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Sample records for spatial autocorrelation analysis

  1. Spatial autocorrelation analysis of tourist arrivals using municipal data: A Serbian example

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    Stankov Uglješa

    2017-01-01

    Full Text Available Spatial autocorrelation methodologies can be used to reveal patterns and temporal changes of different spatial variables, including tourism arrivals. The research adopts a GIS-based approach to spatially analyse tourist arrivals in Serbia, using Global Moran's I and Anselin's Local Moran's I statistics applied on the level of municipalities. To assess feasibility of this approach the article discusses spatial changes of tourist arrivals in order to identify potentially significant trends of interest for tourism development policy in Serbia. There is a significant spatial inequality in the distribution of tourism arrivals in Serbia that is not adequately addressed in tourism development plans. The results of global autocorrelation suggest the existence of low and decreasing spatial clustering for domestic tourist arrivals and high, relatively stable spatial clustering for international tourists. Local autocorrelation statistics revealed different of domestic and international tourism arrivals. In order to assess feasibility of this approach these results are discussed in their significance to tourism development policy in Serbia.

  2. New approaches for calculating Moran's index of spatial autocorrelation.

    Science.gov (United States)

    Chen, Yanguang

    2013-01-01

    Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

  3. New approaches for calculating Moran's index of spatial autocorrelation.

    Directory of Open Access Journals (Sweden)

    Yanguang Chen

    Full Text Available Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

  4. Consequences of spatial autocorrelation for niche-based models

    DEFF Research Database (Denmark)

    Segurado, P.; Araújo, Miguel B.; Kunin, W. E.

    2006-01-01

    1.  Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2.  Analyses were based o...

  5. Spatial Autocorrelation and Uncertainty Associated with Remotely-Sensed Data

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    Daniel A. Griffith

    2016-06-01

    Full Text Available Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pixels in realistically-sized remotely-sensed images, a situation that more recently has changed. Recent advances in spatial statistical estimation theory support the extraction of information and the distilling of knowledge from remotely-sensed images in a way that accounts for latent spatial autocorrelation. This paper summarizes an effective methodological approach to achieve this end, illustrating results with a 2002 remotely sensed-image of the Florida Everglades, and simulation experiments. Specifically, uncertainty of spatial autocorrelation parameter in a spatial autoregressive model is modeled with a beta-beta mixture approach and is further investigated with three different sampling strategies: coterminous sampling, random sub-region sampling, and increasing domain sub-regions. The results suggest that uncertainty associated with remotely-sensed data should be cast in consideration of spatial autocorrelation. It emphasizes that one remaining challenge is to better quantify the spatial variability of spatial autocorrelation estimates across geographic landscapes.

  6. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

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    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  7. A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

    Science.gov (United States)

    Suryowati, K.; Bekti, R. D.; Faradila, A.

    2018-04-01

    Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

  8. Balance Maintenance in the Upright Body Position: Analysis of Autocorrelation

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    Stodolka¹ Jacek

    2016-04-01

    Full Text Available The present research aimed to analyze values of the autocorrelation function measured for different time values of ground reaction forces during stable upright standing. It was hypothesized that if recording of force in time depended on the quality and way of regulating force by the central nervous system (as a regulator, then the application of autocorrelation for time series in the analysis of force changes in time function would allow to determine regulator properties and its functioning. The study was performed on 82 subjects (students, athletes, senior and junior soccer players and subjects who suffered from lower limb injuries. The research was conducted with the use of two Kistler force plates and was based on measurements of ground reaction forces taken during a 15 s period of standing upright while relaxed. The results of the autocorrelation function were statistically analyzed. The research revealed a significant correlation between a derivative extreme and velocity of reaching the extreme by the autocorrelation function, described as gradient strength. Low correlation values (all statistically significant were observed between time of the autocorrelation curve passing through 0 axis and time of reaching the first peak by the said function. Parameters computed on the basis of the autocorrelation function are a reliable means to evaluate the process of flow of stimuli in the nervous system. Significant correlations observed between the parameters of the autocorrelation function indicate that individual parameters provide similar properties of the central nervous system.

  9. Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

    Science.gov (United States)

    Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

    2017-08-07

    The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human

  10. Logistic regression for southern pine beetle outbreaks with spatial and temporal autocorrelation

    Science.gov (United States)

    M. L. Gumpertz; C.-T. Wu; John M. Pye

    2000-01-01

    Regional outbreaks of southern pine beetle (Dendroctonus frontalis Zimm.) show marked spatial and temporal patterns. While these patterns are of interest in themselves, we focus on statistical methods for estimating the effects of underlying environmental factors in the presence of spatial and temporal autocorrelation. The most comprehensive available information on...

  11. An investigation on thermal patterns in Iran based on spatial autocorrelation

    Science.gov (United States)

    Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

    2018-02-01

    The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

  12. Spatial Autocorrelation Patterns of Understory Plant Species in a Subtropical Rainforest at Lanjenchi, Southern Taiwan

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    Su-Wei Fan

    2010-06-01

    Full Text Available Many studies described relationships between plant species and intrinsic or exogenous factors, but few quantified spatial scales of species patterns. In this study, quantitative methods were used to explore the spatial scale of understory species (including resident and transient species, in order to identify the influential factors of species distribution. Resident species (including herbaceous species, climbers and tree ferns < 1 m high were investigated on seven transects, each 5-meter wide and 300-meter long, at Lanjenchi plot in Nanjenshan Reserve, southern Taiwan. Transient species (seedling of canopy, subcanopy and shrub species < 1 cm diameter at breast height were censused in three of the seven transects. The herb coverage and seedling abundance were calculated for each 5 × 5 m quadrat along the transects, and Moran’s I and Galiano’s new local variance (NLV indices were then used to identify the spatial scale of autocorrelation for each species. Patterns of species abundance of understory layer varied among species at fine scale within 50 meters. Resident species showed a higher proportion of significant autocorrelation than the transient species. Species with large size or prolonged fronds or stems tended to show larger scales in autocorrelation. However, dispersal syndromes and fruit types did not relate to any species’ spatial patterns. Several species showed a significant autocorrelation at a 180-meter class which happened to correspond to the local replicates of topographical features in hilltops. The spatial patterns of understory species at Lanjenchi plot are mainly influenced by species’ intrinsic traits and topographical characteristics.

  13. Periodicity in spatial data and geostatistical models: autocorrelation between patches

    Science.gov (United States)

    Volker C. Radeloff; Todd F. Miller; Hong S. He; David J. Mladenoff

    2000-01-01

    Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such...

  14. Power properties of invariant tests for spatial autocorrelation in linear regression

    NARCIS (Netherlands)

    Martellosio, F.

    2006-01-01

    Many popular tests for residual spatial autocorrelation in the context of the linear regression model belong to the class of invariant tests. This paper derives a number of exact properties of the power function of such tests. In particular, we extend the work of Krämer (2005, Journal of Statistical

  15. Simultaneous maximization of spatial and temporal autocorrelation in spatio-temporal data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2002-01-01

    . This is done by solving the generalized eigenproblem represented by the Rayleigh coefficient where is the dispersion of and is the dispersion of the difference between and spatially shifted. Hence, the new variates are obtained from the conjugate eigenvectors and the autocorrelations obtained are , i.e., high...

  16. Spatial autocorrelation in farmland grasshopper assemblages (Orthoptera: Acrididae) in western France.

    Science.gov (United States)

    Badenhausser, I; Gouat, M; Goarant, A; Cornulier, T; Bretagnolle, V

    2012-10-01

    Agricultural intensification in western Europe has caused a dramatic loss of grassland surfaces in farmlands, which have resulted in strong declines in grassland invertebrates, leading to cascade effects at higher trophic levels among consumers of invertebrates. Grasshoppers are important components of grassland invertebrate assemblages in European agricultural ecosystems, particularly as prey for bird species. Understanding how grasshopper populations are distributed in fragmented landscapes with low grassland availability is critical for both studies in biodiversity conservation and insect management. We assessed the range and strength of spatial autocorrelation for two grasshopper taxa (Gomphocerinae subfamily and Calliptamus italicus L.) across an intensive farmland in western France. Data from surveys carried out over 8 yr in 1,715 grassland fields were analyzed using geostatistics. Weak spatial patterns were observed at small spatial scales, suggesting important local effects of management practices on grasshopper densities. Spatial autocorrelation patterns for both grasshopper taxa were only detected at intermediate scales. For Gomphocerinae, the range of spatial autocorrelation varied from 802 to 2,613 m according to the year, depending both on grasshopper density and on grassland surfaces in the study site, whereas spatial patterns for the Italian locust were more variable and not related to grasshopper density or grassland surfaces. Spatial patterns in the distribution of Gomphocerinae supported our hypothesis that habitat availability was a major driver of grasshopper distribution in the landscape, and suggested it was related to density-dependent processes such as dispersal.

  17. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

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    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  18. Spatial autocorrelation method using AR model; Kukan jiko sokanho eno AR model no tekiyo

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Obuchi, T; Saito, T [Iwate University, Iwate (Japan). Faculty of Engineering

    1996-05-01

    Examination was made about the applicability of the AR model to the spatial autocorrelation (SAC) method, which analyzes the surface wave phase velocity in a microtremor, for the estimation of the underground structure. In this examination, microtremor data recorded in Morioka City, Iwate Prefecture, was used. In the SAC method, a spatial autocorrelation function with the frequency as a variable is determined from microtremor data observed by circular arrays. Then, the Bessel function is adapted to the spatial autocorrelation coefficient with the distance between seismographs as a variable for the determination of the phase velocity. The result of the AR model application in this study and the results of the conventional BPF and FFT method were compared. It was then found that the phase velocities obtained by the BPF and FFT methods were more dispersed than the same obtained by the AR model. The dispersion in the BPF method is attributed to the bandwidth used in the band-pass filter and, in the FFT method, to the impact of the bandwidth on the smoothing of the cross spectrum. 2 refs., 7 figs.

  19. Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach

    Science.gov (United States)

    Mohebbi, Mohammadreza; Wolfe, Rory; Forbes, Andrew

    2014-01-01

    This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference. PMID:24413702

  20. Análise quantitativa da influência de um novo paradigma ecológico: autocorrelação espacial - DOI: 10.4025/actascibiolsci.v25i1.2113 Quantitative analysis of the influence of a new ecological paradigm: spatial autocorrelation - DOI: 10.4025/actascibiolsci.v25i1.2113

    Directory of Open Access Journals (Sweden)

    Luis Mauricio Bini

    2003-04-01

    Full Text Available O objetivo desse trabalho foi o de avaliar a influência da autocorrelação espacial (ausência de independência estatística de observações obtidas ao longo do espaço geográfico nos estudos ecológicos. Para tanto, uma avaliação dos trabalhos que empregaram os métodos necessários para a quantificação da autocorrelação espacial foi realizada, utilizando os dados fornecidos pelo “Institute for Scientific Information”. Os resultados demonstraram que existe uma tendência crescente da utilização das análises de autocorrelação espacial em estudos ecológicos, e que a presença de autocorrelação espacial significativa foi detectada na maior parte dos estudos. Além disso, esses estudos foram desenvolvidos em vários países, por cientistas de diferentes nacionalidades, com diferentes grupos de organismos e em diferentes tipos de ecossistemas. Dessa forma, pode-se considerar que o reconhecimento explícito da estrutura espacial dos processos naturais, por meio da análise da autocorrelação espacial, é um novo paradigma dos estudos ecológicosThe aim of this paper was to evaluate the influence of the spatial autocorrelation (absence of independence among observations gathered along geographical space in ecological studies. For this task, an evaluation of the studies that used spatial autocorrelation analysis was carried out using the data furnished by the Institute for Scientific Information. There is a positive temporal tendency in the number of studies that used spatial autocorrelation analysis. A significant autocorrelation was detected in most studies. Moreover, scientist of several nationalities carried out these studies in different countries, with different organisms and in different types of ecosystems. In this way, it is possible to consider that the explicit incorporation of the spatial structure of natural processes, through the autocorrelation analysis, is a new ecological paradigm

  1. Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

    Science.gov (United States)

    Songhurst, Anna; Coulson, Tim

    2014-03-01

    Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

  2. Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

    2018-02-01

    In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

  3. Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

    Science.gov (United States)

    Miralha, L.; Kim, D.

