. To clarify these issues we present a key-space analysis of the technique. For a range of problem instances we plot the distribution of decryption errors in the key-space indicating the lack of feasibility of a simple brute-force attack.

  20. Techniques and Applications of Urban Data Analysis

    KAUST Repository

    AlHalawani, Sawsan N.

    2016-05-26

    Digitization and characterization of urban spaces are essential components as we move to an ever-growing ’always connected’ world. Accurate analysis of such digital urban spaces has become more important as we continue to get spatial and social context-aware feedback and recommendations in our daily activities. Modeling and reconstruction of urban environments have thus gained unprecedented importance in the last few years. Such analysis typically spans multiple disciplines, such as computer graphics, and computer vision as well as architecture, geoscience, and remote sensing. Reconstructing an urban environment usually requires an entire pipeline consisting of different tasks. In such a pipeline, data analysis plays a strong role in acquiring meaningful insights from the raw data. This dissertation primarily focuses on the analysis of various forms of urban data and proposes a set of techniques to extract useful information, which is then used for different applications. The first part of this dissertation presents a semi-automatic framework to analyze facade images to recover individual windows along with their functional configurations such as open or (partially) closed states. The main advantage of recovering both the repetition patterns of windows and their individual deformation parameters is to produce a factored facade representation. Such a factored representation enables a range of applications including interactive facade images, improved multi-view stereo reconstruction, facade-level change detection, and novel image editing possibilities. The second part of this dissertation demonstrates the importance of a layout configuration on its performance. As a specific application scenario, I investigate the interior layout of warehouses wherein the goal is to assign items to their storage locations while reducing flow congestion and enhancing the speed of order picking processes. The third part of the dissertation proposes a method to classify cities

  1. Science with High Spatial Resolution Far-Infrared Data

    Science.gov (United States)

    Terebey, Susan (Editor); Mazzarella, Joseph M. (Editor)

    1994-01-01

    The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants.

  2. TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION

    Directory of Open Access Journals (Sweden)

    А. А. Vershinina

    2014-01-01

    Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.

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

    Science.gov (United States)

    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. Copyright

  4. Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis

    DEFF Research Database (Denmark)

    Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner

    2017-01-01

    This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel ...... in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.......This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel...... photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices...

  5. Usefulness of 3D-CE renal artery MRA using parallel imaging with array spatial sensitivity encoding technique (ASSET)

    International Nuclear Information System (INIS)

    Shibasaki, Toshiro; Seno Masafumi; Takoi, Kunihiro; Sato, Hirofumi; Hino, Tsuyoshi

    2003-01-01

    In this study of 3D contrast enhanced MR angiography of the renal artery using the array spatial sensitivity encoding technique (ASSET), the acquisition time per 1 phase shortened fairly. And using the technique of spectral inversion at lipids (SPECIAL) together with ASSET, the quality of image was improved by emphasizing the contrast. The timing of acquisition was determined by the test injection. We started acquiring the MR angiography 2 seconds after the arrival of maximum enhancement of the test injection at the upper abdominal aorta near the renal artery. As a result parenchymal enhancement was not visible and depiction of the segmental artery was possible in 14 (82%) of 17 patients. At the present time we consider it better not to use the Fractional number of excitation (NEX) together with ASSET, as it may cause various artifacts. (author)

  6. Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

    Science.gov (United States)

    Dostal, P.; Krasula, L.; Klima, M.

    2012-06-01

    Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

  7. Development of fault diagnostic technique using reactor noise analysis

    International Nuclear Information System (INIS)

    Park, Jin Ho; Kim, J. S.; Oh, I. S.; Ryu, J. S.; Joo, Y. S.; Choi, S.; Yoon, D. B.

    1999-04-01

    The ultimate goal of this project is to establish the analysis technique to diagnose the integrity of reactor internals using reactor noise. The reactor noise analyses techniques for the PWR and CANDU NPP(Nuclear Power Plants) were established by which the dynamic characteristics of reactor internals and SPND instrumentations could be identified, and the noise database corresponding to each plant(both Korean and foreign one) was constructed and compared. Also the change of dynamic characteristics of the Ulchin 1 and 2 reactor internals were simulated under presumed fault conditions. Additionally portable reactor noise analysis system was developed so that real time noise analysis could directly be able to be performed at plant site. The reactor noise analyses techniques developed and the database obtained from the fault simulation, can be used to establish a knowledge based expert system to diagnose the NPP's abnormal conditions. And the portable reactor noise analysis system may be utilized as a substitute for plant IVMS(Internal Vibration Monitoring System). (author)

  8. Development of fault diagnostic technique using reactor noise analysis

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jin Ho; Kim, J. S.; Oh, I. S.; Ryu, J. S.; Joo, Y. S.; Choi, S.; Yoon, D. B

    1999-04-01

    The ultimate goal of this project is to establish the analysis technique to diagnose the integrity of reactor internals using reactor noise. The reactor noise analyses techniques for the PWR and CANDU NPP(Nuclear Power Plants) were established by which the dynamic characteristics of reactor internals and SPND instrumentations could be identified, and the noise database corresponding to each plant(both Korean and foreign one) was constructed and compared. Also the change of dynamic characteristics of the Ulchin 1 and 2 reactor internals were simulated under presumed fault conditions. Additionally portable reactor noise analysis system was developed so that real time noise analysis could directly be able to be performed at plant site. The reactor noise analyses techniques developed and the database obtained from the fault simulation, can be used to establish a knowledge based expert system to diagnose the NPP's abnormal conditions. And the portable reactor noise analysis system may be utilized as a substitute for plant IVMS(Internal Vibration Monitoring System). (author)

  9. Spatial analysis of radiocesium food contamination in rural settlements of Belarus

    International Nuclear Information System (INIS)

    Krivoruchko, K.; Makejchik, A.

    1997-01-01

    An analysis of 53207 records of cesium 137 contents in 83 types of food products obtained in 1993 in Belarus was carried out. Internal exposure from intake of eight selected food components has been estimated. To map the non-uniformly distributed data, different geostatistical approaches are used. The results of spatial analysis of long term internal dose loads on populations under high radiation risk can be used in decision making. (authors). 9 refs., 1 tab., 4 figs

  10. Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

    Science.gov (United States)

    Gaitan, S.; ten Veldhuis, J. A. E.

    2015-06-01

    Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

  11. An analysis of spatial representativeness of air temperature monitoring stations

    Science.gov (United States)

    Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen

    2018-05-01

    Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.

  12. Model Interpretation of Topological Spatial Analysis for the Visually Impaired (Blind Implemented in Google Maps

    Directory of Open Access Journals (Sweden)

    Marcelo Franco Porto

    2013-06-01

    Full Text Available The technological innovations promote the availability of geographic information on the Internet through Web GIS such as Google Earth and Google Maps. These systems contribute to the teaching and diffusion of geographical knowledge that instigates the recognition of the space we live in, leading to the creation of a spatial identity. In these products available on the Web, the interpretation and analysis of spatial information gives priority to one of the human senses: vision. Due to the fact that this representation of information is transmitted visually (image and vectors, a portion of the population is excluded from part of this knowledge because categories of analysis of geographic data such as borders, territory, and space can only be understood by people who can see. This paper deals with the development of a model of interpretation of topological spatial analysis based on the synthesis of voice and sounds that can be used by the visually impaired (blind.The implementation of a prototype in Google Maps and the usability tests performed are also examined. For the development work it was necessary to define the model of topological spatial analysis, focusing on computational implementation, which allows users to interpret the spatial relationships of regions (countries, states and municipalities, recognizing its limits, neighborhoods and extension beyond their own spatial relationships . With this goal in mind, several interface and usability guidelines were drawn up to be used by the visually impaired (blind. We conducted a detailed study of the Google Maps API (Application Programming Interface, which was the environment selected for prototype development, and studied the information available for the users of that system. The prototype was developed based on the synthesis of voice and sounds that implement the proposed model in C # language and in .NET environment. To measure the efficiency and effectiveness of the prototype, usability

  13. Spatial segregation in eastern North Pacific skate assemblages.

    Directory of Open Access Journals (Sweden)

    Joseph J Bizzarro

    Full Text Available Skates (Rajiformes: Rajoidei are common mesopredators in marine benthic communities. The spatial associations of individual species and the structure of assemblages are of considerable importance for effective monitoring and management of exploited skate populations. This study investigated the spatial associations of eastern North Pacific (ENP skates in continental shelf and upper continental slope waters of two regions: central California and the western Gulf of Alaska. Long-term survey data were analyzed using GIS/spatial analysis techniques and regression models to determine distribution (by depth, temperature, and latitude/longitude and relative abundance of the dominant species in each region. Submersible video data were incorporated for California to facilitate habitat association analysis. We addressed three main questions: 1 Are there regions of differential importance to skates?, 2 Are ENP skate assemblages spatially segregated?, and 3 When skates co-occur, do they differ in size? Skate populations were highly clustered in both regions, on scales of 10s of kilometers; however, high-density regions (i.e., hot spots were segregated among species. Skate densities and frequencies of occurrence were substantially lower in Alaska as compared to California. Although skates are generally found on soft sediment habitats, Raja rhina exhibited the strongest association with mixed substrates, and R. stellulata catches were greatest on rocky reefs. Size segregation was evident in regions where species overlapped substantially in geographic and depth distribution (e.g., R. rhina and Bathyraja kincaidii off California; B. aleutica and B. interrupta in the Gulf of Alaska. Spatial niche differentiation in skates appears to be more pronounced than previously reported.

  14. Spatial segregation in eastern North Pacific skate assemblages.

    Science.gov (United States)

    Bizzarro, Joseph J; Broms, Kristin M; Logsdon, Miles G; Ebert, David A; Yoklavich, Mary M; Kuhnz, Linda A; Summers, Adam P

    2014-01-01

    Skates (Rajiformes: Rajoidei) are common mesopredators in marine benthic communities. The spatial associations of individual species and the structure of assemblages are of considerable importance for effective monitoring and management of exploited skate populations. This study investigated the spatial associations of eastern North Pacific (ENP) skates in continental shelf and upper continental slope waters of two regions: central California and the western Gulf of Alaska. Long-term survey data were analyzed using GIS/spatial analysis techniques and regression models to determine distribution (by depth, temperature, and latitude/longitude) and relative abundance of the dominant species in each region. Submersible video data were incorporated for California to facilitate habitat association analysis. We addressed three main questions: 1) Are there regions of differential importance to skates?, 2) Are ENP skate assemblages spatially segregated?, and 3) When skates co-occur, do they differ in size? Skate populations were highly clustered in both regions, on scales of 10s of kilometers; however, high-density regions (i.e., hot spots) were segregated among species. Skate densities and frequencies of occurrence were substantially lower in Alaska as compared to California. Although skates are generally found on soft sediment habitats, Raja rhina exhibited the strongest association with mixed substrates, and R. stellulata catches were greatest on rocky reefs. Size segregation was evident in regions where species overlapped substantially in geographic and depth distribution (e.g., R. rhina and Bathyraja kincaidii off California; B. aleutica and B. interrupta in the Gulf of Alaska). Spatial niche differentiation in skates appears to be more pronounced than previously reported.

  15. Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

    Science.gov (United States)

    Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

    2014-11-01

    Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.

  16. Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

    International Nuclear Information System (INIS)

    Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

    2014-01-01

    Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as M uon Central Slice Theorem . Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction

  17. Multivariate Analysis Techniques for Optimal Vision System Design

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara

    The present thesis considers optimization of the spectral vision systems used for quality inspection of food items. The relationship between food quality, vision based techniques and spectral signature are described. The vision instruments for food analysis as well as datasets of the food items...... used in this thesis are described. The methodological strategies are outlined including sparse regression and pre-processing based on feature selection and extraction methods, supervised versus unsupervised analysis and linear versus non-linear approaches. One supervised feature selection algorithm...... (SSPCA) and DCT based characterization of the spectral diffused reflectance images for wavelength selection and discrimination. These methods together with some other state-of-the-art statistical and mathematical analysis techniques are applied on datasets of different food items; meat, diaries, fruits...

  18. Chromatographic Techniques for Rare Earth Elements Analysis

    Science.gov (United States)

    Chen, Beibei; He, Man; Zhang, Huashan; Jiang, Zucheng; Hu, Bin

    2017-04-01

    The present capability of rare earth element (REE) analysis has been achieved by the development of two instrumental techniques. The efficiency of spectroscopic methods was extraordinarily improved for the detection and determination of REE traces in various materials. On the other hand, the determination of REEs very often depends on the preconcentration and separation of REEs, and chromatographic techniques are very powerful tools for the separation of REEs. By coupling with sensitive detectors, many ambitious analytical tasks can be fulfilled. Liquid chromatography is the most widely used technique. Different combinations of stationary phases and mobile phases could be used in ion exchange chromatography, ion chromatography, ion-pair reverse-phase chromatography and some other techniques. The application of gas chromatography is limited because only volatile compounds of REEs can be separated. Thin-layer and paper chromatography are techniques that cannot be directly coupled with suitable detectors, which limit their applications. For special demands, separations can be performed by capillary electrophoresis, which has very high separation efficiency.

  19. Ultrasonic motion analysis system - measurement of temporal and spatial gait parameters

    NARCIS (Netherlands)

    Huitema, RB; Hof, AL; Postema, K

    The duration of stance and swing phase and step and stride length are important parameters in human gait. In this technical note a low-cost ultrasonic motion analysis system is described that is capable of measuring these temporal and spatial parameters while subjects walk on the floor. By using the

  20. CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

    Directory of Open Access Journals (Sweden)

    Eduarda Martiniano de Oliveira Silveira

    2017-12-01

    Full Text Available Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index was generated in an area of Brazilian amazon tropical forest (1,000 km².We selected samples (1 x 1 km from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property and range (φ-the length scale of the spatial structures of objects parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA approaches.

  1. Generation of future potential scenarios in an Alpine Catchment by applying bias-correction techniques, delta-change approaches and stochastic Weather Generators at different spatial scale. Analysis of their influence on basic and drought statistics.

    Science.gov (United States)

    Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio

    2017-04-01

    and drought statistic of the historical data. A multi-objective analysis using basic statistics (mean, standard deviation and asymmetry coefficient) and droughts statistics (duration, magnitude and intensity) has been performed to identify which models are better in terms of goodness of fit to reproduce the historical series. The drought statistics have been obtained from the Standard Precipitation index (SPI) series using the Theory of Runs. This analysis allows discriminate the best RCM and the best combination of model and correction technique in the bias-correction method. We have also analyzed the possibilities of using different Stochastic Weather Generators to approximate the basic and droughts statistics of the historical series. These analyses have been performed in our case study in a lumped and in a distributed way in order to assess its sensibility to the spatial scale. The statistic of the future temperature series obtained with different ensemble options are quite homogeneous, but the precipitation shows a higher sensibility to the adopted method and spatial scale. The global increment in the mean temperature values are 31.79 %, 31.79 %, 31.03 % and 31.74 % for the distributed bias-correction, distributed delta-change, lumped bias-correction and lumped delta-change ensembles respectively and in the precipitation they are -25.48 %, -28.49 %, -26.42 % and -27.35% respectively. Acknowledgments: This research work has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 and CORDEX projects for the data provided for this study and the R package qmap.

  2. Neutron activation analysis: an emerging technique for conservation/preservation

    International Nuclear Information System (INIS)

    Sayre, E.V.

    1976-01-01

    The diverse applications of neutron activation in analysis, preservation, and documentation of art works and artifacts are described with illustrations for each application. The uses of this technique to solve problems of attribution and authentication, to reveal the inner structure and composition of art objects, and, in some instances to recreate details of the objects are described. A brief discussion of the theory and techniques of neutron activation analysis is also included

  3. Multidimensional Analysis and Location Intelligence Application for Spatial Data Warehouse Hotspot in Indonesia using SpagoBI

    Science.gov (United States)

    Uswatun Hasanah, Gamma; Trisminingsih, Rina

    2016-01-01

    Spatial data warehouse refers to data warehouse which has a spatial component that represents the geographic location of the position or an object on the Earth's surface. Spatial data warehouse can be visualized in the form of a crosstab tables, graphs, and maps. Spatial data warehouse of hotspot in Indonesia has been constructed by researchers from FIRM NASA 2006-2015. This research develops multidimensional analysis module and location intelligence module using SpagoBI. The multidimensional analysis module is able to visualize online analytical processing (OLAP). The location intelligence module creates dynamic map visualization in map zone and map point. Map zone can display the different colors based on the number of hotspot in each region and map point can display different sizes of the point to represent the number of hotspots in each region. This research is expected to facilitate users in the presentation of hotspot data as needed.

  4. Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

    Science.gov (United States)

    Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

    2016-12-01

    Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

  5. Diffraction analysis of customized illumination technique

    Science.gov (United States)

    Lim, Chang-Moon; Kim, Seo-Min; Eom, Tae-Seung; Moon, Seung Chan; Shin, Ki S.

    2004-05-01

    Various enhancement techniques such as alternating PSM, chrome-less phase lithography, double exposure, etc. have been considered as driving forces to lead the production k1 factor towards below 0.35. Among them, a layer specific optimization of illumination mode, so-called customized illumination technique receives deep attentions from lithographers recently. A new approach for illumination customization based on diffraction spectrum analysis is suggested in this paper. Illumination pupil is divided into various diffraction domains by comparing the similarity of the confined diffraction spectrum. Singular imaging property of individual diffraction domain makes it easier to build and understand the customized illumination shape. By comparing the goodness of image in each domain, it was possible to achieve the customized shape of illumination. With the help from this technique, it was found that the layout change would not gives the change in the shape of customized illumination mode.

  6. Spatial distribution of Munida intermedia and M. sarsi (crustacea: Anomura) on the Galician continental shelf (NW Spain): Application of geostatistical analysis

    Science.gov (United States)

    Freire, J.; González-Gurriarán, E.; Olaso, I.

    1992-12-01

    Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.

  7. Spatial-temporal analysis of wind power forecast errors for West-Coast Norway

    Energy Technology Data Exchange (ETDEWEB)

    Revheim, Paal Preede; Beyer, Hans Georg [Agder Univ. (UiA), Grimstad (Norway). Dept. of Engineering Sciences

    2012-07-01

    In this paper the spatial-temporal structure of forecast errors for wind power in West-Coast Norway is analyzed. Starting on the qualitative analysis of the forecast error reduction, with respect to single site data, for the lumped conditions of groups of sites the spatial and temporal correlations of the wind power forecast errors within and between the same groups are studied in detail. Based on this, time-series regression models to be used to analytically describe the error reduction are set up. The models give an expected reduction in forecast error between 48.4% and 49%. (orig.)

  8. Spatial Modulation in the Underwater Acoustic Communication Channel

    National Research Council Canada - National Science Library

    Kilfoyle, Daniel

    2000-01-01

    .... The technique, termed spatial modulation, seeks to control the spatial distribution of signal energy such that multiple parallel communication channels are supported by the single, physical ocean channel...

  9. Input-output analysis of CO2 emissions embodied in trade. The effects of spatial aggregation

    International Nuclear Information System (INIS)

    Su, Bin; Ang, B.W.

    2010-01-01

    Energy-related CO 2 emissions embodied in international trade have been widely studied by researchers using the environmental input-output analysis framework. It is well known that both sector aggregation and spatial aggregation affect the results obtained in such studies. With regard to the latter, past studies are often conducted at the national level irrespective of country or economy size. For a large economy with the needed data, studies may be conducted at different levels of spatial aggregation. We examine this problem analytically by extending the work of Su et al. ([Su, B., Huang, H.C., Ang, B.W., Zhou, P., 2010. Input-output analysis of CO 2 emissions embodied in trade: The effects of sector aggregation. Energy Economics 32 (1), 166-175.]) on sector aggregation. We present a numerical example using the data of China and by dividing the country into eight regions. It is found that the results are highly dependent on spatial aggregation. Our study shows that for a large country like China it is meaningful to look into the effect of spatial aggregation. (author)

  10. Decision Analysis Technique

    Directory of Open Access Journals (Sweden)

    Hammad Dabo Baba

    2014-01-01

    Full Text Available One of the most significant step in building structure maintenance decision is the physical inspection of the facility to be maintained. The physical inspection involved cursory assessment of the structure and ratings of the identified defects based on expert evaluation. The objective of this paper is to describe present a novel approach to prioritizing the criticality of physical defects in a residential building system using multi criteria decision analysis approach. A residential building constructed in 1985 was considered in this study. Four criteria which includes; Physical Condition of the building system (PC, Effect on Asset (EA, effect on Occupants (EO and Maintenance Cost (MC are considered in the inspection. The building was divided in to nine systems regarded as alternatives. Expert's choice software was used in comparing the importance of the criteria against the main objective, whereas structured Proforma was used in quantifying the defects observed on all building systems against each criteria. The defects severity score of each building system was identified and later multiplied by the weight of the criteria and final hierarchy was derived. The final ranking indicates that, electrical system was considered the most critical system with a risk value of 0.134 while ceiling system scored the lowest risk value of 0.066. The technique is often used in prioritizing mechanical equipment for maintenance planning. However, result of this study indicates that the technique could be used in prioritizing building systems for maintenance planning

  11. EFFECTS OF HETEROGENIETY ON SPATIAL PATTERN ANALYSIS OF WILD PISTACHIO TREES IN ZAGROS WOODLANDS, IRAN

    Directory of Open Access Journals (Sweden)

    Y. Erfanifard

    2014-10-01

    Full Text Available 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.

  12. Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

    Science.gov (United States)

    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.

  13. Evaluating patterns of a white-band disease (WBD outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

    Directory of Open Access Journals (Sweden)

    Jennifer A Lentz

    Full Text Available BACKGROUND: Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD, a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. METHODOLOGY/PRINCIPAL FINDINGS: Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect and transect-level (presence/absence of WBD within transects data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1 at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. CONCLUSIONS: As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other

  14. Evaluating patterns of a white-band disease (WBD) outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

    Science.gov (United States)

    Lentz, Jennifer A; Blackburn, Jason K; Curtis, Andrew J

    2011-01-01

    Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD), a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect) and transect-level (presence/absence of WBD within transects) data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1) at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other coral disease studies, as well as, improve reef conservation and management.

  15. Site characterization: a spatial estimation approach

    International Nuclear Information System (INIS)

    Candy, J.V.; Mao, N.

    1980-10-01

    In this report the application of spatial estimation techniques or kriging to groundwater aquifers and geological borehole data is considered. The adequacy of these techniques to reliably develop contour maps from various data sets is investigated. The estimator is developed theoretically in a simplified fashion using vector-matrix calculus. The practice of spatial estimation is discussed and the estimator is then applied to two groundwater aquifer systems and used also to investigate geological formations from borehole data. It is shown that the estimator can provide reasonable results when designed properly

  16. Magnetic Resonance Microscopy Spatially Resolved NMR Techniques and Applications

    CERN Document Server

    Codd, Sarah

    2008-01-01

    This handbook and ready reference covers materials science applications as well as microfluidic, biomedical and dental applications and the monitoring of physicochemical processes. It includes the latest in hardware, methodology and applications of spatially resolved magnetic resonance, such as portable imaging and single-sided spectroscopy. For materials scientists, spectroscopists, chemists, physicists, and medicinal chemists.

  17. 48 CFR 15.404-1 - Proposal analysis techniques.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Proposal analysis techniques. 15.404-1 Section 15.404-1 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION... assistance of other experts to ensure that an appropriate analysis is performed. (6) Recommendations or...