    2017-12-01

    Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

  4. Functional Maximum Autocorrelation Factors

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg

    2005-01-01

    MAF outperforms the functional PCA in concentrating the interesting' spectra/shape variation in one end of the eigenvalue spectrum and allows for easier interpretation of effects. Conclusions. Functional MAF analysis is a useful methods for extracting low dimensional models of temporally or spatially......Purpose. We aim at data where samples of an underlying function are observed in a spatial or temporal layout. Examples of underlying functions are reflectance spectra and biological shapes. We apply functional models based on smoothing splines and generalize the functional PCA in......\\verb+~+\\$\\backslash\\$cite{ramsay97} to functional maximum autocorrelation factors (MAF)\\verb+~+\\$\\backslash\\$cite{switzer85,larsen2001d}. We apply the method to biological shapes as well as reflectance spectra. {\\$\\backslash\\$bf Methods}. MAF seeks linear combination of the original variables that maximize autocorrelation between...

  5. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

    Directory of Open Access Journals (Sweden)

    Brady J Mattsson

    Full Text Available Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

  6. Can spatial autocorrelation method be applied to arbitrary array shape; Kukan jiko sokanho no nin`i array eno tekiyo kanosei

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Iwamoto, K; Saito, T; Tachibana, M [Iwate University, Iwate (Japan). Faculty of Engineering

    1997-05-27

    Methods to learn underground structures by utilizing the dispersion phenomenon of surface waves contained in microtremors include the frequency-wave number analysis method (the F-K method) and the spatial autocorrelation method (the SAC method). Despite the fact that the SAC method is capable of exploring structures at greater depths, the method is not utilized because of its stringent restriction in arrangement of seismometers during observation that they must be arranged evenly on the same circumference. In order to eliminate this restriction in the SAC method, a research group in the Hokuriku University has proposed an expanded spatial autocorrelation (ESAC) method. Using the concept of the ESAC method as its base, a method was realized to improve phase velocity estimation by making a simulation on an array shifted to the radius direction. As a result of the discussion, it was found that the proposed improvement method can be applied to places where waves come from a number of directions, such as urban areas. If the improvement method can be applied, the spatial autocorrelation function needs not be even in the circumferential direction. In other words, the SAC method can be applied to arbitrary arrays. 1 ref., 7 figs.

  7. Auto-correlation analysis of wave heights in the Bay of Bengal

    Indian Academy of Sciences (India)

    Time series observations of significant wave heights in the Bay of Bengal were subjected to auto- correlation analysis to determine temporal variability scale. The analysis indicates an exponen- tial fall of auto-correlation in the first few hours with a decorrelation time scale of about six hours. A similar figure was found earlier ...

  8. Autocorrelation analysis of plasma plume light emissions in deep penetration laser welding of steel

    Czech Academy of Sciences Publication Activity Database

    Mrňa, Libor; Šarbort, Martin; Řeřucha, Šimon; Jedlička, Petr

    2017-01-01

    Roč. 29, č. 1 (2017), s. 1-10, č. článku 012009. ISSN 1042-346X R&D Projects: GA MŠk(CZ) LO1212; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : laser welding * plasma plume * light emissions * autocorrelation analysis * weld depth Subject RIV: BH - Optics, Masers, Lasers OBOR OECD: Optics (including laser optics and quantum optics) Impact factor: 1.492, year: 2016

  9. Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects

    Science.gov (United States)

    de la Mata, Tamara; Llano, Carlos

    2013-07-01

    Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.

  10. ADDING A NEW STEP WITH SPATIAL AUTOCORRELATION TO IMPROVE THE FOUR-STEP TRAVEL DEMAND MODEL WITH FEEDBACK FOR A DEVELOPING CITY

    Directory of Open Access Journals (Sweden)

    Xuesong FENG, Ph.D Candidate

    2009-01-01

    Full Text Available It is expected that improvement of transport networks could give rise to the change of spatial distributions of population-related factors and car ownership, which are expected to further influence travel demand. To properly reflect such an interdependence mechanism, an aggregate multinomial logit (A-MNL model was firstly applied to represent the spatial distributions of these exogenous variables of the travel demand model by reflecting the influence of transport networks. Next, the spatial autocorrelation analysis is introduced into the log-transformed A-MNL model (called SPA-MNL model. Thereafter, the SPA-MNL model is integrated into the four-step travel demand model with feedback (called 4-STEP model. As a result, an integrated travel demand model is newly developed and named as the SPA-STEP model. Using person trip data collected in Beijing, the performance of the SPA-STEP model is empirically compared with the 4-STEP model. It was proven that the SPA-STEP model is superior to the 4-STEP model in accuracy; most of the estimated parameters showed statistical differences in values. Moreover, though the results of the simulations to the same set of assumed scenarios by the 4-STEP model and the SPA-STEP model consistently suggested the same sustainable path for the future development of Beijing, it was found that the environmental sustainability and the traffic congestion for these scenarios were generally overestimated by the 4-STEP model compared with the corresponding analyses by the SPA-STEP model. Such differences were clearly generated by the introduction of the new modeling step with spatial autocorrelation.

  11. A Novel Acoustic Liquid Level Determination Method for Coal Seam Gas Wells Based on Autocorrelation Analysis

    Directory of Open Access Journals (Sweden)

    Ximing Zhang

    2017-11-01

    Full Text Available In coal seam gas (CSG wells, water is periodically removed from the wellbore in order to keep the bottom-hole flowing pressure at low levels, facilitating the desorption of methane gas from the coal bed. In order to calculate gas flow rate and further optimize well performance, it is necessary to accurately monitor the liquid level in real-time. This paper presents a novel method based on autocorrelation function (ACF analysis for determining the liquid level in CSG wells under intense noise conditions. The method involves the calculation of the acoustic travel time in the annulus and processing the autocorrelation signal in order to extract the weak echo under high background noise. In contrast to previous works, the non-linear dependence of the acoustic velocity on temperature and pressure is taken into account. To locate the liquid level of a coal seam gas well the travel time is computed iteratively with the non-linear velocity model. Afterwards, the proposed method is validated using experimental laboratory investigations that have been developed for liquid level detection under two scenarios, representing the combination of low pressure, weak signal, and intense noise generated by gas flowing and leakage. By adopting an evaluation indicator called Crest Factor, the results have shown the superiority of the ACF-based method compared to Fourier filtering (FFT. In the two scenarios, the maximal measurement error from the proposed method was 0.34% and 0.50%, respectively. The latent periodic characteristic of the reflected signal can be extracted by the ACF-based method even when the noise is larger than 1.42 Pa, which is impossible for FFT-based de-noising. A case study focused on a specific CSG well is presented to illustrate the feasibility of the proposed approach, and also to demonstrate that signal processing with autocorrelation analysis can improve the sensitivity of the detection system.

  12. Application of the Spatial Auto-Correlation Method for Shear-Wave Velocity Studies Using Ambient Noise

    Science.gov (United States)

    Asten, M. W.; Hayashi, K.

    2018-05-01

    Ambient seismic noise or microtremor observations used in spatial auto-correlation (SPAC) array methods consist of a wide frequency range of surface waves from the frequency of about 0.1 Hz to several tens of Hz. The wavelengths (and hence depth sensitivity of such surface waves) allow determination of the site S-wave velocity model from a depth of 1 or 2 m down to a maximum of several kilometres; it is a passive seismic method using only ambient noise as the energy source. Application usually uses a 2D seismic array with a small number of seismometers (generally between 2 and 15) to estimate the phase velocity dispersion curve and hence the S-wave velocity depth profile for the site. A large number of methods have been proposed and used to estimate the dispersion curve; SPAC is the one of the oldest and the most commonly used methods due to its versatility and minimal instrumentation requirements. We show that direct fitting of observed and model SPAC spectra generally gives a superior bandwidth of useable data than does the more common approach of inversion after the intermediate step of constructing an observed dispersion curve. Current case histories demonstrate the method with a range of array types including two-station arrays, L-shaped multi-station arrays, triangular and circular arrays. Array sizes from a few metres to several-km in diameter have been successfully deployed in sites ranging from downtown urban settings to rural and remote desert sites. A fundamental requirement of the method is the ability to average wave propagation over a range of azimuths; this can be achieved with either or both of the wave sources being widely distributed in azimuth, and the use of a 2D array sampling the wave field over a range of azimuths. Several variants of the method extend its applicability to under-sampled data from sparse arrays, the complexity of multiple-mode propagation of energy, and the problem of precise estimation where array geometry departs from an

  13. Environmental Correlation and Spatial Autocorrelation of Soil Properties in Keller Peninsula, Maritime Antarctica

    Directory of Open Access Journals (Sweden)

    André Geraldo de Lima Moraes

    2018-01-01

    Full Text Available ABSTRACT: The pattern of variation in soil and landform properties in relation to environmental covariates are closely related to soil type distribution. The aim of this study was to apply digital soil mapping techniques to analysis of the pattern of soil property variation in relation to environmental covariates under periglacial conditions at Keller Peninsula, Maritime Antarctica. We considered the hypothesis that covariates normally used for environmental correlation elsewhere can be adequately employed in periglacial areas in Maritime Antarctica. For that purpose, 138 soil samples from 47 soil sites were collected for analysis of soil chemical and physical properties. We tested the correlation between soil properties (clay, potassium, sand, organic carbon, and pH and environmental covariates. The environmental covariates selected were correlated with soil properties according to the terrain attributes of the digital elevation model (DEM. The models evaluated were linear regression, ordinary kriging, and regression kriging. The best performance was obtained using normalized height as a covariate, with an R2 of 0.59 for sand. In contrast, the lowest R2 of 0.15 was obtained for organic carbon, also using the regression kriging method. Overall, results indicate that, despite the predominant periglacial conditions, the environmental covariates normally used for digital terrain mapping of soil properties worldwide can be successfully employed for understanding the main variations in soil properties and soil-forming factors in this region.

  14. Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis

    Science.gov (United States)

    Cheng, Yezeng; Larin, Kirill V.

    2006-12-01

    Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

  15. Search for neutrino point sources with an all-sky autocorrelation analysis in IceCube

    Energy Technology Data Exchange (ETDEWEB)

    Turcati, Andrea; Bernhard, Anna; Coenders, Stefan [TU, Munich (Germany); Collaboration: IceCube-Collaboration

    2016-07-01

    The IceCube Neutrino Observatory is a cubic kilometre scale neutrino telescope located in the Antarctic ice. Its full-sky field of view gives unique opportunities to study the neutrino emission from the Galactic and extragalactic sky. Recently, IceCube found the first signal of astrophysical neutrinos with energies up to the PeV scale, but the origin of these particles still remains unresolved. Given the observed flux, the absence of observations of bright point-sources is explainable with the presence of numerous weak sources. This scenario can be tested using autocorrelation methods. We present here the sensitivities and discovery potentials of a two-point angular correlation analysis performed on seven years of IceCube data, taken between 2008 and 2015. The test is applied on the northern and southern skies separately, using the neutrino energy information to improve the effectiveness of the method.

  16. Pair and triplet approximation of a spatial lattice population model with multiscale dispersal using Markov chains for estimating spatial autocorrelation.

    Science.gov (United States)

    Hiebeler, David E; Millett, Nicholas E

    2011-06-21

    We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. 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.

  18. 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

  19. Discussion on sensor location in circular array for spatial autocorrelation method; Kukan jiko sokanho no enkei array ni okeru jishinkei haichi no kento

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Iwamoto, K; Saito, T; Yoshida, A [Iwate University, Iwate (Japan). Faculty of Engineering

    1997-05-27

    Methods to derive underground structures by utilizing the dispersion phenomenon of surface waves contained in microtremors include the frequency-wave number analysis method (the F-K method) and the spatial autocorrelation method (SAC method). The SAC method is said capable of estimating the structures to deeper depths than with the F-K method if the same seismometer is used. However, the F-K method is used more frequently. This is because the SAC method imposes a strict restriction that seismometers must be arranged evenly on the same circumference, while the F-K method allows seismometers to be arranged arbitrarily during an observation. Therefore, the present study has discussed whether the SAC method can be applied to observations with the seismometers arranged in the same way as in the F-K method, by using microtremor data acquired from actual observations. It was made clear that a seismometer arrangement for the SAC method may be sufficed with at least three meters arranged on the same circumference. These meters may not have to be arranged evenly, but because the acquired phase velocities may vary according to wave arriving directions and seismometer arrangement, it is desirable to perform observations with seismometers arranged as evenly as possible. 13 figs.