  18. Environmental Risk Assessment: Spatial Analysis of Chemical Hazards and Risks in South Korea

    Science.gov (United States)

    Yu, H.; Heo, S.; Kim, M.; Lee, W. K.; Jong-Ryeul, S.

    2017-12-01

    This study identified chemical hazard and risk levels in Korea by analyzing the spatial distribution of chemical factories and accidents. The number of chemical factories and accidents in 5-km2 grids were used as the attribute value for spatial analysis. First, semi-variograms were conducted to examine spatial distribution patterns and to identify spatial autocorrelation of chemical factories and accidents. Semi-variograms explained that the spatial distribution of chemical factories and accidents were spatially autocorrelated. Second, the results of the semi-variograms were used in Ordinary Kriging to estimate chemical hazard and risk level. The level values were extracted from the Ordinary Kriging result and their spatial similarity was examined by juxtaposing the two values with respect to their location. Six peaks were identified in both the hazard and risk estimation result, and the peaks correlated with major cities in Korea. Third, the estimated hazard and risk levels were classified with geometrical interval and could be classified into four quadrants: Low Hazard and Low Risk (LHLR), Low Hazard and High Risk (LHHR), High Hazard and Low Risk (HHLR), and High Hazard and High Risk (HHHR). The 4 groups identified different chemical safety management issues in Korea; relatively safe LHLR group, many chemical reseller factories were found in HHLR group, chemical transportation accidents were in the LHHR group, and an abundance of factories and accidents were in the HHHR group. Each quadrant represented different safety management obstacles in Korea, and studying spatial differences can support the establishment of an efficient risk management plan.

  19. Graph Theory Roots of Spatial Operators for Kinematics and Dynamics

    Science.gov (United States)

    Jain, Abhinandan

    2011-01-01

    Spatial operators have been used to analyze the dynamics of robotic multibody systems and to develop novel computational dynamics algorithms. Mass matrix factorization, inversion, diagonalization, and linearization are among several new insights obtained using such operators. While initially developed for serial rigid body manipulators, the spatial operators and the related mathematical analysis have been shown to extend very broadly including to tree and closed topology systems, to systems with flexible joints, links, etc. This work uses concepts from graph theory to explore the mathematical foundations of spatial operators. The goal is to study and characterize the properties of the spatial operators at an abstract level so that they can be applied to a broader range of dynamics problems. The rich mathematical properties of the kinematics and dynamics of robotic multibody systems has been an area of strong research interest for several decades. These properties are important to understand the inherent physical behavior of systems, for stability and control analysis, for the development of computational algorithms, and for model development of faithful models. Recurring patterns in spatial operators leads one to ask the more abstract question about the properties and characteristics of spatial operators that make them so broadly applicable. The idea is to step back from the specific application systems, and understand more deeply the generic requirements and properties of spatial operators, so that the insights and techniques are readily available across different kinematics and dynamics problems. In this work, techniques from graph theory were used to explore the abstract basis for the spatial operators. The close relationship between the mathematical properties of adjacency matrices for graphs and those of spatial operators and their kernels were established. The connections hold across very basic requirements on the system topology, the nature of the component

  20. Source-jerk analysis using a semi-explicit inverse kinetic technique

    International Nuclear Information System (INIS)

    Spriggs, G.D.; Pederson, R.A.

    1985-01-01

    A method is proposed for measuring the effective reproduction factor, k, in subcritical systems. The method uses the transient response of a subcritical system to the sudden removal of an extraneous neutron source (i.e., a source jerk). The response is analyzed using an inverse kinetic technique that least-squares fits the exact analytical solution corresponding to a source-jerk transient as derived from the point-reactor model. It has been found that the technique can provide an accurate means of measuring k in systems that are close to critical (i.e., 0.95 < k < 1.0). As a system becomes more subcritical (i.e., k << 1.0) spatial effects can introduce significant biases depending on the source and detector positions. However, methods are available that can correct for these biases and, hence, can allow measuring subcriticality in systems with k as low as 0.5. 12 refs., 3 figs

  1. Source-jerk analysis using a semi-explicit inverse kinetic technique

    International Nuclear Information System (INIS)

    Spriggs, G.D.; Pederson, R.A.

    1985-01-01

    A method is proposed for measuring the effective reproduction factor, k, in subcritical systems. The method uses the transient responses of a subcritical system to the sudden removal of an extraneous neutron source (i.e., a source jerk). The response is analyzed using an inverse kinetic technique that least-squares fits the exact analytical solution corresponding to a source-jerk transient as derived from the point-reactor model. It has been found that the technique can provide an accurate means of measuring k in systems that are close to critical (i.e., 0.95 < k < 1.0). As a system becomes more subcritical (i.e., k << 1.0) spatial effects can introduce significant biases depending on the source and detector positions. However, methods are available that can correct for these biases and, hence, can allow measuring subcriticality in systems with k as low as 0.5

  2. Applications Of Binary Image Analysis Techniques

    Science.gov (United States)

    Tropf, H.; Enderle, E.; Kammerer, H. P.

    1983-10-01

    After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.

  3. Spatial normalization of array-CGH data

    Directory of Open Access Journals (Sweden)

    Brennetot Caroline

    2006-05-01

    Full Text Available Abstract Background Array-based comparative genomic hybridization (array-CGH is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, normalization is required to correct for experimental artifacts while preserving the true biological signal. We investigated various sources of systematic variation in array-CGH data and identified two distinct types of spatial effect of no biological relevance as the predominant experimental artifacts: continuous spatial gradients and local spatial bias. Local spatial bias affects a large proportion of arrays, and has not previously been considered in array-CGH experiments. Results We show that existing normalization techniques do not correct these spatial effects properly. We therefore developed an automatic method for the spatial normalization of array-CGH data. This method makes it possible to delineate and to eliminate and/or correct areas affected by spatial bias. It is based on the combination of a spatial segmentation algorithm called NEM (Neighborhood Expectation Maximization and spatial trend estimation. We defined quality criteria for array-CGH data, demonstrating significant improvements in data quality with our method for three data sets coming from two different platforms (198, 175 and 26 BAC-arrays. Conclusion We have designed an automatic algorithm for the spatial normalization of BAC CGH-array data, preventing the misinterpretation of experimental artifacts as biologically relevant outliers in the genomic profile. This algorithm is implemented in the R package MANOR (Micro-Array NORmalization, which is described at http://bioinfo.curie.fr/projects/manor and available from the Bioconductor site http://www.bioconductor.org. It can also be tested on the CAPweb bioinformatics platform at http://bioinfo.curie.fr/CAPweb.

  4. Spatial econometrics using microdata

    CERN Document Server

    Dubé, Jean

    2014-01-01

    This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares appr

  5. ANALYSIS OF SPATIAL CHANGES IN GROUNDWATER RETENTION FOR THE ODER VALLEY IN THE MALCZYCE REGION

    Directory of Open Access Journals (Sweden)

    Edyta Nowicka

    2015-10-01

    Full Text Available The paper presents the analysis of spatial changes of groundwater retention for a part of the Oder valley situated below the barrage in Brzeg Dolny. For the analysis of selected monthly average elevations of the groundwater table of the selected measuring points (32 piezometers located in the area described, and 7 gauges on the Oder river, Średzka Woda, Jeziorka and Nowy Rów. The change of groundwater retention is presented in spatial terms for vegetation periods of years: 2010, 2011 and 2012. The database was made interpolating the groundwater table elevation for the area in question. On this basis, differences between ordinates the groundwater table were calculated. The next step was to obtain the spatial distribution of groundwater retention states and its analysis. The results show significant changes in the states of groundwater retention on the selected portion of the valley in the individual growing seasons. According to formation of changes in status of groundwater retention relative to the distance from the Odra river was analysed.

  6. A Flood Risk Assessment of Quang Nam, Vietnam Using Spatial Multicriteria Decision Analysis

    Directory of Open Access Journals (Sweden)

    Chinh Luu

    2018-04-01

    Full Text Available Vietnam is highly vulnerable to flood and storm impacts. Holistic flood risk assessment maps that adequately consider flood risk factors of hazard, exposure, and vulnerability are not available. These are vital for flood risk preparedness and disaster mitigation measures at the local scale. Unfortunately, there is a lack of knowledge about spatial multicriteria decision analysis and flood risk analysis more broadly in Vietnam. In response to this need, we identify and quantify flood risk components in Quang Nam province through spatial multicriteria decision analysis. The study presents a new approach to local flood risk assessment mapping, which combines historical flood marks with exposure and vulnerability data. The flood risk map output could assist and empower decision-makers in undertaking flood risk management activities in the province. Our study demonstrates a methodology to build flood risk assessment maps using flood mark, exposure and vulnerability data, which could be applied in other provinces in Vietnam.

  7. Determinants of the distribution and concentration of biogas production in Germany. A spatial econometric analysis

    International Nuclear Information System (INIS)

    Scholz, Lukas

    2015-01-01

    The biogas production in Germany is characterized by a heterogeneous distribution and the formation of regional centers. In the present study the determinants of the spatial distribution and concentration are analyzed with methods of spatial statistics and spatial econometrics. In addition to the consideration of ''classic'' site factors of agricultural production, the analysis here focuses on the possible relevance of agglomeration effects. The results of the work contribute to a better understanding of the regional distribution and concentration of the biogas production in Germany. [de

  8. Spatial Analysis in Determining Physical Factors of Pedestrian Space Livability, Case Study: Pedestrian Space on Jalan Kemasan, Yogyakarta

    Science.gov (United States)

    Fauzi, A. F.; Aditianata, A.

    2018-02-01

    The existence of street as a place to perform various human activities becomes an important issue nowadays. In the last few decades, cars and motorcycles dominate streets in various cities in the world. On the other hand, human activity on the street is the determinant of the city livability. Previous research has pointed out that if there is lots of human activity in the street, then the city will be interesting. Otherwise, if the street has no activity, then the city will be boring. Learning from that statement, now various cities in the world are developing the concept of livable streets. Livable streets shown by diversity of human activities conducted in the streets’ pedestrian space. In Yogyakarta, one of the streets shown diversity of human activities is Jalan Kemasan. This study attempts to determine the physical factors of pedestrian space affecting the livability in Jalan Kemasan Yogyakarta through spatial analysis. Spatial analysis was performed by overlay technique between liveable point (activity diversity) distribution map and variable distribution map. Those physical pedestrian space research variable included element of shading, street vendors, building setback, seat location, divider between street and pedestrian way, and mixed use building function. More diverse the activity of one variable, then those variable are more affected then others. Overlay result then strengthened by field observation to qualitatively ensure the deduction. In the end, this research will provide valuable input for street and pedestrian space planning that is comfortable for human activities.

  9. Spatial-temporal event detection in climate parameter imagery.

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  10. Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis

    Directory of Open Access Journals (Sweden)

    Levy Jonathan I

    2007-05-01

    Full Text Available Abstract Background There has been growing interest among exposure assessors, epidemiologists, and policymakers in the concept of "hot spots", or more broadly, the "spatial extent" of impacts from traffic-related air pollutants. This review attempts to quantitatively synthesize findings about the spatial extent under various circumstances. Methods We include both the peer-reviewed literature and government reports, and focus on four significant air pollutants: carbon monoxide, benzene, nitrogen oxides, and particulate matter (including both ultrafine particle counts and fine particle mass. From the identified studies, we extracted information about significant factors that would be hypothesized to influence the spatial extent within the study, such as the study type (e.g., monitoring, air dispersion modeling, GIS-based epidemiological studies, focus on concentrations or health risks, pollutant under study, background concentration, emission rate, and meteorological factors, as well as the study's implicit or explicit definition of spatial extent. We supplement this meta-analysis with results from some illustrative atmospheric dispersion modeling. Results We found that pollutant characteristics and background concentrations best explained variability in previously published spatial extent estimates, with a modifying influence of local meteorology, once some extreme values based on health risk estimates were removed from the analysis. As hypothesized, inert pollutants with high background concentrations had the largest spatial extent (often demonstrating no significant gradient, and pollutants formed in near-source chemical reactions (e.g., nitrogen dioxide had a larger spatial extent than pollutants depleted in near-source chemical reactions or removed through coagulation processes (e.g., nitrogen oxide and ultrafine particles. Our illustrative dispersion model illustrated the complex interplay of spatial extent definitions, emission rates

  11. Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

    Science.gov (United States)

    Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

    2018-01-01

    This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

  12. Sensitivity analysis of hybrid thermoelastic techniques

    Science.gov (United States)

    W.A. Samad; J.M. Considine

    2017-01-01

    Stress functions have been used as a complementary tool to support experimental techniques, such as thermoelastic stress analysis (TSA) and digital image correlation (DIC), in an effort to evaluate the complete and separate full-field stresses of loaded structures. The need for such coupling between experimental data and stress functions is due to the fact that...