  20. Spatial Autocorrelation, Source Water and the Distribution of Total and Viable Microbial Abundances within a Crystalline Formation to a Depth of 800 m

    Directory of Open Access Journals (Sweden)

    E. D. Beaton

    2017-09-01

    Full Text Available Proposed radioactive waste repositories require long residence times within deep geological settings for which we have little knowledge of local or regional subsurface dynamics that could affect the transport of hazardous species over the period of radioactive decay. Given the role of microbial processes on element speciation and transport, knowledge and understanding of local microbial ecology within geological formations being considered as host formations can aid predictions for long term safety. In this relatively unexplored environment, sampling opportunities are few and opportunistic. We combined the data collected for geochemistry and microbial abundances from multiple sampling opportunities from within a proposed host formation and performed multivariate mixing and mass balance (M3 modeling, spatial analysis and generalized linear modeling to address whether recharge can explain how subsurface communities assemble within fracture water obtained from multiple saturated fractures accessed by boreholes drilled into the crystalline formation underlying the Chalk River Laboratories site (Deep River, ON, Canada. We found that three possible source waters, each of meteoric origin, explained 97% of the samples, these are: modern recharge, recharge from the period of the Laurentide ice sheet retreat (ca. ∼12000 years before present and a putative saline source assigned as Champlain Sea (also ca. 12000 years before present. The distributed microbial abundances and geochemistry provide a conceptual model of two distinct regions within the subsurface associated with bicarbonate – used as a proxy for modern recharge – and manganese; these regions occur at depths relevant to a proposed repository within the formation. At the scale of sampling, the associated spatial autocorrelation means that abundances linked with geochemistry were not unambiguously discerned, although fine scale Moran’s eigenvector map (MEM coefficients were correlated with

  1. Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

    Science.gov (United States)

    Mei, Zhixiong; Wu, Hao; Li, Shiyun

    2018-06-01

    The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the

  2. Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility

    Energy Technology Data Exchange (ETDEWEB)

    Kirby, R. Jason [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States); Qi, Feng [Sanford Burnham Prebys Medical Discovery Institute, Applied Bioinformatics Facility, 6400 Sanger Rd, Orlando, FL 32827 (United States); Phatak, Sharangdhar; Smith, Layton H. [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States); Malany, Siobhan, E-mail: smalany@sbpdiscovery.org [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States)

    2016-08-15

    Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data.

  3. Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility

    International Nuclear Information System (INIS)

    Kirby, R. Jason; Qi, Feng; Phatak, Sharangdhar; Smith, Layton H.; Malany, Siobhan

    2016-01-01

    Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data

  4. AFM topographies of densely packed nanoparticles: a quick way to determine the lateral size distribution by autocorrelation function analysis

    International Nuclear Information System (INIS)

    Fekete, L.; Kůsová, K.; Petrák, V.; Kratochvílová, I.

    2012-01-01

    The distribution of sizes is one of the basic characteristics of nanoparticles. Here, we propose a novel way to determine the lateral distribution of sizes from AFM topographies. Our algorithm is based on the autocorrelation function and can be applied both on topographies containing spatially separated and densely packed nanoparticles as well as on topographies of polycrystalline films. As no manual treatment is required, this algorithm can be easily automatable for batch processing. The algorithm works in principle with any kind of spatially mapped information (AFM current maps, optical microscope images, etc.), and as such has no size limitations. However, in the case of AFM topographies, the tip/sample convolution effects will be the factor limiting the smallest size to which the algorithm is applicable. Here, we demonstrate the usefulness of this algorithm on objects with sizes ranging between 20 nm and 1.5 μm.

  5. On the Decay Ratio Determination in BWR Stability Analysis by Auto-Correlation Function Techniques

    International Nuclear Information System (INIS)

    Behringer, K.; Hennig, D.

    2002-11-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. These models, corrected for signal filtering and including a background term under the peak in the PSD, are then least-squares fitted to the ACF of the previously filtered neutron signal, in order to determine the oscillation frequency and the decay ratio. Our method uses fast Fourier transform techniques with signal segmentation for filtering and ACF estimation. Gliding 'short-term' ACF estimates on a record allow the evaluation of uncertainties. Numerical results are given which have been obtained from neutron data of the recent Forsmark I and Forsmark II NEA benchmark project. Our results are compared with those obtained by other participants in the benchmark project. The present PSI report is an extended version of the publication K. Behringer, D. Hennig 'A novel auto-correlation function method for the determination of the decay ratio in BWR stability studies' (Behringer, Hennig, 2002)

  6. FREQUENCY ANALYSIS OF RLE-BLOCKS REPETITIONS IN THE SERIES OF BINARY CODES WITH OPTIMAL MINIMAX CRITERION OF AUTOCORRELATION FUNCTION

    Directory of Open Access Journals (Sweden)

    A. A. Kovylin

    2013-01-01

    Full Text Available The article describes the problem of searching for binary pseudo-random sequences with quasi-ideal autocorrelation function, which are to be used in contemporary communication systems, including mobile and wireless data transfer interfaces. In the synthesis of binary sequences sets, the target set is manning them based on the minimax criterion by which a sequence is considered to be optimal according to the intended application. In the course of the research the optimal sequences with order of up to 52 were obtained; the analysis of Run Length Encoding was carried out. The analysis showed regularities in the distribution of series number of different lengths in the codes that are optimal on the chosen criteria, which would make it possible to optimize the searching process for such codes in the future.

  7. Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis [chapter 7

    Science.gov (United States)

    Samuel A. Cushman

    2010-01-01

    In the previous chapter we presented the idea of a multi-layer, multi-scale, spatially referenced data-cube as the foundation for monitoring and for implementing flexible modeling of ecological pattern-process relationships in particulate, in context and to integrate these across large spatial extents at the grain of the strongest linkage between response and driving...

  8. A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

    Science.gov (United States)

    Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

    2018-01-01

    Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

  9. Parallel auto-correlative statistics with VTK.

    Energy Technology Data Exchange (ETDEWEB)

    Pebay, Philippe Pierre; Bennett, Janine Camille

    2013-08-01

    This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

  10. On-site processing systems for determination of the phase velocity of Rayleigh waves in microtremors using the spatial autocorrelation method; Kukan jiko sokanho wo mochiita bidochu no Rayleigh ha iso sokudo no genba kettei system

    Energy Technology Data Exchange (ETDEWEB)

    Matsuoka, T; Umezawa, N [Saitama Institute of Environmental Pollution, Saitama (Japan)

    1996-05-01

    To render the spatial autocorrelation (SAC) method easier to use, a system has been constructed that can be used with ease on the site for the calculation of phase velocities. This system can perform two observation methods of the same frequency characteristics, that is, the simultaneous multi-point observation and one-point independent observation. The pickup is a velocity type seismograph of a natural period of 1 second that has been so electrically adjusted as to work on an apparent natural period of 7 seconds. Among the frequency characteristics, those related to phase are regarded as important because the SAC method is based on the measurement of coherence between two points. The analysis software runs on a waveform processing software DADiSP/WIN designed for personal computers. To know the operability of this system on the site and to accumulate records using the SAC method, observations were made at the depth of 100-500m at 6 locations in Saitama Prefecture where the underground structure was known thanks to prior PS logging. As the result, a dispersion curve was obtained by use of an array of appropriate dimensions at every location agreeing with the underground structure. 9 refs., 10 figs.

  11. 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

  12. 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.

  13. AFM topographies of densely packed nanoparticles: a quick way to determine the lateral size distribution by autocorrelation function analysis

    Czech Academy of Sciences Publication Activity Database

    Fekete, Ladislav; Kůsová, Kateřina; Petrák, Václav; Kratochvílová, Irena

    2012-01-01

    Roč. 14, č. 8 (2012), s. 1-10 ISSN 1388-0764 R&D Projects: GA AV ČR KAN200100801; GA TA ČR TA01011165; GA ČR(CZ) GAP304/10/1951; GA ČR GPP204/12/P235 Institutional research plan: CEZ:AV0Z10100520 Keywords : lateral grain size distribution * AFM * autocorrelation function * nanodiamond Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.175, year: 2012

  14. Recommended number of strides for automatic assessment of gait symmetry and regularity in above-knee amputees by means of accelerometry and autocorrelation analysis

    Directory of Open Access Journals (Sweden)

    Tura Andrea

    2012-02-01

    Full Text Available Abstract Background Symmetry and regularity of gait are essential outcomes of gait retraining programs, especially in lower-limb amputees. This study aims presenting an algorithm to automatically compute symmetry and regularity indices, and assessing the minimum number of strides for appropriate evaluation of gait symmetry and regularity through autocorrelation of acceleration signals. Methods Ten transfemoral amputees (AMP and ten control subjects (CTRL were studied. Subjects wore an accelerometer and were asked to walk for 70 m at their natural speed (twice. Reference values of step and stride regularity indices (Ad1 and Ad2 were obtained by autocorrelation analysis of the vertical and antero-posterior acceleration signals, excluding initial and final strides. The Ad1 and Ad2 coefficients were then computed at different stages by analyzing increasing portions of the signals (considering both the signals cleaned by initial and final strides, and the whole signals. At each stage, the difference between Ad1 and Ad2 values and the corresponding reference values were compared with the minimum detectable difference, MDD, of the index. If that difference was less than MDD, it was assumed that the portion of signal used in the analysis was of sufficient length to allow reliable estimation of the autocorrelation coefficient. Results All Ad1 and Ad2 indices were lower in AMP than in CTRL (P Conclusions Without the need to identify and eliminate the phases of gait initiation and termination, twenty strides can provide a reasonable amount of information to reliably estimate gait regularity in transfemoral amputees.

  15. Exploration of underground basement structures in Kanto plain using the spatial autocorrelation method. 1. S-wave velocity structure along the line from Hatoyama, Saitama to Noda, Chiba; Kukan jiko sokanho ni yoru Kanto heiya no kiban kozo tansa. 1. Saitamaken Hatoyama machi - Chibaken Nodashi kan no S ha sokudo kozo

    Energy Technology Data Exchange (ETDEWEB)

    Matsuoka, T; Umezawa, N; Shiraishi, H [Saitama Institute of Environmental Pollution, Saitama (Japan)

    1997-05-27

    The Saitama prefectural government has been conducting basement structure exploration using the spatial autocorrelation method by dividing the entire plain area into meshes, for the purpose of improving the accuracy of estimating large-scale seismic damages. This paper reports the result of explorations on meshes in the east-west direction in the central part of Saitama Prefecture. The present exploration was intended on ten meshes in the east-west direction along the north latitude 36-degree line. The number of exploration points is 13 comprising three points on the hilly area bordering on the eastern edge of the Kanto mountainous area and ten points on the plain area. The arrangement constitutes a traverse line with a total distance of about 33 km from the west edge (Hatoyama-machi in Saitama Prefecture) to the east edge (Noda City in Chiba Prefecture). The phase velocities were estimated from the result of the array microtremor observations using the spatial autocorrelation method applied with the FET. The phase velocities were used to estimate underground structures by using an inverse analysis. As a result, detailed two-dimensional S-wave velocity structures were revealed on the traverse line. The velocity cross section expresses change in the basement structures with sufficient resolution, and at the same time the information is judged highly harmonious with existing deep boring data and the result of artificial earthquake exploration. 15 refs., 6 figs.

  16. Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

    NARCIS (Netherlands)

    Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

    2015-01-01

    Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

  17. Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

    NARCIS (Netherlands)

    Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

    Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

  18. 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

  19. 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.

  20. 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.

  1. Application of computer intensive data analysis methods to the analysis of digital images and spatial data

    DEFF Research Database (Denmark)

    Windfeld, Kristian

    1992-01-01

    Computer-intensive methods for data analysis in a traditional setting has developed rapidly in the last decade. The application of and adaption of some of these methods to the analysis of multivariate digital images and spatial data are explored, evaluated and compared to well established classical...... into the projection pursuit is presented. Examples from remote sensing are given. The ACE algorithm for computing non-linear transformations for maximizing correlation is extended and applied to obtain a non-linear transformation that maximizes autocorrelation or 'signal' in a multivariate image....... This is a generalization of the minimum /maximum autocorrelation factors (MAF's) which is a linear method. The non-linear method is compared to the linear method when analyzing a multivariate TM image from Greenland. The ACE method is shown to give a more detailed decomposition of the image than the MAF-transformation...

  2. Poincaré plot analysis of autocorrelation function of RR intervals in patients with acute myocardial infarction.

    Science.gov (United States)

    Chuang, Shin-Shin; Wu, Kung-Tai; Lin, Chen-Yang; Lee, Steven; Chen, Gau-Yang; Kuo, Cheng-Deng

    2014-08-01

    The Poincaré plot of RR intervals (RRI) is obtained by plotting RRIn+1 against RRIn. The Pearson correlation coefficient (ρRRI), slope (SRRI), Y-intercept (YRRI), standard deviation of instantaneous beat-to-beat RRI variability (SD1RR), and standard deviation of continuous long-term RRI variability (SD2RR) can be defined to characterize the plot. Similarly, the Poincaré plot of autocorrelation function (ACF) of RRI can be obtained by plotting ACFk+1 against ACFk. The corresponding Pearson correlation coefficient (ρACF), slope (SACF), Y-intercept (YACF), SD1ACF, and SD2ACF can be defined similarly to characterize the plot. By comparing the indices of Poincaré plots of RRI and ACF between patients with acute myocardial infarction (AMI) and patients with patent coronary artery (PCA), we found that the ρACF and SACF were significantly larger, whereas the RMSSDACF/SDACF and SD1ACF/SD2ACF were significantly smaller in AMI patients. The ρACF and SACF correlated significantly and negatively with normalized high-frequency power (nHFP), and significantly and positively with normalized very low-frequency power (nVLFP) of heart rate variability in both groups of patients. On the contrary, the RMSSDACF/SDACF and SD1ACF/SD2ACF correlated significantly and positively with nHFP, and significantly and negatively with nVLFP and low-/high-frequency power ratio (LHR) in both groups of patients. We concluded that the ρACF, SACF, RMSSDACF/SDACF, and SD1ACF/SD2ACF, among many other indices of ACF Poincaré plot, can be used to differentiate between patients with AMI and patients with PCA, and that the increase in ρACF and SACF and the decrease in RMSSDACF/SDACF and SD1ACF/SD2ACF suggest an increased sympathetic and decreased vagal modulations in both groups of patients.

  3. 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.

  4. Linear Prediction Using Refined Autocorrelation Function

    Directory of Open Access Journals (Sweden)

    M. Shahidur Rahman

    2007-07-01

    Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

  5. Review of relationships between grey-tone co-occurrence, semivariance, and autocorrelation based image texture analysis approaches

    NARCIS (Netherlands)

    Sanden, van der J.J.; Hoekman, D.H.

    2005-01-01

    In the present paper we review relationships between commonly used statistical approaches to analysis of image texture. The approaches considered characterize image texture by means of the statistics of grey- tone co- occurrence contrast, grey- tone co- occurrence correlation, semivariance, and

  6. A novel auto-correlation function method and FORTRAN codes for the determination of the decay ratio in BWR stability analysis

    International Nuclear Information System (INIS)

    Behringer, K.

    2001-08-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)

  7. A novel auto-correlation function method and FORTRAN codes for the determination of the decay ratio in BWR stability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Behringer, K

    2001-08-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)

  8. 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.

  9. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  10. 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

  11. 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.

  12. An autocorrelation method to detect low frequency earthquakes within tremor

    Science.gov (United States)

    Brown, J.R.; Beroza, G.C.; Shelly, D.R.

    2008-01-01

    Recent studies have shown that deep tremor in the Nankai Trough under western Shikoku consists of a swarm of low frequency earthquakes (LFEs) that occur as slow shear slip on the down-dip extension of the primary seismogenic zone of the plate interface. The similarity of tremor in other locations suggests a similar mechanism, but the absence of cataloged low frequency earthquakes prevents a similar analysis. In this study, we develop a method for identifying LFEs within tremor. The method employs a matched-filter algorithm, similar to the technique used to infer that tremor in parts of Shikoku is comprised of LFEs; however, in this case we do not assume the origin times or locations of any LFEs a priori. We search for LFEs using the running autocorrelation of tremor waveforms for 6 Hi-Net stations in the vicinity of the tremor source. Time lags showing strong similarity in the autocorrelation represent either repeats, or near repeats, of LFEs within the tremor. We test the method on an hour of Hi-Net recordings of tremor and demonstrates that it extracts both known and previously unidentified LFEs. Once identified, we cross correlate waveforms to measure relative arrival times and locate the LFEs. The results are able to explain most of the tremor as a swarm of LFEs and the locations of newly identified events appear to fill a gap in the spatial distribution of known LFEs. This method should allow us to extend the analysis of Shelly et al. (2007a) to parts of the Nankai Trough in Shikoku that have sparse LFE coverage, and may also allow us to extend our analysis to other regions that experience deep tremor, but where LFEs have not yet been identified. Copyright 2008 by the American Geophysical Union.

  13. 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....

  14. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  15. 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...

  16. Computation and analysis of the transverse current autocorrelation function, Ct(k,t), for small wave vectors: A molecular-dynamics study for a Lennard-Jones fluid

    Science.gov (United States)

    Vogelsang, R.; Hoheisel, C.

    1987-02-01

    Molecular-dynamics (MD) calculations are reported for three thermodynamic states of a Lennard-Jones fluid. Systems of 2048 particles and 105 integration steps were used. The transverse current autocorrelation function, Ct(k,t), has been determined for wave vectors of the range 0.5viscosities which showed a systematic behavior as a function of k. Extrapolation to the hydrodynamic region at k=0 gave shear viscosity coefficients in good agreement with direct Green-Kubo results obtained in previous work. The two-exponential model fit for the memory function proposed by other authors does not provide a reasonable description of the MD results, as the fit parameters show no systematic wave-vector dependence, although the Ct(k,t) functions are somewhat better fitted. Similarly, the semiempirical interpolation formula for the decay time based on the viscoelastic concept proposed by Akcasu and Daniels fails to reproduce the correct k dependence for the wavelength range investigated herein.

  17. 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.

  18. 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

  19. Coded aperture imagery filtered autocorrelation decoding; Imagerie par ouverture de codage decodage par autocorrelation filtree

    Energy Technology Data Exchange (ETDEWEB)

    Rouyer, A. [CEA Bruyeres-le-Chatel, 91 (France)

    2005-10-15

    Coded aperture imagery is particularly suited for imaging objects emitting penetrating radiation (hard X rays, gamma, neutrons), or for particles with rectilinear trajectories (electrons, protons, alpha particles, etc.). It is used when methods based on classical optical principles (reflection, refraction, diffraction), are invalid, or when the source emission is too weak for the well known pinhole method to give a usable image. The optical system consists in an aperture through an absorbing screen, named coding aperture, whose transmission is calculated in such a way that the spatial resolution is similar to that of a simple pinhole device, but with a far superior radiation collecting efficiency. We present a new decoding method,, called filtered autocorrelation, and illustrate its performances on images obtained with various coding apertures. (author)

  20. 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.

  1. The specification of weight structures in network autocorrelation models of social influence

    NARCIS (Netherlands)

    Leenders, Roger Th.A.J.

    2002-01-01

    Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models,

  2. Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

    Science.gov (United States)

    Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

    2007-01-01

    This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than

  3. A simple method to estimate interwell autocorrelation

    Energy Technology Data Exchange (ETDEWEB)

    Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.

  4. 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

  5. Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

    Science.gov (United States)

    Wittemyer, George; Polansky, Leo; Douglas-Hamilton, Iain; Getz, Wayne M

    2008-12-09

    The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series. This autocorrelation is weaker during the wet season, indicating random movements are more common when ecological conditions are good. Periodograms of socially dominant individuals are consistent across seasons, whereas subordinate individuals show distinct differences diverging from that of dominants during the dry season. We link temporally localized statistical properties of movement to landscape features and find that diurnal movement correlation is more common within protected wildlife areas, and multiday movement correlations found among lower ranked individuals are typically outside of protected areas where predation risks are greatest. A frequency-related spatial analysis of movement-step lengths reveal that rest cycles related to the spatial distribution of critical resources (i.e., forage and water) are responsible for creating the observed patterns. Our approach generates unique information regarding the spatial-temporal interplay between environmental and individual characteristics, providing an original approach for understanding the movement ecology of individual animals and the spatial organization of animal populations.

  6. General simulation algorithm for autocorrelated binary processes.

    Science.gov (United States)

    Serinaldi, Francesco; Lombardo, Federico

    2017-02-01

    The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

  7. General simulation algorithm for autocorrelated binary processes

    Science.gov (United States)

    Serinaldi, Francesco; Lombardo, Federico

    2017-02-01

    The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

  8. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2001-01-01

    Based on the analysis of auto-correlation function, the notion of the distance between auto-correlation function was quoted, and the characterization of the noise and the signal with noise were discussed by using the distance. Then, the method of auto- adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low signal with noise ratio circumstance

  9. 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...

  10. Persistent spatial clusters of plasmacytosis among Danish mink farms

    DEFF Research Database (Denmark)

    Themudo, Goncalo Espregueira Cruz; Østergaard, Jørgen; Ersbøll, Annette Kjær

    2011-01-01

    % in 1996. Nevertheless, the disease persists in the Vendsyssel district of Northern Jutland, despite the eradication efforts. In this study, we used spatial epidemiological analysis to test for spatial autocorrelation of the distribution of farms positive for the disease. We investigated 2375 farms...

  11. 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.

  12. Autocorrelation in queuing network-type production systems - revisited

    DEFF Research Database (Denmark)

    Nielsen, Erland Hejn

    2007-01-01

    , either production managers are missing important aspects in production planning, or the 'realistic' autocorrelation patterns inherent in actual production setups are not like those considered in the literature. In this paper, relevant and 'realistic' types of autocorrelation schemes are characterised...

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

    Science.gov (United States)

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

    2016-01-01

    The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77–7.61), diarrhea (OR = 2.16, 95% CI = 1.24–3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04–35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region. PMID:26903612

  14. 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.

  15. Nanoscale and femtosecond optical autocorrelator based on a single plasmonic nanostructure

    International Nuclear Information System (INIS)

    Melentiev, P N; Afanasiev, A E; Balykin, V I; Tausenev, A V; Konyaschenko, A V; Klimov, V V

    2014-01-01

    We demonstrated a nanoscale size, ultrafast and multiorder optical autocorrelator with a single plasmonic nanostructure for measuring the spatio-temporal dynamics of femtosecond laser light. As a nanostructure, we use a split hole resonator (SHR), which was made in an aluminium nanofilm. The Al material yields the fastest response time (100 as). The SHR nanostructure ensures a high nonlinear optical efficiency of the interaction with laser radiation, which leads to (1) the second, (2) the third harmonics generation and (3) the multiphoton luminescence, which, in turn, are used to perform multi-order autocorrelation measurements. The nano-sized SHR makes it possible to conduct autocorrelation measurements (i) with a subwavelength spatial resolution and (ii) with no significant influence on the duration of the laser pulse. The time response realized by the SHR nanostructure is about 10 fs. (letter)

  16. The study for the Spatial Distribution Pattern of NDVI in the Western of Jilin Province

    Science.gov (United States)

    Yang, Shu-jie; Li, Xiao-dong; Yan, Shou-gang

    2018-02-01

    Using methods of spatial autocorrelation analysis and trend analysis, the paper studies the spatial distribution pattern of NDVI based on the GIMMS NDVI dataset (1998-2008), in Western Jilin. The maximum value for 15d is got through the method of MAX processing. Results show that: the NDVI in growing season shows a rising trend in western Jilin in 1998-2008. In the study area, the NDVI in Western Jilin shows positive spatial autocorrelation in the whole region, but the partial NDVI is apt to scattered distribution, which means the vegetation cover of Western Jilin is generally fragmental.

  17. Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

    Science.gov (United States)

    Wallace, C.S.A.; Marsh, S.E.

    2005-01-01

    Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

  18. Applying spatial clustering analysis to a township-level social vulnerability assessment in Taiwan

    Directory of Open Access Journals (Sweden)

    Wen-Yen Lin

    2016-09-01

    Full Text Available The degree of social vulnerability may vary according to the conditions and backgrounds of different locations, yet spatial clustering phenomena may exist when nearby spatial units exhibit similar characteristics. This study applied spatial autocorrelation statistics to analyze the spatial association of vulnerability among townships in Taiwan. The vulnerability was first assessed on the basis of a social vulnerability index that was constructed using Fuzzy Delphi and analytic hierarchy process methods. Subsequently, the corresponding indicator variables were applied to calculate standardized vulnerability assessment scores by using government data. According to the results of the vulnerability assessment in which T scores were normalized, the distribution of social vulnerabilities varied among the townships. The scores were further analyzed using spatial autocorrelation statistics for spatial clustering of vulnerability distribution. The Local G statistic identified 42 significant spatial association pockets, whereas the Global G statistic indicated no spatial phenomenon of clustering. This phenomenon was verified and explained by applying Moran's I statistics to examine the homogeneity and heterogeneity of spatial associations. Although both statistics were originally designed to identify the existence of spatial clustering, they serve diverse purposes, and the results can be compared to obtain additional insights into the distribution patterns of social vulnerability.