  13. Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement

    Directory of Open Access Journals (Sweden)

    Ali Soleymani

    2014-06-01

    Full Text Available Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the ``reliable scale'' is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and

  14. Spatial and Temporal Assessment on Drug Addiction Using Multivariate Analysis and GIS

    International Nuclear Information System (INIS)

    Mohd Ekhwan Toriman; Mohd Ekhwan Toriman; Siti Nor Fazillah Abdullah; Izwan Arif Azizan; Mohd Khairul Amri Kamarudin; Roslan Umar; Nasir Mohamad

    2015-01-01

    There is a need for managing and displaying drug addiction phenomena and trend at both spatial and temporal scales. Spatial and temporal assessment on drug addiction in Terengganu was undertaken to understand the geographical area of district in the same cluster, in addition, identify the hot spot area of this problem and analysis the trend of drug addiction. Data used were topography map of Terengganu and number of drug addicted person in Terengganu by district within 10 years (2004-2013). Number of drug addicted person by district were mapped using Geographic Information system and analysed using a combination of multivariate analysis which is cluster analysis were applied to the database in order to validate the correlation between data in the same cluster. Result showed a cluster analysis for number of drug addiction by district generated three clusters which are Besut and Kuala Terengganu in cluster 1 named moderate drug addicted person (MDA), Dungun, Marang, Setiu and Hulu Terengganu in cluster 2 named lower drug addicted person (LDA) and Kemaman in cluster 3 named high drug addicted person(HDA). This analysis indicates that cluster 3 which is Kemaman is a hot spot area. These results were beneficial for stakeholder to monitor and manage this problem especially in the hot spot area which needs to be emphasized. (author)

  15. Bayesian learning for spatial filtering in an EEG-based brain-computer interface.

    Science.gov (United States)

    Zhang, Haihong; Yang, Huijuan; Guan, Cuntai

    2013-07-01

    Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

  16. Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

    Directory of Open Access Journals (Sweden)

    S. Gaitan

    2015-06-01

    Full Text Available Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

  17. The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures

    Energy Technology Data Exchange (ETDEWEB)

    Pyka, Grzegorz, E-mail: gregory.pyka@mtm.kuleuven.be [Department of Metallurgy and Materials Engineering, KU Leuven, Kasteelpark Arenberg 44 – PB2450, B-3001 Leuven (Belgium); Kerckhofs, Greet [Department of Metallurgy and Materials Engineering, KU Leuven, Kasteelpark Arenberg 44 – PB2450, B-3001 Leuven (Belgium); Biomechanics Research Unit, Université de Liege, Chemin des Chevreuils 1 - BAT 52/3, B-4000 Liège (Belgium); Schrooten, Jan; Wevers, Martine [Department of Metallurgy and Materials Engineering, KU Leuven, Kasteelpark Arenberg 44 – PB2450, B-3001 Leuven (Belgium)

    2014-01-15

    In material science microfocus X-ray computed tomography (micro-CT) is one of the most popular non-destructive techniques to visualise and quantify the internal structure of materials in 3D. Despite constant system improvements, state-of-the-art micro-CT images can still hold several artefacts typical for X-ray CT imaging that hinder further image-based processing, structural and quantitative analysis. For example spatial resolution is crucial for an appropriate characterisation as the voxel size essentially influences the partial volume effect. However, defining the adequate image resolution is not a trivial aspect and understanding the correlation between scan parameters like voxel size and the structural properties is crucial for comprehensive material characterisation using micro-CT. Therefore, the objective of this study was to evaluate the influence of the spatial image resolution on the micro-CT based morphological analysis of three-dimensional (3D) open porous structures with a high surface complexity. In particular the correlation between the local surface properties and the accuracy of the micro-CT-based macro-morphology of 3D open porous Ti6Al4V structures produced by selective laser melting (SLM) was targeted and revealed for rough surfaces a strong dependence of the resulting structure characteristics on the scan resolution. Reducing the surface complexity by chemical etching decreased the sensitivity of the overall morphological analysis to the spatial image resolution and increased the detection limit. This study showed that scan settings and image processing parameters need to be customized to the material properties, morphological parameters under investigation and the desired final characteristics (in relation to the intended functional use). Customization of the scan resolution can increase the reliability of the micro-CT based analysis and at the same time reduce its operating costs. - Highlights: • We examine influence of the image resolution

  18. Spatial and temporal analysis of postural control in dyslexic children.

    Science.gov (United States)

    Gouleme, Nathalie; Gerard, Christophe Loic; Bui-Quoc, Emmanuel; Bucci, Maria Pia

    2015-07-01

    The aim of this study is to examine postural control of dyslexic children using both spatial and temporal analysis. Thirty dyslexic (mean age 9.7±0.3years) and thirty non-dyslexic age-matched children participated in the study. Postural stability was evaluated using Multitest Equilibre from Framiral®. Posture was recorded in the following conditions: eyes open fixating a target (EO) and eyes closed (EC) on stable (-S-) and unstable (-U-) platforms. The findings of this study showed poor postural stability in dyslexic children with respect to the non-dyslexic children group, as demonstrated by both spatial and temporal analysis. In both groups of children postural control depends on the condition, and improves when the eyes are open on a stable platform. Dyslexic children have spectral power indices that are higher than in non-dyslexic children and they showed a shorter cancelling time. Poor postural control in dyslexic children could be due to a deficit in using sensory information most likely caused by impairment in cerebellar activity. The reliability of brain activation patterns, namely in using sensory input and cerebellar activity may explain the deficit in postural control in dyslexic children. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Fault tree analysis: concepts and techniques

    International Nuclear Information System (INIS)

    Fussell, J.B.

    1976-01-01

    Concepts and techniques of fault tree analysis have been developed over the past decade and now predictions from this type analysis are important considerations in the design of many systems such as aircraft, ships and their electronic systems, missiles, and nuclear reactor systems. Routine, hardware-oriented fault tree construction can be automated; however, considerable effort is needed in this area to get the methodology into production status. When this status is achieved, the entire analysis of hardware systems will be automated except for the system definition step. Automated analysis is not undesirable; to the contrary, when verified on adequately complex systems, automated analysis could well become a routine analysis. It could also provide an excellent start for a more in-depth fault tree analysis that includes environmental effects, common mode failure, and human errors. The automated analysis is extremely fast and frees the analyst from the routine hardware-oriented fault tree construction, as well as eliminates logic errors and errors of oversight in this part of the analysis. Automated analysis then affords the analyst a powerful tool to allow his prime efforts to be devoted to unearthing more subtle aspects of the modes of failure of the system

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

    Science.gov (United States)

    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. Spectral theory and nonlinear analysis with applications to spatial ecology

    CERN Document Server

    Cano-Casanova, S; Mora-Corral , C

    2005-01-01

    This volume details some of the latest advances in spectral theory and nonlinear analysis through various cutting-edge theories on algebraic multiplicities, global bifurcation theory, non-linear Schrödinger equations, non-linear boundary value problems, large solutions, metasolutions, dynamical systems, and applications to spatial ecology. The main scope of the book is bringing together a series of topics that have evolved separately during the last decades around the common denominator of spectral theory and nonlinear analysis - from the most abstract developments up to the most concrete applications to population dynamics and socio-biology - in an effort to fill the existing gaps between these fields.

  2. Concept of spatial channel theory applied to reactor shielding analysis

    International Nuclear Information System (INIS)

    Williams, M.L.; Engle, W.W. Jr.

    1977-01-01

    The concept of channel theory is used to locate spatial regions that are important in contributing to a shielding response. The method is analogous to the channel-theory method developed for ascertaining important energy channels in cross-section analysis. The mathematical basis for the theory is shown to be the generalized reciprocity relation, and sample problems are given to exhibit and verify properties predicted by the mathematical equations. A practical example is cited from the shielding analysis of the Fast Flux Test Facility performed at Oak Ridge National Laboratory, in which a perspective plot of channel-theory results was found useful in locating streaming paths around the reactor cavity shield

  3. Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry

    Directory of Open Access Journals (Sweden)

    Ali Ahmadi

    2015-01-01

    Full Text Available 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.

  4. Spatial prediction of near surface soil water retention functions using hydrogeophysics

    Science.gov (United States)

    Gibson, J. P.; Franz, T. E.

    2017-12-01

    The hydrological community often turns to widely available spatial datasets such as SSURGO to characterize the spatial variability of soil across a landscape of interest. This has served as a reasonable first approximation when lacking localized soil data. However, previous work has shown that information loss within land surface models primarily stems from parameterization. Localized soil sampling is both expensive and time intense, and thus a need exists in connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with larger spatial datasets. In this work, we utilize 2 geophysical techniques; cosmic ray neutron probe and electromagnetic induction, to identify temporally stable soil moisture patterns. This is achieved by measuring numerous times over a range of wet to dry field conditions in order to apply an empirical orthogonal function. We then present measured water retention functions of shallow cores extracted within each temporally stable zone. Lastly, we use soil moisture patterns as a covariate to predict soil hydraulic properties in areas without measurement and validate using a leave-one-out cross validation analysis. Using these approaches to better constrain soil hydraulic property variability, we speculate that further research can better estimate hydrologic fluxes in areas of interest.

  5. Nonlinear analysis techniques of block masonry walls in nuclear power plants

    International Nuclear Information System (INIS)

    Hamid, A.A.; Harris, H.G.

    1986-01-01

    Concrete masonry walls have been used extensively in nuclear power plants as non-load bearing partitions serving as pipe supports, fire walls, radiation shielding barriers, and similar heavy construction separations. When subjected to earthquake loads, these walls should maintain their structural integrity. However, some of the walls do not meet design requirements based on working stress allowables. Consequently, utilities have used non-linear analysis techniques, such as the arching theory and the energy balance technique, to qualify such walls. This paper presents a critical review of the applicability of non-linear analysis techniques for both unreinforced and reinforced block masonry walls under seismic loading. These techniques are critically assessed in light of the performance of walls from limited available test data. It is concluded that additional test data are needed to justify the use of nonlinear analysis techniques to qualify block walls in nuclear power plants. (orig.)

  6. Natural landscape features, human-related attractants, and conflict hotspots: A spatial analysis of human-grizzly bear conflicts

    Science.gov (United States)

    Wilson, S.M.; Madel, M.J.; Mattson, D.J.; Graham, J.M.; Burchfield, J.A.; Belsky, J.M.