  19. 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.

  20. Search paths of swans foraging on spatially autocorrelated tubers

    NARCIS (Netherlands)

    Nolet, B.A.; Mooij, W.M.

    2002-01-01

    1. Tundra swans forage on below-ground pondweed tubers that are heterogeneously distributed in space. The swans have no visual cues to delineate patches. It was tested whether swans employ an area-restricted search tactic. Theory predicts that swans should alternate between an intensive (low-speed,

  1. An improved Fuzzy Kappa statistic that accounts for spatial autocorrelation

    NARCIS (Netherlands)

    Hagen - Zanker, A.H.

    2009-01-01

    The Fuzzy Kappa statistic expresses the agreement between two categorical raster maps. The statistic goes beyond cell-by-cell comparison and gives partial credit to cells based on the categories found in the neighborhood. When matching categories are found at shorter distances the agreement is

  2. Assessment of smoothed spectra using autocorrelation function

    International Nuclear Information System (INIS)

    Urbanski, P.; Kowalska, E.

    2006-01-01

    Recently, data and signal smoothing became almost standard procedures in the spectrometric and chromatographic methods. In radiometry, the main purpose to apply smoothing is minimisation of the statistical fluctuation and avoid distortion. The aim of the work was to find a qualitative parameter, which could be used, as a figure of merit for detecting distortion of the smoothed spectra, based on the linear model. It is assumed that as long as the part of the raw spectrum removed by the smoothing procedure (v s ) will be of random nature, the smoothed spectrum can be considered as undistorted. Thanks to this feature of the autocorrelation function, drifts of the mean value in the removed noise vs as well as its periodicity can be more easily detected from the autocorrelogram than from the original data

  3. Multivariate Process Control with Autocorrelated Data

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2011-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control and monitoring. This new high dimensional data...... often exhibit not only cross-­‐correlation among the quality characteristics of interest but also serial dependence as a consequence of high sampling frequency and system dynamics. In practice, the most common method of monitoring multivariate data is through what is called the Hotelling’s T2 statistic....... In this paper, we discuss the effect of autocorrelation (when it is ignored) on multivariate control charts based on these methods and provide some practical suggestions and remedies to overcome this problem....

  4. Response predictions using the observed autocorrelation function

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

    2018-01-01

    This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

  5. 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...

  6. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2000-01-01

    There are certain shortcomings for the endpoint detection by time-waveform envelope and/or by checking the travel table (both labelled as the artificial detection method). Based on the analysis of the auto-correlation function, the notion of the distance between auto-correlation functions was quoted, and the characterizations of the noise and the signal with noise were discussed by using the distance. Then, the method of auto-adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low SNR circumstance

  7. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  8. The Spatial Econometric Analysis of China’s Banking Competition and Its Influential Factors

    Directory of Open Access Journals (Sweden)

    Ying Li

    2015-12-01

    Full Text Available This paper determines alternative indexes to measure banking competition from the perspective of industrial economics. Spatial correlation of competition in China’s banking environment is studied from the perspective of spatial economics. A spatial panel data model is built to make an empirical study of factors influencing banking competition. The results show that the global autocorrelation test index Moran’s I indicates that China’s banking competition has obvious spatial correlation characteristics and significant spatial clustering. The space LISA map indicates that banking competition in most provinces has the characteristics of spatial dependence, and only a few provinces have the characteristics of spatial heterogeneity. Human capital, economic growth, financial scale of development, and foreign direct investment all have a significant positive effect on improving the degree of banking competition. Government intervention has a significant negative impact on the degree of banking competition, while fixed asset investment has no significant impact on it.

  9. Avaliação e aplicação de testes para a detecção da autocorrelação espacial usando marcadores genéticos Evaluation and application of tests for the detection of spatial autocorrelation using data genetics marks

    Directory of Open Access Journals (Sweden)

    João Marcos Louzada

    2006-04-01

    Full Text Available O índice I de Moran é a ferramenta usual para se medir a intensidade da autocorrelação espacial em dados de marcadores genéticos. A estatística I é assintoticamente normalmente distribuída, podendo ser avaliada como desvios da normal padrão mediante o suposto-N (aproximação normal. Porém, para pequenos números de populações (m25}, deve-se aplicar o teste de Mantel em qualquer das situações simuladas.Moran's I index is the usual tool to measure the intensity of the spatial autocorrelation in genetic markers data. I statistics is asymptotically normally distributed and it may be evaluated as standard normal deviations (assumption-N, normality. However, for small numbers of populations (m<8, the Mantel' s randomness test (assumption-R developed by Mantel (1967 should be applied. Thus, this study was done to evaluate the performance of both tests accordding to type I error rate sand their power. They were evaluated via Monte Carlo simulation, in which, the situations of average allelic frequencies, {p=0,1, p=0,25 and p=0,5} were analyzed under H0. Number for populations varying from {m= 5, 10, 25 and 50}were taken into account and for each population, the number of individuals in {n=1, 2, 5, 10 and 30} was varied as well. As regards to the alternative hypothesis (with spatial pattern, in addition to these same situations simulated in H0, the behavior of these criteria of tests was evaluated according to the variation of the amplitude in the average local allelic frequency in {A=0,1; 0,2; 0,5; 0,8 e 1,0}. Therefore, the performance of the test studied could be analyzed as the degree of variability of the average frequencies generated on a linear surface, related to the geographic space and by means of it's different slopes. The normal approximation was considered better withpopulations as combined with the weighing systems inverse of the distance and inverse of the distance squared in both levels of significance 1% and 5%. The same

  10. 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.

  11. Inference for local autocorrelations in locally stationary models.

    Science.gov (United States)

    Zhao, Zhibiao

    2015-04-01

    For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides an important generalization of the R function acf() to locally stationary Gaussian processes. Simulation studies and two empirical applications are developed. For the global temperature series, we find that the local autocorrelations are time-varying and have a "V" shape during 1910-1960. For the S&P 500 index, we conclude that the returns satisfy the efficient-market hypothesis whereas the magnitudes of returns show significant local autocorrelations.

  12. 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....

  13. An improved triple collocation algorithm for decomposing autocorrelated and white soil moisture retrieval errors

    Science.gov (United States)

    If not properly account for, auto-correlated errors in observations can lead to inaccurate results in soil moisture data analysis and reanalysis. Here, we propose a more generalized form of the triple collocation algorithm (GTC) capable of decomposing the total error variance of remotely-sensed surf...

  14. A model-free approach to eliminate autocorrelation when testing for process capability

    DEFF Research Database (Denmark)

    Vanmann, Kerstin; Kulahci, Murat

    2008-01-01

    There is an increasing use of on-line data acquisition systems in industry. This usually leads to autocorrelated data and implies that the assumption of independent observations has to be re-examined. Most decision procedures for capability analysis assume independent data. In this article we pre...

  15. 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...

  16. 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

  17. 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...

  18. Adaptive non-collinear autocorrelation of few-cycle pulses with an angular tunable bi-mirror

    Energy Technology Data Exchange (ETDEWEB)

    Treffer, A., E-mail: treffer@mbi-berlin.de; Bock, M.; König, S.; Grunwald, R. [Max Born Institute for Nonlinear Optics and Short-Pulse Spectroscopy, Max Born Strasse 2A, D-12489 Berlin (Germany); Brunne, J.; Wallrabe, U. [Laboratory for Microactuators, Department of Microsystems Engineering, IMTEK, University of Freiburg, Georges-Koehler-Allee 102, Freiburg 79110 (Germany)

    2016-02-01

    Adaptive autocorrelation with an angular tunable micro-electro-mechanical system is reported. A piezo-actuated Fresnel bi-mirror structure was applied to measure the second order autocorrelation of near-infrared few-cycle laser pulses in a non-collinear setup at tunable superposition angles. Because of enabling measurements with variable scaling and minimizing the influence of distortions by adaptive self-reconstruction, the approach extends the capability of autocorrelators. Flexible scaling and robustness against localized amplitude obscurations are demonstrated. The adaptive reconstruction of temporal frequency information by the Fourier analysis of autocorrelation data is shown. Experimental results and numerical simulations of the beam propagation and interference are compared for variable angles.

  19. 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.

  20. 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.

  1. Autocorrelation and cross-correlation in time series of homicide and attempted homicide

    Science.gov (United States)

    Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

    2014-04-01

    We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

  2. Autocorrelation in queuing network type production systems - revisited

    DEFF Research Database (Denmark)

    Nielsen, Erland Hejn

    -production systems (Takahashi and Nakamura, 1998) establishes that autocorrelation plays definitely a non-negligible role in relation to the dimensioning as well as functioning of Kanban-controlled production flow lines . This must logically either imply that production managers are missing an important aspect...... in their production planning reasoning, or that the 'realistic' autocorrelation patterns , inherent in actual production setups , are not like those so far considered in the literature. In this paper, an attempt to characterise relevant and 'realistic' types of autocorrelation schemes as well as their levels...

  3. A Statistical Toolbox For Mining And Modeling Spatial Data

    Directory of Open Access Journals (Sweden)

    D’Aubigny Gérard

    2016-12-01

    Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.

  4. [Spatial analysis of syphilis and gonorrhea infections in a Public Health Service in Madrid].

    Science.gov (United States)

    Wijers, Irene G M; Sánchez Gómez, Amaya; Taveira Jiménez, Jose Antonio

    2017-06-21

    Sexually transmitted diseases are a significant public health problem. Within the Madrid Autonomous Region, the districts with the highest syphilis and gonorrhea incidences are part of the same Public Health Service (Servicio de Salud Pública del Área 7, SSPA 7). The objective of this study was to identify, by spatial analysis, clusters of syphilis and gonorrhea infections in this SSPA in Madrid. All confirmed syphilis and gonorrhea cases registered in SSPA 7 in Madrid were selected. Moran's I was calculated in order to identify the existence of spatial autocorrelation and a cluster analysis was performed. Clusters and cumulative incidences (CI) per health zone were mapped. The district with most cases was Centro (CI: 67.5 and 160.7 per 100.000 inhabitants for syphilis and gonorrhea, respectively) with the highest CI (120.0 and 322.6 per 100.000 inhabitants) in the Justicia health zone.91.6% of all syphilis cases and 89.6% of gonorrhea cases were among men who have sex with men (MSM). Moran's I was 0.54 and 0.55 (p=0.001) for syphilis and gonorrhea, respectively. For syphilis, a cluster was identified including the six health zones of the Centro district, with a relative risk (RR)of 6.66 (p=0.001). For gonorrhea, a cluster was found including the Centro district, three health zones of the Chamberí district and one of Latina (RR 5.05; p=0.001). Centro was the district with most cases of syphilis and gonorrhea and the most affected population were MSM. For both infections, clusters were found with an important overlap. By identifying the most vulnerable health zones and populations, these results can help to design public health measures for preventing sexually transmitted diseases.

  5. 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

  6. Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey.

    Science.gov (United States)

    Erdogan, Saffet

    2009-10-01

    The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey. Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of Paccidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as Paccidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R(2) values. Geographically weighted regression provided values of 0.89-0.99 adjusted R(2) for death and accident rates, compared with 0

  7. 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

  8. Crude oil market efficiency and modeling. Insights from the multiscaling autocorrelation pattern

    International Nuclear Information System (INIS)

    Alvarez-Ramirez, Jose; Alvarez, Jesus; Solis, Ricardo

    2010-01-01

    Empirical research on market inefficiencies focuses on the detection of autocorrelations in price time series. In the case of crude oil markets, statistical support is claimed for weak efficiency over a wide range of time-scales. However, the results are still controversial since theoretical arguments point to deviations from efficiency as prices tend to revert towards an equilibrium path. This paper studies the efficiency of crude oil markets by using lagged detrended fluctuation analysis (DFA) to detect delay effects in price autocorrelations quantified in terms of a multiscaling Hurst exponent (i.e., autocorrelations are dependent of the time scale). Results based on spot price data for the period 1986-2009 indicate important deviations from efficiency associated to lagged autocorrelations, so imposing the random walk for crude oil prices has pronounced costs for forecasting. Evidences in favor of price reversion to a continuously evolving mean underscores the importance of adequately incorporating delay effects and multiscaling behavior in the modeling of crude oil price dynamics. (author)

  9. Crude oil market efficiency and modeling. Insights from the multiscaling autocorrelation pattern

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Departamento de Economia, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Alvarez, Jesus [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Solis, Ricardo [Departamento de Economia, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico)

    2010-09-15

    Empirical research on market inefficiencies focuses on the detection of autocorrelations in price time series. In the case of crude oil markets, statistical support is claimed for weak efficiency over a wide range of time-scales. However, the results are still controversial since theoretical arguments point to deviations from efficiency as prices tend to revert towards an equilibrium path. This paper studies the efficiency of crude oil markets by using lagged detrended fluctuation analysis (DFA) to detect delay effects in price autocorrelations quantified in terms of a multiscaling Hurst exponent (i.e., autocorrelations are dependent of the time scale). Results based on spot price data for the period 1986-2009 indicate important deviations from efficiency associated to lagged autocorrelations, so imposing the random walk for crude oil prices has pronounced costs for forecasting. Evidences in favor of price reversion to a continuously evolving mean underscores the importance of adequately incorporating delay effects and multiscaling behavior in the modeling of crude oil price dynamics. (author)

  10. Thirty-two phase sequences design with good autocorrelation ...

    Indian Academy of Sciences (India)

    mum peak aperiodic autocorrelation sidelobe level one are called Barker Sequences. ... the generation and processing of polyphase signals have now become easy ..... Cook C E, Bernfield M 1967 An introduction to theory and application.

  11. 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 ...

  12. Generalised recurrence plot analysis for spatial data

    International Nuclear Information System (INIS)

    Marwan, Norbert; Kurths, Juergen; Saparin, Peter

    2007-01-01

    Recurrence plot based methods are highly efficient and widely accepted tools for the investigation of time series or one-dimensional data. We present an extension of the recurrence plots and their quantifications in order to study recurrent structures in higher-dimensional spatial data. The capability of this extension is illustrated on prototypical 2D models. Next, the tested and proved approach is applied to assess the bone structure from CT images of human proximal tibia. We find that the spatial structures in trabecular bone become more recurrent during the bone loss in osteoporosis

  13. Velocity and stress autocorrelation decay in isothermal dissipative particle dynamics

    Science.gov (United States)

    Chaudhri, Anuj; Lukes, Jennifer R.

    2010-02-01

    The velocity and stress autocorrelation decay in a dissipative particle dynamics ideal fluid model is analyzed in this paper. The autocorrelation functions are calculated at three different friction parameters and three different time steps using the well-known Groot/Warren algorithm and newer algorithms including self-consistent leap-frog, self-consistent velocity Verlet and Shardlow first and second order integrators. At low friction values, the velocity autocorrelation function decays exponentially at short times, shows slower-than exponential decay at intermediate times, and approaches zero at long times for all five integrators. As friction value increases, the deviation from exponential behavior occurs earlier and is more pronounced. At small time steps, all the integrators give identical decay profiles. As time step increases, there are qualitative and quantitative differences between the integrators. The stress correlation behavior is markedly different for the algorithms. The self-consistent velocity Verlet and the Shardlow algorithms show very similar stress autocorrelation decay with change in friction parameter, whereas the Groot/Warren and leap-frog schemes show variations at higher friction factors. Diffusion coefficients and shear viscosities are calculated using Green-Kubo integration of the velocity and stress autocorrelation functions. The diffusion coefficients match well-known theoretical results at low friction limits. Although the stress autocorrelation function is different for each integrator, fluctuates rapidly, and gives poor statistics for most of the cases, the calculated shear viscosities still fall within range of theoretical predictions and nonequilibrium studies.

  14. 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.

  15. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette); V. Capasso

    2009-01-01

    htmlabstractWe give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects

  16. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    Lieshout, van M.N.M.; Capasso, V.

    2009-01-01

    We give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects through a video

  17. Second order analysis for spatial Hawkes processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Torrisi, Giovanni Luca

    We derive summary statistics for stationary Hawkes processes which can be considered as spatial versions of classical Hawkes processes. Particularly, we derive the intensity, the pair correlation function and the Bartlett spectrum. Our results for Gaussian fertility rates and the extension...... to marked Hawkes processes are discussed....

  18. [Inequities in health: socio-demographic and spatial analysis of breast cancer in women from Córdoba, Argentina].

    Science.gov (United States)

    Tumas, Natalia; Pou, Sonia Alejandra; Díaz, María Del Pilar

    To identify sociodemographic determinants associated with the spatial distribution of the breast cancer incidence in the province of Córdoba, Argentina, in order to reveal underlying social inequities. An ecological study was developed in Córdoba (26 counties as geographical units of analysis). The spatial autocorrelation of the crude and standardised incidence rates of breast cancer, and the sociodemographic indicators of urbanization, fertility and population ageing were estimated using Moran's index. These variables were entered into a Geographic Information System for mapping. Poisson multilevel regression models were adjusted, establishing the breast cancer incidence rates as the response variable, and by selecting sociodemographic indicators as covariables and the percentage of households with unmet basic needs as adjustment variables. In Córdoba, Argentina, a non-random pattern in the spatial distribution of breast cancer incidence rates and in certain sociodemographic indicators was found. The mean increase in annual urban population was inversely associated with breast cancer, whereas the proportion of households with unmet basic needs was directly associated with this cancer. Our results define social inequity scenarios that partially explain the geographical differentials in the breast cancer burden in Córdoba, Argentina. Women residing in socioeconomically disadvantaged households and in less urbanized areas merit special attention in future studies and in breast cancer public health activities. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India

    Directory of Open Access Journals (Sweden)

    Arun Kumar Taxak

    2014-08-01

    Full Text Available Gridded rainfall data of 0.5×0.5° resolution (CRU TS 3.21 was analysed to study long term spatial and temporal trends on annual and seasonal scales in Wainganga river basin located in Central India during 1901–2012. After testing the presence of autocorrelation, Mann–Kendall (Modified Mann–Kendall test was applied to non-auto correlated (auto correlated series to detect the trends in rainfall data. Theil and Sen׳s slope estimator test was used for finding the magnitude of change over a time period. For detecting the most probable change year, Pettitt–Mann–Whitney test was applied. The Rainfall series was then divided into two partial duration series for finding changes in trends before and after the change year. Arc GIS was used to explore spatial patterns of the trends over the entire basin. Though most of the grid points shows a decreasing trend in annual rainfall, only seven grids has a significant decreasing trend during 1901–2012. On the basis of seasonal trend analysis, non-significant increasing trend is observed only in post monsoon season while seven grid points show significant decreasing trend in monsoon rainfall and non-significant in pre-monsoon and winter rainfall over the last 112 years. During the study period, overall a 8.45% decrease in annual rainfall is estimated. The most probable year of change was found to be 1948 in annual and monsoonal rainfall. There is an increasing rainfall trend in the basin during the period 1901–1948, which is reversed during the period 1949–2012 resulting in decreasing rainfall trend in the basin. Homogeneous trends in annual and seasonal rainfall over a grid points is exhibited in the basin by van Belle and Hughes׳ homogeneity trend test.

  20. The Czech Pirate Party in the 2010 and 2013 Parliamentary Elections and the 2014 European Parliament Elections: Spatial Analysis of Voter Support

    Directory of Open Access Journals (Sweden)

    Maškarinec Pavel

    2017-01-01

    Full Text Available The paper presents a spatial analysis of the Czech Pirate Party (Pirates voter support in the 2010 and 2013 parliamentary elections and the 2014 European Parliament elections. The main method applied for classifying electoral results was the spatial autocorrelation and spatial regression. The result of the analysis has shown that territorial support for the Pirates copies to a great extent the areas of high support for right-wing parties and simultaneously the areas exemplified by a high development potential. In the case of spatial characteristics, little support for the Pirates was shown in Moravia and higher in the Sudetenland in terms of determinants of support. Additionally to spatial regimes, inter-regional support for the Pirates was also influenced by other non-spatial characteristics, although the strength of their influence was relatively weak. The units which embodied a successful environment for voting for the Pirates were particularly characterized by greater urbanization and a greater number of entrepreneurs, while a lack of jobs and the older age structure, i.e. the signs that in the socio-economic, or socio-ecological sense define peripheral areas, negatively impacted the gains of the Pirates. Ambiguous influence was exercised by college-educated inhabitants, who in the parliamentary elections in 2010 and 2013 decreased the gains of the Pirates, however, in the elections to the European Parliament in 2014 a direction of relationship was modified and turned positive.

  1. Spatial analysis of various multiplex cinema types

    Directory of Open Access Journals (Sweden)

    Young-Seo Park

    2016-03-01

    Full Text Available This study identifies the spatial characteristics and relationships of each used space according to the multiplex type. In this study, multiplexes are classified according to screen rooms and circulation systems, and each used space is quantitatively analyzed. The multiplex type based on screen rooms and moving line systems influences the relationship and characteristics of each used space in various ways. In particular, the structure of the used space of multiplexes has a significant effect on profit generation and audience convenience.

  2. Examining the Association of Economic Development with Intercity Multimodal Transport Demand in China: A Focus on Spatial Autoregressive Analysis

    Directory of Open Access Journals (Sweden)

    Jinbao Zhao

    2018-02-01

    Full Text Available Transportation is generally perceived as a catalyst for economic development. This has been highlighted in previous studies. However, less attention has been paid to examine the relationship between economy and transport demand by exploring spatially cross-sectional data, especially for countries with significant regional economic imbalance, like China. In this article, we assess the economic influence of intercity multimodal transport demand at the prefecture level in China. Spatial autoregressive regression models are used to examine the impact of transport demand on economy by deep analysis of transport modes (land, air, and water and regions (eastern, central, and western. Through contrasting results from spatial lag model and spatial error model with those from the ordinary least square, this study finds that the estimation results can become more accurate by controlling for spatial autocorrelation, especially at the national level. Through rigorous analysis it is identified that except for water passenger traffic, all other intercity transport demand significantly contribute to a city’s economic development level in gross domestic product. In particular, air transport demands distribute more evenly and are estimated with the highest beta coefficients at both national and regional levels. In addition, the beta coefficients for land, air and water transportation are estimated with different magnitudes and significances at the national and regional levels. This study contributes to the ongoing discussion on the relationship between intercity multimodal transport demand and economic development level. Findings from this paper provide planning makers with valid and efficient strategies to better develop the economy by leveraging the special “⊣” cluster pattern of economic development and the benefits of air transportation.

  3. 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.

  4. [Analysis of Spatial Clustering of HIV infected in men who have sex with men in Chongqing of 2004-2015].

    Science.gov (United States)

    Hao, Y X; Qin, Q Q; Wu, G H; Zhang, W; Guo, W; Cui, Y; Liu, H; Hu, Y Y; Sun, J P

    2017-05-06

    Objective: To analyze the spatial clustering characteristics of HIV/AIDS among men who have sex with men (MSM) in Chongqing from January 2004 to December 2015 and understand the HIV/AIDS related behaviors among MSM by interview. Methods: Data related to MSM who were infected with HIV and whose present address were in Chongqing, were collected from Information System on the HIV/AIDS Prevention and Control. Information included the age when the information was inputted, address, occupation, education level, and marital status. The total number of MSM who were infected with HIV and reported was 6 604 in Chongqing. Those with unknown address were ruled out. The spatial autocorrelation analysis and the local spatial autocorrelation analysis were carried out by using ArcGIS 10.3. In addition, in November 2015 and May 2016, using a convenience sampling, we conducted one-on-one interviews among 23 MSM in the Chongqing Center for Disease Control and prevention. Receiving voluntary counseling and testing in the urban area of Chongqing and willing to participate in the interview by oral informed consent; male and self-described as MSM. The content of the interview included basic information, sexual orientation, sexual role, the main place of making friends, the main place of sexual behavior, a long-term experience in other provinces and drug abuse. Results: The HIV/AIDS reported number in Chongqing from 2004 to 2015 showed an uptrend, except in 2010. The age distribution of 6 604 cases of HIV positive patients was mainly concentrated in the 15-34 years old, about 68.5% (4 522 cases). There was a positive spatial autocorrelation in MSM, except 2005 (Moran's I =- 0.046, P = 0.823), form 2004 to 2015, Global Moran's I values were 0.308, 0.254, 0.335, 0.683, 0.673, 0.558, 0.620, 0.673, 0.685, 0.654 and 0.649, respectively; all P values were internet (17 participants). Most of the participants (11 participants) were making friends in the bar. The majority of respondents would ask

  5. 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.