    2005-01-01

    There is a long history of conflict in the western United States between humans and grizzly bears (Ursus arctos) involving agricultural attractants. However, little is known about the spatial dimensions of this conflict and the relative importance of different attractants. This study was undertaken to better understand the spatial and functional components of conflict between humans and grizzly bears on privately owned agricultural lands in Montana. Our investigations focused on spatial associations of rivers and creeks, livestock pastures, boneyards (livestock carcass dump sites), beehives, and grizzly bear habitat with reported human-grizzly bear conflicts during 1986-2001. We based our analysis on a survey of 61 of 64 livestock producers in our study in the Rocky Mountain East Front, Montana. With the assistance of livestock and honey producers, we mapped the locations of cattle and sheep pastures, boneyards, and beehives. We used density surface mapping to identify seasonal clusters of conflicts that we term conflict hotspots. Hotspots accounted for 75% of all conflicts and encompassed approximately 8% of the study area. We also differentiated chronic (4 or more years of conflicts) from non-chronic hotspots (fewer than 4 years of conflict). The 10 chronic hotpots accounted for 58% of all conflicts. Based on Monte Carlo simulations, we found that conflict locations were most strongly associated with rivers and creeks followed by sheep lambing areas and fall sheep pastures. Conflicts also were associated with cattle calving areas, spring cow-calf pastures, summer and fall cattle pastures, and boneyards. The Monte Carlo simulations indicated associations between conflict locations and unprotected beehives at specific analysis scales. Protected (fenced) beehives were less likely to experience conflicts than unprotected beehives. Conflicts occurred at a greater rate in riparian and wetland vegetation than would be expected. The majority of conflicts occurred in a

  7. A Bayesian method to mine spatial data sets to evaluate the vulnerability of human beings to catastrophic risk.

    Science.gov (United States)

    Li, Lianfa; Wang, Jinfeng; Leung, Hareton; Zhao, Sisi

    2012-06-01

    Vulnerability of human beings exposed to a catastrophic disaster is affected by multiple factors that include hazard intensity, environment, and individual characteristics. The traditional approach to vulnerability assessment, based on the aggregate-area method and unsupervised learning, cannot incorporate spatial information; thus, vulnerability can be only roughly assessed. In this article, we propose Bayesian network (BN) and spatial analysis techniques to mine spatial data sets to evaluate the vulnerability of human beings. In our approach, spatial analysis is leveraged to preprocess the data; for example, kernel density analysis (KDA) and accumulative road cost surface modeling (ARCSM) are employed to quantify the influence of geofeatures on vulnerability and relate such influence to spatial distance. The knowledge- and data-based BN provides a consistent platform to integrate a variety of factors, including those extracted by KDA and ARCSM to model vulnerability uncertainty. We also consider the model's uncertainty and use the Bayesian model average and Occam's Window to average the multiple models obtained by our approach to robust prediction of the risk and vulnerability. We compare our approach with other probabilistic models in the case study of seismic risk and conclude that our approach is a good means to mining spatial data sets for evaluating vulnerability. © 2012 Society for Risk Analysis.

  8. Augmented reality to training spatial skills

    OpenAIRE

    Martin-Gutierrez, Jorge; Contero, Manuel; Alcañiz Raya, Mariano Luis

    2015-01-01

    La Laguna University has been offering courses for the development of spatial skills since 2004. Each year since that time spatial ability of engineering students has been measured before and after the courses to check progress after each training session. We have developed a spatial skills training course based on augmented reality and graphic engineering contents, and designed the AR_Dehaes tool, which is based on its own library the uses computer vision techniques for incorporating vis...

  9. Application of novel techniques of medical imaging to the non-destructive analysis of carbon-carbon composite materials

    Science.gov (United States)

    More, Nicole; Basse-Cathalinat, Bernard; Baquey, Charles; Lacroix, Francis; Ducassou, Dominique

    1983-09-01

    Rigorous control of all stages of the fabrication of a composite material is vital. It is best if this control uses non-destructive methods, so allowing the same item to be studied during the different stages of its manufacture. Much research has already been done to perfect such investigations in medicine, so providing a minimum of trauma to the patient. Most of these medical applications use radioactive isotopes. The present work describes the application of currently available techniques, employed in nuclear medicine, for the analysis of the density and porosity of carbon-carbon composite materials. Two most powerful medical techniques are applied to measure variations of density of a composite material. These are transmission computed tomography using X-rays and the absorption of photons. The quantitative measurement of porosity can be derived from a scintigraphic technique which allows a detailed non-invasive study of the interior of the composite and the spatial variation of porosity at every stage of its fabrication. For each type of investigation, the principle of the method, a description of the apparatus and several examples of results obtained are presented. The advantages and limitations of these techniques which complement those currently available are discussed, together with future possibilities for non-destructive control of industrial processes. It is likely that their proven success in medicine will be extended to the other fields described.

  10. Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework. [relations (mathematics)

    Science.gov (United States)

    Peuquet, Donna J.

    1987-01-01

    A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

  11. Analysis of ancient pigments by Raman microscopy

    International Nuclear Information System (INIS)

    Zuo Jian; Xu Cunyi

    1999-01-01

    Raman microscopy can be applied for the spatial resolution, and non-destructive in situ analysis of inorganic pigments in pottery, manuscripts and paintings. Compared with other techniques, it is the best single technique for this purpose. An overview is presented of the applications of Raman microscopy in the analysis of ancient pigments

  12. Spatial Operations

    Directory of Open Access Journals (Sweden)

    Anda VELICANU

    2010-09-01

    Full Text Available This paper contains a brief description of the most important operations that can be performed on spatial data such as spatial queries, create, update, insert, delete operations, conversions, operations on the map or analysis on grid cells. Each operation has a graphical example and some of them have code examples in Oracle and PostgreSQL.

  13. A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

    Science.gov (United States)

    Wang, Jun; Wang, Yang; Zeng, Hui

    2016-01-01

    A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

  14. Development of environmental sample analysis techniques for safeguards

    International Nuclear Information System (INIS)

    Magara, Masaaki; Hanzawa, Yukiko; Esaka, Fumitaka

    1999-01-01

    JAERI has been developing environmental sample analysis techniques for safeguards and preparing a clean chemistry laboratory with clean rooms. Methods to be developed are a bulk analysis and a particle analysis. In the bulk analysis, Inductively-Coupled Plasma Mass Spectrometer or Thermal Ionization Mass Spectrometer are used to measure nuclear materials after chemical treatment of sample. In the particle analysis, Electron Probe Micro Analyzer and Secondary Ion Mass Spectrometer are used for elemental analysis and isotopic analysis, respectively. The design of the clean chemistry laboratory has been carried out and construction will be completed by the end of March, 2001. (author)

  15. Adaptive Analysis of Functional MRI Data

    International Nuclear Information System (INIS)

    Friman, Ola

    2003-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

  16. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  17. Application of pattern recognition techniques to crime analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

    1976-08-15

    The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

  18. APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

    International Nuclear Information System (INIS)

    STOYANOVA, R.S.; OCHS, M.F.; BROWN, T.R.; ROONEY, W.D.; LI, X.; LEE, J.H.; SPRINGER, C.S.

    1999-01-01

    Standard analysis methods for processing inversion recovery MR images traditionally have used single pixel techniques. In these techniques each pixel is independently fit to an exponential recovery, and spatial correlations in the data set are ignored. By analyzing the image as a complete dataset, improved error analysis and automatic segmentation can be achieved. Here, the authors apply principal component analysis (PCA) to a series of relaxographic images. This procedure decomposes the 3-dimensional data set into three separate images and corresponding recovery times. They attribute the 3 images to be spatial representations of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) content

  19. Conservation and restoration of forested wetlands: new techniques and perspectives

    Science.gov (United States)

    James Johnston; Steve Hartley; Antonio Martucci

    2000-01-01

    A partnership of state and federal agencies and private organizations is developing advanced spatial analysis techniques applied for conservation and restoration of forested wetlands. The project goal is to develop an application to assist decisionmakers in defining the eligibility of land sites for entry in the Wetland Reserve Program (WRP) of the U.S. Department of...

  20. Photography activities for developing students’ spatial orientation and spatial visualization

    Science.gov (United States)

    Hendroanto, Aan; van Galen, Frans; van Eerde, D.; Prahmana, R. C. I.; Setyawan, F.; Istiandaru, A.

    2017-12-01

    Spatial orientation and spatial visualization are the foundation of students’ spatial ability. They assist students’ performance in learning mathematics, especially geometry. Considering its importance, the present study aims to design activities to help young learners developing their spatial orientation and spatial visualization ability. Photography activity was chosen as the context of the activity to guide and support the students. This is a design research study consisting of three phases: 1) preparation and designing 2) teaching experiment, and 3) retrospective analysis. The data is collected by tests and interview and qualitatively analyzed. We developed two photography activities to be tested. In the teaching experiments, 30 students of SD Laboratorium UNESA, Surabaya were involved. The results showed that the activities supported the development of students’ spatial orientation and spatial visualization indicated by students’ learning progresses, answers, and strategies when they solved the problems in the activities.

  1. HIGH SPATIAL-RESOLUTION IMAGING OF TE INCLUSIONS IN CZT MATERIAL

    International Nuclear Information System (INIS)

    CAMARDA, G.S.; BOLOTNIKOV, A.E.; CARINI, G.A.; CUI, Y.; KOHMAN, K.T.; LI, L.; JAMES, R.B.

    2006-01-01

    We present new results from our studies of defects in current single-crystal CdZnTe material. Our previous measurements, carried out on thin (∼1 mm) and long (>12 mm) CZT detectors, indicated that small (1-20 (micro)m) Te inclusions can significantly degrade the device's energy resolution and detection efficiency. We are conducting detailed studies of the effects of Te inclusions by employing different characterization techniques with better spatial resolution, such as quantitative fluorescence mapping, X-ray micro-diffraction, and TEM. Also, IR microscopy and gamma-mapping with pulse-shape analysis with higher spatial resolution generated more accurate results in the areas surrounding the micro-defects (Te inclusions). Our results reveal how the performance of CdZnTe detectors is influenced by Te inclusions, such as their spatial distribution, concentration, and size. We also discuss a model of charge transport through areas populated with Te inclusions

  2. Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations

    Science.gov (United States)

    Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter

    2013-04-01

    Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the

  3. The statistical geoportal and the ``cartographic added value'' - creation of the spatial knowledge infrastructure

    Science.gov (United States)

    Fiedukowicz, Anna; Gasiorowski, Jedrzej; Kowalski, Paweł; Olszewski, Robert; Pillich-Kolipinska, Agata

    2012-11-01

    The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge. Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here. Szeroki dostep do danych zródłowych publikowanych w licznych serwisach internetowych sprawia, iz współczesnie problemem jest nie pozyskanie informacji, lecz umiejetne przekształcenie jej w uzyteczna wiedze. Kartograficzna metoda badan, która od wielu lat słuzy temu celowi w odniesieniu do danych przestrzennych, zyskuje dzis nowe oblicze - pozwala na wykonywanie złozonych analiz dzieki wykorzystaniu intensywnego rozwoju technologii informatycznych. Znaczaca wiekszosc zastosowan metod analitycznych tzw. eksploracyjnej analizy danych (data mining) i ich "wzbogacania” (data enrichment) dotyczy jednakze danych nieprzestrzennych. Wykorzystanie tych metod do analizy danych o charakterze przestrzennym, w

  4. Spatial Factor Analysis for Aerosol Optical Depth in Metropolises in China with Regard to Spatial Heterogeneity

    Directory of Open Access Journals (Sweden)

    Hui Shi

    2018-04-01

    Full Text Available A substantial number of studies have analyzed how driving factors impact aerosols, but they have been little concerned with the spatial heterogeneity of aerosols and the factors that impact aerosols. The spatial distributions of the aerosol optical depth (AOD retrieved by Moderate Resolution Imaging Spectrometer (MODIS data at 550-nm and 3-km resolution for three highly developed metropolises, the Beijing-Tianjin-Hebei (BTH region, the Yangtze River Delta (YRD, and the Pearl River Delta (PRD, in China during 2015 were analyzed. Different degrees of spatial heterogeneity of the AOD were found, which were indexed by Moran’s I index giving values of 0.940, 0.715, and 0.680 in BTH, YRD, and PRD, respectively. For the spatial heterogeneity, geographically weighted regression (GWR was employed to carry out a spatial factor analysis, where terrain, climate condition, urban development, and vegetation coverage were taken as the potential driving factors. The results of the GWR imply varying relationships between the AOD and the factors. The results were generally consistent with existing studies, but the results suggest the following: (1 Elevation increase would more likely lead to a strong negative impact on aerosols (with most of the coefficients ranging from −1.5~0 in the BTH, −1.5~0 in the YRD, and −1~0 in the PRD in the places with greater elevations where the R-squared values are always larger than 0.5. However, the variation of elevations cannot explain the variation of aerosols in the places with relatively low elevations (with R-squared values approximately 0.1, ranging from 0 to 0.3, and approximately 0.1 in the BTH, YRD, and PRD, such as urban areas in the BTH and YRD. (2 The density of the built-up areas made a strong and positive impact on aerosols in the urban areas of the BTH (R-squared larger than 0.5, while the R-squared dropped to 0.1 in the places far away from the urban areas. (3 The vegetation coverage led to a stronger

  5. Application status of on-line nuclear techniques in analysis of coal quality

    International Nuclear Information System (INIS)

    Cai Shaohui

    1993-01-01

    Nuclear techniques are favourable for continuous on-line analysis, because they are fast, non-intrusive. They can be used in the adverse circumstances in coal industry. The paper reviews the application status of on-line nuclear techniques in analysis of coal quality and economic benefits derived from such techniques in developed countries

  6. OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

    Energy Technology Data Exchange (ETDEWEB)

    de Raad, Markus [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); de Rond, Tristan [Univ. of California, Berkeley, CA (United States); Rübel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Keasling, Jay D. [Univ. of California, Berkeley, CA (United States); Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark); Northen, Trent R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Bowen, Benjamin P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)

    2017-05-03

    Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data. By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.