  6. 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 ...

  7. 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.

  8. 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...

  9. 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.

  10. Binary codes with impulse autocorrelation functions for dynamic experiments

    International Nuclear Information System (INIS)

    Corran, E.R.; Cummins, J.D.

    1962-09-01

    A series of binary codes exist which have autocorrelation functions approximating to an impulse function. Signals whose behaviour in time can be expressed by such codes have spectra which are 'whiter' over a limited bandwidth and for a finite time than signals from a white noise generator. These codes are used to determine system dynamic responses using the correlation technique. Programmes have been written to compute codes of arbitrary length and to compute 'cyclic' autocorrelation and cross-correlation functions. Complete listings of these programmes are given, and a code of 1019 bits is presented. (author)

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Estimating the Autocorrelated Error Model with Trended Data: Further Results,

    Science.gov (United States)

    1979-11-01

    Perhaps the most serious deficiency of OLS in the presence of autocorrelation is not inefficiency but bias in its estimated standard errors--a bias...k for all t has variance var(b) = o2/ Tk2 2This refutes Maeshiro’s (1976) conjecture that "an estimator utilizing relevant extraneous information

  16. Waveguide superconducting single-photon autocorrelators for quantum photonic applications

    NARCIS (Netherlands)

    Sahin, D.; Gaggero, A.; Frucci, G.; Jahanmirinejad, S.; Sprengers, J.P.; Mattioli, F.; Leoni, R.; Beetz, J.; Lermer, M.; Kamp, M.; Höfling, S.; Fiore, A.; Hasan, Z.U.; Hemmer, P.R.; Lee, H.; Santori, C.M.

    2013-01-01

    We report a novel component for integrated quantum photonic applications, a waveguide single-photon autocorrelator. It is based on two superconducting nanowire detectors patterned onto the same GaAs ridge waveguide. Combining the electrical output of the two detectors in a correlation card enables

  17. Performances Of Estimators Of Linear Models With Autocorrelated ...

    African Journals Online (AJOL)

    The performances of five estimators of linear models with Autocorrelated error terms are compared when the independent variable is autoregressive. The results reveal that the properties of the estimators when the sample size is finite is quite similar to the properties of the estimators when the sample size is infinite although ...

  18. Performances of estimators of linear auto-correlated error model ...

    African Journals Online (AJOL)

    The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...

  19. Mathematical Analysis of Urban Spatial Networks

    CERN Document Server

    Blanchard, Philippe

    2009-01-01

    Cities can be considered to be among the largest and most complex artificial networks created by human beings. Due to the numerous and diverse human-driven activities, urban network topology and dynamics can differ quite substantially from that of natural networks and so call for an alternative method of analysis. The intent of the present monograph is to lay down the theoretical foundations for studying the topology of compact urban patterns, using methods from spectral graph theory and statistical physics. These methods are demonstrated as tools to investigate the structure of a number of real cities with widely differing properties: medieval German cities, the webs of city canals in Amsterdam and Venice, and a modern urban structure such as found in Manhattan. Last but not least, the book concludes by providing a brief overview of possible applications that will eventually lead to a useful body of knowledge for architects, urban planners and civil engineers.

  20. Autocorrelations in hybrid Monte Carlo simulations

    International Nuclear Information System (INIS)

    Schaefer, Stefan; Virotta, Francesco

    2010-11-01

    Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)

  1. 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.

  2. Multiscale analysis of the spatial variability of heavy metals and organic matter in soils and groundwater across Spain

    Science.gov (United States)

    Luque-Espinar, J. A.; Pardo-Igúzquiza, E.; Grima-Olmedo, J.; Grima-Olmedo, C.

    2018-06-01

    During the last years there has been an increasing interest in assessing health risks caused by exposure to contaminants found in soil, air, and water, like heavy metals or emerging contaminants. This work presents a study on the spatial patterns and interaction effects among relevant heavy metals (Sb, As and Pb) that may occur together in different minerals. Total organic carbon (TOC) have been analyzed too because it is an essential component in the regulatory mechanisms that control the amount of metal in soils. Even more, exposure to these elements is associated with a number of diseases and environmental problems. These metals can have both natural and anthropogenic origins. A key component of any exposure study is a reliable model of the spatial distribution the elements studied. A geostatistical analysis have been performed in order to show that selected metals are auto-correlated and cross-correlated and type and magnitude of such cross-correlation varies depending on the spatial scale under consideration. After identifying general trends, we analyzed the residues left after subtracting the trend from the raw variables. Three scales of variability were identified (compounds or factors) with scales of 5, 35 and 135 km. The first factor (F1) basically identifies anomalies of natural origin but, in some places, of anthropogenics origin as well. The other two are related to geology (F2 and F3) although F3 represents more clearly geochemical background related to large lithological groups. Likewise, mapping of two major structures indicates that significant faults have influence on the distribution of the studied elements. Finally, influence of soil and lithology on groundwater by means of contingency analysis was assessed.

  3. Evaluating the coefficients of autocorrelation in a series of annual run-off of the Far East rivers

    Energy Technology Data Exchange (ETDEWEB)

    Sakharyuk, A V

    1981-01-01

    An evaluation is made of the coefficients of autocorrelation in series of annual river run-off based on group analysis using data on the distribution law of sampling correlation coefficients of temporal series subordinate to the III type Pearson's distribution.

  4. Spatial and spatiotemporal pattern analysis of coconut lethal yellowing in Mozambique.

    Science.gov (United States)

    Bonnot, F; de Franqueville, H; Lourenço, E

    2010-04-01

    Coconut lethal yellowing (LY) is caused by a phytoplasma and is a major threat for coconut production throughout its growing area. Incidence of LY was monitored visually on every coconut tree in six fields in Mozambique for 34 months. Disease progress curves were plotted and average monthly disease incidence was estimated. Spatial patterns of disease incidence were analyzed at six assessment times. Aggregation was tested by the coefficient of spatial autocorrelation of the beta-binomial distribution of diseased trees in quadrats. The binary power law was used as an assessment of overdispersion across the six fields. Spatial autocorrelation between symptomatic trees was measured by the BB join count statistic based on the number of pairs of diseased trees separated by a specific distance and orientation, and tested using permutation methods. Aggregation of symptomatic trees was detected in every field in both cumulative and new cases. Spatiotemporal patterns were analyzed with two methods. The proximity of symptomatic trees at two assessment times was investigated using the spatiotemporal BB join count statistic based on the number of pairs of trees separated by a specific distance and orientation and exhibiting the first symptoms of LY at the two times. The semivariogram of times of appearance of LY was calculated to characterize how the lag between times of appearance of LY was related to the distance between symptomatic trees. Both statistics were tested using permutation methods. A tendency for new cases to appear in the proximity of previously diseased trees and a spatially structured pattern of times of appearance of LY within clusters of diseased trees were detected, suggesting secondary spread of the disease.

  5. [Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain].

    Science.gov (United States)

    Gómez-Barroso, Diana; Prieto-Flores, María-Eugenia; Mellado San Gabino, Ana; Moreno Jiménez, Antonio

    2015-01-01

    Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations. An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped. SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p AUP. The LISA method showed similar patterns to those previously observed.

  6. 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.

  7. 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…

  8. 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…

  9. 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

  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. 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 ...

  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. 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…

  14. 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 ...

  15. Correction of Spatial Bias in Oligonucleotide Array Data

    Directory of Open Access Journals (Sweden)

    Philippe Serhal

    2013-01-01

    Full Text Available Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs for each intended target, on average, correlate with their target’s true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users’ current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays. A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias.

  16. Correction of Spatial Bias in Oligonucleotide Array Data

    Science.gov (United States)

    Lemieux, Sébastien

    2013-01-01

    Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083

  17. Momentum autocorrelation function of a classic diatomic chain

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Ming B., E-mail: mingbyu@gmail.com

    2016-10-23

    A classical harmonic diatomic chain is studied using the recurrence relations method. The momentum autocorrelation function results from contributions of acoustic and optical branches. By use of convolution theorem, analytical expressions for the acoustic and optical contributions are derived as even-order Bessel function expansions with coefficients given in terms of integrals of elliptic functions in real axis and a contour parallel to the imaginary axis, respectively. - Highlights: • Momentum autocorrelation function of a classic diatomic chain is studied. • It is derived as even-order Bessel function expansion using the convolution theorem. • The expansion coefficients are integrals of elliptic functions. • Addition theorem is used to reduce complex elliptic function to complex sum of real ones.

  18. Biometric feature extraction using local fractal auto-correlation

    International Nuclear Information System (INIS)

    Chen Xi; Zhang Jia-Shu

    2014-01-01

    Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. Climatic factors associated with amyotrophic lateral sclerosis: a spatial analysis from Taiwan.

    Science.gov (United States)

    Tsai, Ching-Piao; Tzu-Chi Lee, Charles

    2013-11-01

    Few studies have assessed the spatial association of amyotrophic lateral sclerosis (ALS) incidence in the world. The aim of this study was to identify the association of climatic factors and ALS incidence in Taiwan. A total of 1,434 subjects with the primary diagnosis of ALS between years 1997 and 2008 were identified in the national health insurance research database. The diagnosis was also verified by the national health insurance programme, which had issued and providing them with "serious disabling disease (SDD) certificates". Local indicators of spatial association were employed to investigate spatial clustering of age-standardised incidence ratios in the townships of the study area. Spatial regression was utilised to reveal any association of annual average climatic factors and ALS incidence for the 12-year study period. The climatic factors included the annual average time of sunlight exposure, average temperature, maximum temperature, minimum temperature, atmospheric pressure, rainfall, relative humidity and wind speed with spatial autocorrelation controlled. Significant correlations were only found for exposure to sunlight and rainfall and it was similar in both genders. The annual average of the former was found to be negatively correlated with ALS, while the latter was positively correlated with ALS incidence. While accepting that ALS is most probably multifactorial, it was concluded that sunlight deprivation and/or rainfall are associated to some degree with ALS incidence in Taiwan.

  4. Analysis of Spatial Pattern among Grasshopper and Vegetation in Heihe based on GIS

    Science.gov (United States)

    Zhou, Wei; Wang, KeMing; Zhao, Chengzhang; Zhang, Qi-peng

    Geostatistics was used to analyze the grasshopper and dominant plants population spatial pattern and their relationship in the upper reaches of Heihe River under GIS platform. The results showed that the plants and grasshoppers populations have strong spatial correlation in study area. The Semivariogram curve of Chorthippus brunneus huabeiensis, Filchnerella, Aneurolepidium dasystanchys and Artemisia dalailamae is spherical model, Gomphocerus licenti and Stipa krylovii's Semivariogram curve is exponential and Gaussian model respectively, and their spatial autocorrelation scope is 10.8, 11.3, 11.5, 12.4, 23.5 and 59.7 meters respectively. Stipa krylovii and Artemisia dalailamae spatial distribution was patchy, Aneurolepidium dasystanchys showed flaky distribution; Gomphocerus licenti and Chorthippus brunneus huabeiensis mainly located in southeast areas with high coverage of Stipa krylovii and Aneurolepidium dasystanchys. Filchnerella nearly located in North areas with high coverage of Artemisia dalailamae, but were rarely found in south and east areas. The effects of different plants coverage on grasshopper abundance are significantly different. Filchnerella abundance and Artemisia dalailamae coverage showed significantly positive correlation, Chorthippus brunneus huabeiensis and Gomphocerus licenti positively correlated with Aneurolepidium dasystanchys and Stipa krylovii. Grasshopper spatial patterns and occurrence numbers are both influenced by grasshopper biological characteristics and plant community composition, which reflected complex coupled relation between grasshopper and plant.

  5. 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)

  6. 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.

  7. [Ecological risk assessment of land use based on exploratory spatial data analysis (ESDA): a case study of Haitan Island, Fujian Province].