  7. Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors

    International Nuclear Information System (INIS)

    Long, Ruyin; Shao, Tianxiang; Chen, Hong

    2016-01-01

    Highlights: • We evaluate the industrial carbon productivity of China’s provinces. • The regional disparity and clustering features exist simultaneously. • There is evident spatial dependence in regional industrial carbon productivity. • We employ spatial panel data models to examine the impact factors. • Spatial effects are found to be important in understanding industrial CO_2 emissions. - Abstract: This study measured the industrial carbon productivity of 30 provinces in China from 2005 to 2012 and examined the space–time characteristics and the main factors of China’s industrial carbon productivity using Moran’s I index and spatial panel data models. The empirical results indicate that there is significant positive spatial dependence and clustering characteristics in China’s province-level industrial carbon productivity. The spatial dependence may create biased estimated parameters in an ordinary least squares framework; according to the analysis of our spatial panel models, industrial energy efficiency, the opening degree, technological progress, and the industrial scale structure have significantly positive effects on industrial carbon productivity whereas per-capita GDP, the industrial energy consumption structure, and the industrial ownership structure exert a negative effect on industrial carbon productivity.

  8. Spatial Distribution Analysis of Scrub Typhus in Korea

    OpenAIRE

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

    2013-01-01

    Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does...

  9. Magnetic separation techniques in sample preparation for biological analysis: a review.

    Science.gov (United States)

    He, Jincan; Huang, Meiying; Wang, Dongmei; Zhang, Zhuomin; Li, Gongke

    2014-12-01

    Sample preparation is a fundamental and essential step in almost all the analytical procedures, especially for the analysis of complex samples like biological and environmental samples. In past decades, with advantages of superparamagnetic property, good biocompatibility and high binding capacity, functionalized magnetic materials have been widely applied in various processes of sample preparation for biological analysis. In this paper, the recent advancements of magnetic separation techniques based on magnetic materials in the field of sample preparation for biological analysis were reviewed. The strategy of magnetic separation techniques was summarized. The synthesis, stabilization and bio-functionalization of magnetic nanoparticles were reviewed in detail. Characterization of magnetic materials was also summarized. Moreover, the applications of magnetic separation techniques for the enrichment of protein, nucleic acid, cell, bioactive compound and immobilization of enzyme were described. Finally, the existed problems and possible trends of magnetic separation techniques for biological analysis in the future were proposed. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Line-Scan Hyperspectral Imaging Techniques for Food Safety and Quality Applications

    Directory of Open Access Journals (Sweden)

    Jianwei Qin

    2017-01-01

    Full Text Available Hyperspectral imaging technologies in the food and agricultural area have been evolving rapidly over the past 15 years owing to tremendous interest from both academic and industrial fields. Line-scan hyperspectral imaging is a major method that has been intensively researched and developed using different physical principles (e.g., reflectance, transmittance, fluorescence, Raman, and spatially resolved spectroscopy and wavelength regions (e.g., visible (VIS, near infrared (NIR, and short-wavelength infrared (SWIR. Line-scan hyperspectral imaging systems are mainly developed and used for surface inspection of food and agricultural products using area or line light sources. Some of these systems can also be configured to conduct spatially resolved spectroscopy measurements for internal or subsurface food inspection using point light sources. This paper reviews line-scan hyperspectral imaging techniques, with introduction, demonstration, and summarization of existing and emerging techniques for food and agricultural applications. The main topics include related spectroscopy techniques, line-scan measurement methods, hardware components and systems, system calibration methods, and spectral and image analysis techniques. Applications in food safety and quality are also presented to reveal current practices and future trends of line-scan hyperspectral imaging techniques.

  11. Performance analysis of clustering techniques over microarray data: A case study

    Science.gov (United States)

    Dash, Rasmita; Misra, Bijan Bihari

    2018-03-01

    Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

  12. Techniques for Automated Performance Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Marcus, Ryan C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-09-02

    The performance of a particular HPC code depends on a multitude of variables, including compiler selection, optimization flags, OpenMP pool size, file system load, memory usage, MPI configuration, etc. As a result of this complexity, current predictive models have limited applicability, especially at scale. We present a formulation of scientific codes, nodes, and clusters that reduces complex performance analysis to well-known mathematical techniques. Building accurate predictive models and enhancing our understanding of scientific codes at scale is an important step towards exascale computing.

  13. Spatial Heterodyne Observation of Water (SHOW) from a high altitude aircraft

    Science.gov (United States)

    Bourassa, A. E.; Langille, J.; Solheim, B.; Degenstein, D. A.; Letros, D.; Lloyd, N. D.; Loewen, P.

    2017-12-01

    The Spatial Heterodyne Observations of Water instrument (SHOW) is limb-sounding satellite prototype that is being developed in collaboration between the University of Saskatchewan, York University, the Canadian Space Agency and ABB. The SHOW instrument combines a field-widened SHS with an imaging system to observe limb-scattered sunlight in a vibrational band of water (1363 nm - 1366 nm). Currently, the instrument has been optimized for deployment on NASA's ER-2 aircraft. Flying at an altitude of 70, 000 ft the ER-2 configuration and SHOW viewing geometry provides high spatial resolution (limb-measurements of water vapor in the Upper troposphere and lower stratosphere region. During an observation campaign from July 15 - July 22, the SHOW instrument performed 10 hours of observations from the ER-2. This paper describes the SHOW measurement technique and presents the preliminary analysis and results from these flights. These observations are used to validate the SHOW measurement technique and demonstrate the sampling capabilities of the instrument.

  14. Prompt Gamma Activation Analysis (PGAA): Technique of choice for nondestructive bulk analysis of returned comet samples

    International Nuclear Information System (INIS)

    Lindstrom, D.J.; Lindstrom, R.M.

    1989-01-01

    Prompt gamma activation analysis (PGAA) is a well-developed analytical technique. The technique involves irradiation of samples in an external neutron beam from a nuclear reactor, with simultaneous counting of gamma rays produced in the sample by neutron capture. Capture of neutrons leads to excited nuclei which decay immediately with the emission of energetic gamma rays to the ground state. PGAA has several advantages over other techniques for the analysis of cometary materials: (1) It is nondestructive; (2) It can be used to determine abundances of a wide variety of elements, including most major and minor elements (Na, Mg, Al, Si, P, K, Ca, Ti, Cr, Mn, Fe, Co, Ni), volatiles (H, C, N, F, Cl, S), and some trace elements (those with high neutron capture cross sections, including B, Cd, Nd, Sm, and Gd); and (3) It is a true bulk analysis technique. Recent developments should improve the technique's sensitivity and accuracy considerably

  15. LABOUR INPUT IN POLISH AGRICULTURE AGAINST SIZE OF AGRICULTURAL HOLDINGS – SPATIAL ANALYSIS*

    Directory of Open Access Journals (Sweden)

    Łukasz Wiśniewski

    2016-09-01

    Full Text Available The aim of this paper is to present the analysis of spatial diversifi cation in the labour input in agriculture on the basis of these selected indicators: annual work unit (AWU per 100 ha agricultural acreage; number of people per AWU; and comparison of labour input to EU-15 standards (LI-EU. Agricultural holdings have been categorised by size into three groups: 0–10 ha (small, 10–20 ha (average, and over 20 ha (large. Labour resources were subject to a comparative study of the density rates of AWUs per 100 ha agricultural acreage in Poland and the EU (EU-15. The analysis covered all of Poland with consideration of the administrative division into sixteen voivodeships (tabular analysis and 314 poviats (townships and country districts together, including regional offi ces of the Agency for Restructuring and Modernisation of Agriculture (ARiMR; cartographic analysis. The results of the Agricultural Census of 2010 were used in the study. It demonstrated a signifi cant spatial diversifi cation in labour input in agriculture in general and in each holding size group. Predominantly, the diff erences are related to historical and political factors. The analysis corroborated agrarian overpopulation in south-east Poland.

  16. A review on applications of the wavelet transform techniques in spectral analysis

    International Nuclear Information System (INIS)

    Medhat, M.E.; Albdel-hafiez, A.; Hassan, M.F.; Ali, M.A.; Awaad, Z.

    2004-01-01

    Starting from 1989, a new technique known as wavelet transforms (WT) has been applied successfully for analysis of different types of spectra. WT offers certain advantages over Fourier transforms for analysis of signals. A review of using this technique through different fields of elemental analysis is presented

  17. Model of spatial analysis of electric power market using the Fuzzy C-Means technical classification; Modelo de analise espacial de mercado de energia eletrica utilizando a tecnica de classificacao Fuzzy C-Means

    Energy Technology Data Exchange (ETDEWEB)

    Neto, J.C. [Companhia Energetica de Goias (CELG-D), Goiania, GO (Brazil)], E-mail: joao.cn@celg.com.br; Lima, W.S. [Votorantim Siderurgia, Resende, Rio de Janeiro, RJ (Brazil). Gerencia Geral de Tecnologia], E-mail: wagner.lima@vmetais.com.br

    2009-07-01

    The power distribution companies live with an antagonistic reality: an increasing energy demand, due to steady economic and population growth, and a limitation on their financial resources to expand its network. Therefore, it is essential an improvement in activity of planning of the power distribution system trying to improve the application of available resources. In this context fits the application of Geographic Information System combined with clustering techniques and classification in order to enhance the planning process, giving the planner a more complete picture of the consumer market by the distributor. This paper presents a system that makes use of Geographic Information System combined with the technique of clustering and classification Fuzzy C-Means, with the aim of analyzing the distribution of network load and the performance of the technique. Each group performed leads to a spatial representation (scenario). This, together with an index measuring the performance of the group (intra-group and inter-group) implemented in this work, provides a favorable environment for spatial analysis of the electric power market.

  18. Le dysfonctionnement socio-spatial des grands ensembles en Algérie: technique de l’analyse wayfinding par méthode “movement traces” et l’analyse morphologique (syntaxe spatiale par logiciel “depthmap”

    Directory of Open Access Journals (Sweden)

    Amara Hima

    2018-03-01

    Full Text Available Résumé La technique de l’analyse syntaxique de la visibilité (Visibility Graph Analysis – VGA et de l’accessibilité (All Line Analysis – ALA par logiciel “DepthMap©(UCL, Londres” et l’analyse du dysfonctionnement wayfinding par méthode “movement traces”, sont utilisées dans ce papier afin de développer un modèle d’analyse et d’investigation de l’impact des changements spatiaux sur le dysfonctionnement socio-spatial du wayfinding, ainsi sur la reproduction urbaine, notamment les transformations des façades et l’appropriation des espaces extérieurs dans les grands ensembles en Algérie. Nous donnons ici le cas d’étude de la cité 1000 logt-Biskra et la cité 500 logt-M’sila. Afin de vérifier cette hypothèse, un modèle d’analyse hybride a été développé par croisement des résultats d’analyses des deux techniques. Par conséquent, le schéma de l’interférence montre que la majorité des piétons préfèrent parcourir les axes courts et droits — caractérisés par une forte propriété syntaxique de visibilité et d’accessibilité (l’intégration, la connectivité et l’intelligibilité — en directions des équipements adjacents et aux milieux des deux cités. Ces itinéraires ont un impact sur les transformations des façades et l’appropriation des espaces extérieurs. Le modèle développé promet de futures recherches sur le plan de la quantification, la modélisation et la simulation du processus de la reproduction urbaine, notamment par les automates cellulaires.

  19. Suitable Site Selection of Small Dams Using Geo-Spatial Technique: a Case Study of Dadu Tehsil, Sindh

    Science.gov (United States)

    Khalil, Zahid

    2016-07-01

    Decision making about identifying suitable sites for any project by considering different parameters, is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30 meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pair wise comparison method, also known as Analytical Hierarchy Process (AHP) is took into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision making about suitable sites analysis for small dams using geo-spatial data with minimal amount of ground data. This suitability maps can be helpful for water resource

  20. A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China

    Science.gov (United States)

    Ge, Xiangyu; Zhou, Yanli; Liu, Songlin

    2018-01-01

    Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China’s central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their neighboring areas? The present study aims to tackle these issues. This is the first research that simultaneously studies the nexus between nitrogen oxides emissions and economic development/urbanization, with the application of a spatial panel data technique. Our empirical findings suggest that spatial dependence of nitrogen oxides emissions distribution exists at the provincial level. Through the investigation of the existence of an environmental Kuznets curve (EKC) embedded within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, we conclude something interesting: an inverse N-shaped EKC describes both the income-nitrogen oxides nexus and the urbanization-nitrogen oxides nexus. Some well-directed policy advice is provided to reduce nitrogen oxides in the future. Moreover, these results contribute to the literature on development and pollution. PMID:29641500

  1. A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China.

    Science.gov (United States)

    Ge, Xiangyu; Zhou, Zhimin; Zhou, Yanli; Ye, Xinyue; Liu, Songlin

    2018-04-11

    Abstract : Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China's central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their neighboring areas? The present study aims to tackle these issues. This is the first research that simultaneously studies the nexus between nitrogen oxides emissions and economic development/urbanization, with the application of a spatial panel data technique. Our empirical findings suggest that spatial dependence of nitrogen oxides emissions distribution exists at the provincial level. Through the investigation of the existence of an environmental Kuznets curve (EKC) embedded within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, we conclude something interesting: an inverse N-shaped EKC describes both the income-nitrogen oxides nexus and the urbanization-nitrogen oxides nexus. Some well-directed policy advice is provided to reduce nitrogen oxides in the future. Moreover, these results contribute to the literature on development and pollution.

  2. A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China

    Directory of Open Access Journals (Sweden)

    Xiangyu Ge

    2018-04-01

    Full Text Available Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China’s central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their neighboring areas? The present study aims to tackle these issues. This is the first research that simultaneously studies the nexus between nitrogen oxides emissions and economic development/urbanization, with the application of a spatial panel data technique. Our empirical findings suggest that spatial dependence of nitrogen oxides emissions distribution exists at the provincial level. Through the investigation of the existence of an environmental Kuznets curve (EKC embedded within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT framework, we conclude something interesting: an inverse N-shaped EKC describes both the income-nitrogen oxides nexus and the urbanization-nitrogen oxides nexus. Some well-directed policy advice is provided to reduce nitrogen oxides in the future. Moreover, these results contribute to the literature on development and pollution.

  3. Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: I. spatial analysis

    Directory of Open Access Journals (Sweden)

    M. van Den Berg

    2000-06-01

    Full Text Available The spatial variability of strongly weathered soils under sugarcane and soybean/wheat rotation was quantitatively assessed on 33 fields in two regions in São Paulo State, Brazil: Araras (15 fields with sugarcane and Assis (11 fields with sugarcane and seven fields with soybean/wheat rotation. Statistical methods used were: nested analysis of variance (for 11 fields, semivariance analysis and analysis of variance within and between fields. Spatial levels from 50 m to several km were analyzed. Results are discussed with reference to a previously published study carried out in the surroundings of Passo Fundo (RS. Similar variability patterns were found for clay content, organic C content and cation exchange capacity. The fields studied are quite homogeneous with respect to these relatively stable soil characteristics. Spatial variability of other characteristics (resin extractable P, pH, base- and Al-saturation and also soil colour, varies with region and, or land use management. Soil management for sugarcane seems to have induced modifications to greater depths than for soybean/wheat rotation. Surface layers of soils under soybean/wheat present relatively little variation, apparently as a result of very intensive soil management. The major part of within-field variation occurs at short distances (< 50 m in all study areas. Hence, little extra information would be gained by increasing sampling density from, say, 1/km² to 1/50 m². For many purposes, the soils in the study regions can be mapped with the same observation density, but residual variance will not be the same in all areas. Bulk sampling may help to reveal spatial patterns between 50 and 1.000 m.

  4. Defensible Spaces in Philadelphia: Exploring Neighborhood Boundaries Through Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Rory Kramer

    2017-02-01

    Full Text Available Few spatial scales are as important to individual outcomes as the neighborhood. However, it is nearly impossible to define neighborhoods in a generalizable way. This article proposes that by shifting the focus to measuring neighborhood boundaries rather than neighborhoods, scholars can avoid the problem of the indefinable neighborhood and better approach questions of what predicts racial segregation across areas. By quantifying an externality space theory of neighborhood boundaries, this article introduces a novel form of spatial analysis to test where potential physical markers of neighborhood boundaries (major roads, rivers, railroads, and the like are associated with persistent racial boundaries between 1990 and 2010. Using Philadelphia as a case study, the paper identifies neighborhoods with persistent racial boundaries. It theorizes that local histories of white reactions to black in-migration explain which boundaries persistently resisted racial turnover, unlike the majority of Philadelphia’s neighborhoods, and that those racial boundaries shape the location, progress, and reaction to new residential development in those neighborhoods.

  5. Diving into the consumer nutrition environment: A Bayesian spatial factor analysis of neighborhood restaurant environment.

    Science.gov (United States)

    Luan, Hui; Law, Jane; Lysy, Martin

    2018-02-01

    Neighborhood restaurant environment (NRE) plays a vital role in shaping residents' eating behaviors. While NRE 'healthfulness' is a multi-facet concept, most studies evaluate it based only on restaurant type, thus largely ignoring variations of in-restaurant features. In the few studies that do account for such features, healthfulness scores are simply averaged over accessible restaurants, thereby concealing any uncertainty that attributed to neighborhoods' size or spatial correlation. To address these limitations, this paper presents a Bayesian Spatial Factor Analysis for assessing NRE healthfulness in the city of Kitchener, Canada. Several in-restaurant characteristics are included. By treating NRE healthfulness as a spatially correlated latent variable, the adopted modeling approach can: (i) identify specific indicators most relevant to NRE healthfulness, (ii) provide healthfulness estimates for neighborhoods without accessible restaurants, and (iii) readily quantify uncertainties in the healthfulness index. Implications of the analysis for intervention program development and community food planning are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Analysis technique for controlling system wavefront error with active/adaptive optics

    Science.gov (United States)

    Genberg, Victor L.; Michels, Gregory J.

    2017-08-01

    The ultimate goal of an active mirror system is to control system level wavefront error (WFE). In the past, the use of this technique was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for controlling system level WFE using a linear optics model is presented. An error estimate is included in the analysis output for both surface error disturbance fitting and actuator influence function fitting. To control adaptive optics, the technique has been extended to write system WFE in state space matrix form. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

  7. Research on digital multi-channel pulse height analysis techniques

    International Nuclear Information System (INIS)

    Xiao Wuyun; Wei Yixiang; Ai Xianyun; Ao Qi

    2005-01-01

    Multi-channel pulse height analysis techniques are developing in the direction of digitalization. Based on digital signal processing techniques, digital multi-channel analyzers are characterized by powerful pulse processing ability, high throughput, improved stability and flexibility. This paper analyzes key techniques of digital nuclear pulse processing. With MATLAB software, main algorithms are simulated, such as trapezoidal shaping, digital baseline estimation, digital pole-zero/zero-pole compensation, poles and zeros identification. The preliminary general scheme of digital MCA is discussed, as well as some other important techniques about its engineering design. All these lay the foundation of developing homemade digital nuclear spectrometers. (authors)

  8. Participative Spatial Scenario Analysis for Alpine Ecosystems

    Science.gov (United States)

    Kohler, Marina; Stotten, Rike; Steinbacher, Melanie; Leitinger, Georg; Tasser, Erich; Schirpke, Uta; Tappeiner, Ulrike; Schermer, Markus

    2017-10-01

    Land use and land cover patterns are shaped by the interplay of human and ecological processes. Thus, heterogeneous cultural landscapes have developed, delivering multiple ecosystem services. To guarantee human well-being, the development of land use types has to be evaluated. Scenario development and land use and land cover change models are well-known tools for assessing future landscape changes. However, as social and ecological systems are inextricably linked, land use-related management decisions are difficult to identify. The concept of social-ecological resilience can thereby provide a framework for understanding complex interlinkages on multiple scales and from different disciplines. In our study site (Stubai Valley, Tyrol/Austria), we applied a sequence of steps including the characterization of the social-ecological system and identification of key drivers that influence farmers' management decisions. We then developed three scenarios, i.e., "trend", "positive" and "negative" future development of farming conditions and assessed respective future land use changes. Results indicate that within the "trend" and "positive" scenarios pluri-activity (various sources of income) prevents considerable changes in land use and land cover and promotes the resilience of farming systems. Contrarily, reductions in subsidies and changes in consumer behavior are the most important key drivers in the negative scenario and lead to distinct abandonment of grassland, predominantly in the sub-alpine zone of our study site. Our conceptual approach, i.e., the combination of social and ecological methods and the integration of local stakeholders' knowledge into spatial scenario analysis, resulted in highly detailed and spatially explicit results that can provide a basis for further community development recommendations.

  9. Romanian medieval earring analysis by X-ray fluorescence technique

    International Nuclear Information System (INIS)

    Therese, Laurent; Guillot, Philippe; Muja, Cristina

    2011-01-01

    Full text: Several instrumental techniques of elemental analysis are now used for the characterization of archaeological materials. The combination between archaeological and analytical information can provide significant knowledge on the constituting material origin, heritage authentication and restoration, provenance, migration, social interaction and exchange. Surface mapping techniques such as X-Ray Fluorescence have become a powerful tool for obtaining qualitative and semi-quantitative information about the chemical composition of cultural heritage materials, including metallic archaeological objects. In this study, the material comes from the Middle Age cemetery of Feldioara (Romania). The excavation of the site located between the evangelical church and the parsonage led to the discovery of several funeral artifacts in 18 graves among a total of 127 excavated. Even if the inventory was quite poor, some of the objects helped in establishing the chronology. Six anonymous Hungarian denarii (silver coins) were attributed to Geza II (1141-1161) and Stefan III (1162-1172), placing the cemetery in the second half of the XII century. This period was also confirmed by three loop shaped earrings with the end in 'S' form (one small and two large earrings). The small earring was found during the excavation in grave number 86, while the two others were discovered together in grave number 113. The anthropological study shown that skeletons excavated from graves 86 and 113 belonged respectively to a child (1 individual, medium level preservation, 9 months +/- 3 months) and to an adult (1 individual). In this work, elemental mapping were obtained by X-ray fluorescence (XRF) technique from Jobin Yvon Horiba XGT-5000 instrument offering detailed elemental images with a spatial resolution of 100μm. The analysis revealed that the earrings were composed of copper, zinc and tin as major elements. Minor elements were also determined. The comparison between the two large earrings

  10. Romanian medieval earring analysis by X-ray fluorescence technique

    Energy Technology Data Exchange (ETDEWEB)

    Therese, Laurent; Guillot, Philippe, E-mail: philippe.guillot@univ-jfc.fr [Laboratoire Diagnostics des Plasmas, CUFR J.F.C, Albi (France); Muja, Cristina [Laboratoire Diagnostics des Plasmas, CUFR J.F.C, Albi (France); Faculty of Biology, University of Bucharest (Romania); Vasile Parvan Institute of Archaeology, Bucharest, (Romania)

    2011-07-01

    Full text: Several instrumental techniques of elemental analysis are now used for the characterization of archaeological materials. The combination between archaeological and analytical information can provide significant knowledge on the constituting material origin, heritage authentication and restoration, provenance, migration, social interaction and exchange. Surface mapping techniques such as X-Ray Fluorescence have become a powerful tool for obtaining qualitative and semi-quantitative information about the chemical composition of cultural heritage materials, including metallic archaeological objects. In this study, the material comes from the Middle Age cemetery of Feldioara (Romania). The excavation of the site located between the evangelical church and the parsonage led to the discovery of several funeral artifacts in 18 graves among a total of 127 excavated. Even if the inventory was quite poor, some of the objects helped in establishing the chronology. Six anonymous Hungarian denarii (silver coins) were attributed to Geza II (1141-1161) and Stefan III (1162-1172), placing the cemetery in the second half of the XII century. This period was also confirmed by three loop shaped earrings with the end in 'S' form (one small and two large earrings). The small earring was found during the excavation in grave number 86, while the two others were discovered together in grave number 113. The anthropological study shown that skeletons excavated from graves 86 and 113 belonged respectively to a child (1 individual, medium level preservation, 9 months +/- 3 months) and to an adult (1 individual). In this work, elemental mapping were obtained by X-ray fluorescence (XRF) technique from Jobin Yvon Horiba XGT-5000 instrument offering detailed elemental images with a spatial resolution of 100{mu}m. The analysis revealed that the earrings were composed of copper, zinc and tin as major elements. Minor elements were also determined. The comparison between the two

  11. Spatial Data Envelopment Analysis Method for the Evaluation of Regional Infrastructure Disparities

    Directory of Open Access Journals (Sweden)

    Birutė Galinienė

    2012-12-01

    Full Text Available Purpose—to achieve a more detailed assessment of regional differences, exploring regional infrastructure and human capital usage efficiency and to display analysis capabilities of spatial data efficient frontier method.Design/methodology/approach—the data envelopment analysis (DEA is applied to find the efficient frontier, which extends the application of production function of the regions. This method of mathematical programming optimization allows assessing the effectiveness of the regional spatial aspects presented. In recent studies this method is applied for evaluating the European Union regional policy issues.Findings—the application of DEA reveals its feasibility for regional input and output studies to evaluate more detailed and more reasonable fund allocation between Lithuanian regions. This analysis shows that in the comparatively efficient Lithuanian regions, such as Vilnius and Klaipėda, “the bottleneck” of usage of transport infrastructure and regional specific human capital is reached. It is stated that decision-making units could enhance region attractiveness for private investors by improving indirect factors in these regions. For practical significance of the study the results are compared with German regional analysis, conducted by Schaffer and other researchers (2011.Practical implications—the practical value of this work is based on giving more accurate planning tools for fund allocation decisions in Lithuanian regions while planning infrastructure and human capital development. The regional indicators were analyzed for 2010.Research type—case study.

  12. Spatial and temporal superresolution concepts to study plasma membrane organization by single molecule fluorescence techniques

    International Nuclear Information System (INIS)

    Ruprecht, V.

    2010-01-01

    Fluorescence microscopy techniques are currently among the most important experimental tools to study cellular processes. Ultra-sensitive detection devices nowadays allow for measuring even individual farnesylacetate labeled target molecules with nanometer spatial accuracy and millisecond time resolution. The emergence of single molecule fluorescence techniques especially contributed to the field of membrane biology and provided basic knowledge on structural and dynamic features of the cellular plasma membrane. However, we are still confronted with a rather fragmentary understanding of the complex architecture and functional interrelations of membrane constituents. In this thesis new concepts in one- and dual-color single molecule fluorescence techniques are presented that allow for addressing organization principles and interaction dynamics in the live cell plasma membrane. Two complementary experimental strategies are described which differ in their detection principle: single molecule fluorescence imaging and fluorescence correlation spectroscopy. The presented methods are discussed in terms of their implementation, accuracy, quantitative and statistical data analysis, as well as live cell applications. State-of-the-art dual color single molecule imaging is introduced as the most direct experimental approach to study interaction dynamics between differently labeled target molecules. New analytical estimates for robust data analysis are presented that facilitate quantitative recording and identification of co localizations in dual color single molecule images. A novel dual color illumination scheme is further described that profoundly extends the current range and sensitivity of conventional dual color single molecule experiments. The method enables working at high surface densities of fluorescent molecules - a feature typically incommensurable with single molecule imaging - and is especially suited for the detection of rare interactions by tracking co localized

  13. Characterization of decommissioned reactor internals: Monte Carlo analysis technique

    International Nuclear Information System (INIS)

    Reid, B.D.; Love, E.F.; Luksic, A.T.

    1993-03-01

    This study discusses computer analysis techniques for determining activation levels of irradiated reactor component hardware to yield data for the Department of Energy's Greater-Than-Class C Low-Level Radioactive Waste Program. The study recommends the Monte Carlo Neutron/Photon (MCNP) computer code as the best analysis tool for this application and compares the technique to direct sampling methodology. To implement the MCNP analysis, a computer model would be developed to reflect the geometry, material composition, and power history of an existing shutdown reactor. MCNP analysis would then be performed using the computer model, and the results would be validated by comparison to laboratory analysis results from samples taken from the shutdown reactor. The report estimates uncertainties for each step of the computational and laboratory analyses; the overall uncertainty of the MCNP results is projected to be ±35%. The primary source of uncertainty is identified as the material composition of the components, and research is suggested to address that uncertainty

  14. Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis

    DEFF Research Database (Denmark)

    Flores Alsina, Xavier; Comas, J.; Rodríguez-Roda, I.

    2007-01-01

    The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant...... analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii......) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation...

  15. A Spatial and Temporal analysis of Labour Market Characteristics

    Directory of Open Access Journals (Sweden)

    Pośpiech Ewa

    2016-12-01

    Full Text Available The use of spatial methods is becoming increasingly common in social and economic research as it emphasizes the relevance of spatiality to the understanding of socio-economic facts. Once embraced, the spatial factor can substantially help explain variations in the properties being examined, thus improving the quality of their description and supporting the development of econometric models. This paper explores some of the characteristics of Poland’s job market, making an inquiry into their spatial dependencies. The study looks at the country’s labour market from a local perspective, examining its properties for spatial autocorrelation (both global and local. Linear econometric models are subsequently built for such variables as the number of persons in employment, the number of women and men in employment. The models are further investigated to assess the applicability of spatial modelling in their development.

  16. Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures

    Science.gov (United States)

    Noor, Ahmed K.; Peters, Jeanne M.

    1987-01-01

    An efficient preconditioned conjugate gradient (PCG) technique and a computational procedure are presented for the analysis of symmetric anisotropic structures. The technique is based on selecting the preconditioning matrix as the orthotropic part of the global stiffness matrix of the structure, with all the nonorthotropic terms set equal to zero. This particular choice of the preconditioning matrix results in reducing the size of the analysis model of the anisotropic structure to that of the corresponding orthotropic structure. The similarities between the proposed PCG technique and a reduction technique previously presented by the authors are identified and exploited to generate from the PCG technique direct measures for the sensitivity of the different response quantities to the nonorthotropic (anisotropic) material coefficients of the structure. The effectiveness of the PCG technique is demonstrated by means of a numerical example of an anisotropic cylindrical panel.

  17. Technique Triangulation for Validation in Directed Content Analysis

    Directory of Open Access Journals (Sweden)

    Áine M. Humble PhD

    2009-09-01

    Full Text Available Division of labor in wedding planning varies for first-time marriages, with three types of couples—traditional, transitional, and egalitarian—identified, but nothing is known about wedding planning for remarrying individuals. Using semistructured interviews, the author interviewed 14 couples in which at least one person had remarried and used directed content analysis to investigate the extent to which the aforementioned typology could be transferred to this different context. In this paper she describes how a triangulation of analytic techniques provided validation for couple classifications and also helped with moving beyond “blind spots” in data analysis. Analytic approaches were the constant comparative technique, rank order comparison, and visual representation of coding, using MAXQDA 2007's tool called TextPortraits.

  18. Coherent Code Tracking for Spatial Transmit Diversity DS-CDMA Systems

    Directory of Open Access Journals (Sweden)

    R. W. Stewart

    2005-09-01

    Full Text Available Spatial transmit diversity schemes are now well integrated into third-generation cellular mobile communication system specifications. When DS-CDMA-based technology is deployed in typical macro- and microcell environments, multipath diversity and spatial diversity may be exploited simultaneously by a 2D RAKE receiver. The work presented in this paper focuses on taking advantage of spatial transmit diversity in synchronising the 2D RAKE structure. We investigate the use of coherent and noncoherent techniques for tracking the timing parameters of each multipath component. It is shown that both noncoherent and coherent techniques benefit from transmit diversity. Additionally the performance gap between these two techniques increases with the number of antennas.

  19. The Determinants of VAT Introduction : A Spatial Duration Analysis

    NARCIS (Netherlands)

    Cizek, P.; Lei, J.; Ligthart, J.E.

    2012-01-01

    Abstract: The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. This specification relies highly on a pre-determinate covariance structure of the errors. However, the spatial effect may not only exist in the unobserved

  20. Feasibility of Triticale (Tritico secale wittmack. X Cropping in Agricultural Lands of Gorgan County by Spatial Analysis Tools

    Directory of Open Access Journals (Sweden)

    maral Niazmoradi

    2017-12-01

    agricultural lands of Gorgan county by spatial analysis of GIS and evaluation of environmental variables. Material and Methods One of the most important areas for crop production in Golestan province located in north of Iran, is the Gorgan region. This area is located between latitude 54° 12.9' N and 54° 44.9' N and longitude 36° 30.6' E and 36° 58.8' E.Almost every farm in Gorgan region are rainfed. In order to spatial feasibility of triticale cropping in Gorgan county, agroecological requirements of triticale was identified and classified from scientific resources. Some environmental factors including, climatic variables such as precipitation and temperature in scale of annual, monthly and seasonal, topographic variables such as elevation, slope aspects and slops percent, and some soil characteristics as texture, EC, pH, fertility, K, P and organic matter were evaluated using geostatistics and classic methods and then thematic layers were produced in ArcGIS media. In multi-criteria assessment process, one of the most important steps is to determine each criteria weight. Generally, AHP is suitable to determine the weights of assessment factors. In this respect, the first step is to construct an AHP model consisting objectives, criteria, sub-criteria, and alternatives. Then these digital layers were classified based on ecological requirements table of triticale and they were overlaid and interpolated in GIS media and final layer were classified to four classes of high suitable, suitable, less suitable and non-suitable. The suitability analysis was based on matching between land qualities/characteristics and crop requirements. It was accomplished by weighted overlay technique (WOT in GIS. Results and Discussion The results showed that 28.8 thousand ha (44.92% of agricultural lands were located in the high suitable class (S1. This zone was observed occasionally in north and northwest parts of studied region. This zone had the high fertility, high organic matter percent (2