    Science.gov (United States)

    Wu, Jian; Chen, Peng; Wen, Chao-Xiang; Fu, Shi-Feng; Chen, Qing-Hui

    2014-07-01

    As a novel environment management tool, ecological risk assessment has provided a new perspective for the quantitative evaluation of ecological effects of land-use change. In this study, Haitan Island in Fujian Province was taken as a case. Based on the Landsat TM obtained in 1990, SPOT5 RS images obtained in 2010, general layout planning map of Pingtan Comprehensive Experimental Zone in 2030, as well as the field investigation data, we established an ecological risk index to measure ecological endpoints. By using spatial autocorrelation and semivariance analysis of Exploratory Spatial Data Analysis (ESDA), the ecological risk of Haitan Island under different land-use situations was assessed, including the past (1990), present (2010) and future (2030), and the potential risk and its changing trend were analyzed. The results revealed that the ecological risk index showed obvious scale effect, with strong positive correlation within 3000 meters. High-high (HH) and low-low (LL) aggregations were predominant types in spatial distribution of ecological risk index. The ecological risk index showed significant isotropic characteristics, and its spatial distribution was consistent with Anselin Local Moran I (LISA) distribution during the same period. Dramatic spatial distribution change of each ecological risk area was found among 1990, 2010 and 2030, and the fluctuation trend and amplitude of different ecological risk areas were diverse. The low ecological risk area showed a rise-to-fall trend while the medium and high ecological risk areas showed a fall-to-rise trend. In the planning period, due to intensive anthropogenic disturbance, the high ecological risk area spread throughout the whole region. To reduce the ecological risk in land-use and maintain the regional ecological security, the following ecological risk control strategies could be adopted, i.e., optimizing the spatial pattern of land resources, protecting the key ecoregions and controlling the scale of

  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. Microfluidic volumetric flow determination using optical coherence tomography speckle: An autocorrelation approach

    Energy Technology Data Exchange (ETDEWEB)

    De Pretto, Lucas R., E-mail: lucas.de.pretto@usp.br; Nogueira, Gesse E. C.; Freitas, Anderson Z. [Instituto de Pesquisas Energéticas e Nucleares, IPEN–CNEN/SP, Avenida Lineu Prestes, 2242, 05508-000 São Paulo (Brazil)

    2016-04-28

    Functional modalities of Optical Coherence Tomography (OCT) based on speckle analysis are emerging in the literature. We propose a simple approach to the autocorrelation of OCT signal to enable volumetric flow rate differentiation, based on decorrelation time. Our results show that this technique could distinguish flows separated by 3 μl/min, limited by the acquisition speed of the system. We further perform a B-scan of gradient flow inside a microchannel, enabling the visualization of the drag effect on the walls.

  10. 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...

  11. 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...

  12. 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.

  13. 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

  14. Spatial-Temporal Analysis of Air Pollution, Climate Change, and Total Mortality in 120 Cities of China, 2012-2013.

    Science.gov (United States)

    Liu, Longjian; Yang, Xuan; Liu, Hui; Wang, Mingquan; Welles, Seth; Márquez, Shannon; Frank, Arthur; Haas, Charles N

    2016-01-01

    China has had a rapid increase in its economy over the past three decades. However, the economic boom came at a certain cost of depleting air quality. In the study, we aimed to examine the burden of air pollution and its association with climatic factors and health outcomes using data from Chinese national and city-level air quality and public health surveillance systems. City-level daily air pollution index (API, a sum weighted index of SO2, NO2, PM10, CO, and Ozone) in 120 cities in 2012 and 2013, and its association with climate factors were analyzed using multiple linear regression analysis, spatial autocorrelation analysis, and panel fixed models. City-level ecological association between annual average API and total mortality were examined using univariate and partial correlation analysis. Sensitivity analysis was conducted by taking the consideration of time-lag effect between exposures and outcomes. The results show that among the 120 cities, annual average API significantly increased from 2012 to 2013 (65.05 vs. 75.99, p 100 (defined as "slightly polluted"), however, it increased to 21 cities (18%) that experienced API >100 for ≥60 days in 2013. Furthermore, 16 cities (13%) in 2012 and 35 (29%) in 2013 experienced a maximum API >300 (defined as "severely polluted"). API was negatively and significantly correlated with heat index, precipitation, and sunshine hours, but positively with air pressure. Cities with higher API concentrations had significantly higher total mortality rates than those with lower API. About a 4-7% of the variation in total mortality could be explained by the difference in API across the nation. In conclusion, the study highlights an increased trend of air pollution from 2012 to 2013 in China. The magnitude of air pollution varied by seasons and regions and correlated with climatic factors and total mortality across the country.

  15. 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

  16. 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.

  17. 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.

  18. Distributions of Autocorrelated First-Order Kinetic Outcomes: Illness Severity.

    Directory of Open Access Journals (Sweden)

    James D Englehardt

    Full Text Available Many complex systems produce outcomes having recurring, power law-like distributions over wide ranges. However, the form necessarily breaks down at extremes, whereas the Weibull distribution has been demonstrated over the full observed range. Here the Weibull distribution is derived as the asymptotic distribution of generalized first-order kinetic processes, with convergence driven by autocorrelation, and entropy maximization subject to finite positive mean, of the incremental compounding rates. Process increments represent multiplicative causes. In particular, illness severities are modeled as such, occurring in proportion to products of, e.g., chronic toxicant fractions passed by organs along a pathway, or rates of interacting oncogenic mutations. The Weibull form is also argued theoretically and by simulation to be robust to the onset of saturation kinetics. The Weibull exponential parameter is shown to indicate the number and widths of the first-order compounding increments, the extent of rate autocorrelation, and the degree to which process increments are distributed exponential. In contrast with the Gaussian result in linear independent systems, the form is driven not by independence and multiplicity of process increments, but by increment autocorrelation and entropy. In some physical systems the form may be attracting, due to multiplicative evolution of outcome magnitudes towards extreme values potentially much larger and smaller than control mechanisms can contain. The Weibull distribution is demonstrated in preference to the lognormal and Pareto I for illness severities versus (a toxicokinetic models, (b biologically-based network models, (c scholastic and psychological test score data for children with prenatal mercury exposure, and (d time-to-tumor data of the ED01 study.

  19. Size determinations of plutonium colloids using autocorrelation photon spectroscopy

    International Nuclear Information System (INIS)

    Triay, I.R.; Rundberg, R.S.; Mitchell, A.J.; Ott, M.A.; Hobart, D.E.; Palmer, P.D.; Newton, T.W.; Thompson, J.L.

    1989-01-01

    Autocorrelation Photon Spectroscopy (APS) is a light-scattering technique utilized to determine the size distribution of colloidal suspensions. The capabilities of the APS methodology have been assessed by analyzing colloids of known sizes. Plutonium(IV) colloid samples were prepared by a variety of methods including: dilution; peptization; and alpha-induced auto-oxidation of Pu(III). The size of theses Pu colloids was analyzed using APS. The sizes determined for the Pu colloids studied varied from 1 to 370 nanometers. 7 refs., 5 figs., 3 tabs

  20. Spectral velocity estimation using autocorrelation functions for sparse data sets

    DEFF Research Database (Denmark)

    2006-01-01

    The distribution of velocities of blood or tissue is displayed using ultrasound scanners by finding the power spectrum of the received signal. This is currently done by making a Fourier transform of the received signal and then showing spectra in an M-mode display. It is desired to show a B......-mode image for orientation, and data for this has to acquired interleaved with the flow data. The power spectrum can be calculated from the Fourier transform of the autocorrelation function Ry (k), where its span of lags k is given by the number of emission N in the data segment for velocity estimation...

  1. Stable Blind Deconvolution over the Reals from Additional Autocorrelations

    KAUST Repository

    Walk, Philipp

    2017-10-22

    Recently the one-dimensional time-discrete blind deconvolution problem was shown to be solvable uniquely, up to a global phase, by a semi-definite program for almost any signal, provided its autocorrelation is known. We will show in this work that under a sufficient zero separation of the corresponding signal in the $z-$domain, a stable reconstruction against additive noise is possible. Moreover, the stability constant depends on the signal dimension and on the signals magnitude of the first and last coefficients. We give an analytical expression for this constant by using spectral bounds of Vandermonde matrices.

  2. Autocorrelation based reconstruction of two-dimensional binary objects

    International Nuclear Information System (INIS)

    Mejia-Barbosa, Y.; Castaneda, R.

    2005-10-01

    A method for reconstructing two-dimensional binary objects from its autocorrelation function is discussed. The objects consist of a finite set of identical elements. The reconstruction algorithm is based on the concept of class of element pairs, defined as the set of element pairs with the same separation vector. This concept allows to solve the redundancy introduced by the element pairs of each class. It is also shown that different objects, consisting of an equal number of elements and the same classes of pairs, provide Fraunhofer diffraction patterns with identical intensity distributions. However, the method predicts all the possible objects that produce the same Fraunhofer pattern. (author)

  3. 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.

  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. 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.

  6. 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.

  7. Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

    International Nuclear Information System (INIS)

    Keser, Saniye; Duzgun, Sebnem; Aksoy, Aysegul

    2012-01-01

    Highlights: ► Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. ► Traditional non-spatial regression models may not provide sufficient information for better solid waste management. ► Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. ► Significances of global parameters may diminish at local scale for some provinces. ► GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation data is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global

  8. 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

  9. Do Charitable Foundations Spend Money Where People Need It Most? A Spatial Analysis of China

    Directory of Open Access Journals (Sweden)

    Yongze Song

    2018-03-01

    Full Text Available Charitable foundations are a critical part of public services. However, there is a large gap between the locations and expenditures of charitable foundations and the real population needs for most nations. Three types of Chinese local charity foundations, i.e., those for poverty, education and medical assistance, are used as examples to explore the distinct gaps. The spatial distributions of local charity foundations are characterized by spatial scan statistics and spatial autocorrelation models. The local population needs of charitable assistance for poverty, education and medical services are quantified with their respective weighted proxy indexes of the current conditions. Thus, the nonlinear relationships between population needs and the expenditures of local charitable foundations are described with generalized additive models. The results show that both the participation rate and the charity expenditures of the foundations are highly clustered within a few cities where the population needs are relatively small and are furthermore rare among the other cities. The charity expenditures of local foundations are nonlinearly correlated with the current conditions of socioeconomic development, education and medical levels due to the diverse development stages of the cities. This study provides quantitative evidence for local authorities and charitable foundations to make targeted and constructive decisions to gradually reduce the distinct gaps.

  10. 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.

  11. Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

    Directory of Open Access Journals (Sweden)

    Diego Montenegro

    Full Text Available BACKGROUND Chagas disease (CD, caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE and geometrical analysis for interactive assistance (GAIA methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1 house indicator (HI; (2 triatominae indicator (TI; (3 host/reservoir indicator (Ho/RoI; (4 ecotope indicator (EI; and (5 socio-cultural indicator (S-CI. FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors’ setting (border areas on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector

  12. Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi.

    Science.gov (United States)

    Montenegro, Diego; Cunha, Ana Paula da; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel; Junqueira, Angela

    2017-10-01

    Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors' setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. The study model proposed here is flexible and

  13. Break point on the auto-correlation function of Elsässer variable z- in the super-Alfvénic solar wind fluctuations

    Science.gov (United States)

    Wang, X.; Tu, C. Y.; He, J.; Wang, L.

    2017-12-01

    It has been a longstanding debate on what the nature of Elsässer variables z- observed in the Alfvénic solar wind is. It is widely believed that z- represents inward propagating Alfvén waves and undergoes non-linear interaction with z+ to produce energy cascade. However, z- variations sometimes show nature of convective structures. Here we present a new data analysis on z- autocorrelation functions to get some definite information on its nature. We find that there is usually a break point on the z- auto-correlation function when the fluctuations show nearly pure Alfvénicity. The break point observed by Helios-2 spacecraft near 0.3 AU is at the first time lag ( 81 s), where the autocorrelation coefficient has the value less than that at zero-time lag by a factor of more than 0.4. The autocorrelation function breaks also appear in the WIND observations near 1 AU. The z- autocorrelation function is separated by the break into two parts: fast decreasing part and slowly decreasing part, which cannot be described in a whole by an exponential formula. The breaks in the z- autocorrelation function may represent that the z- time series are composed of high-frequency white noise and low-frequency apparent structures, which correspond to the flat and steep parts of the function, respectively. This explanation is supported by a simple test with a superposition of an artificial random data series and a smoothed random data series. Since in many cases z- autocorrelation functions do not decrease very quickly at large time lag and cannot be considered as the Lanczos type, no reliable value for correlation-time can be derived. Our results showed that in these cases with high Alfvénicity, z- should not be considered as inward-propagating wave. The power-law spectrum of z+ should be made by fluid turbulence cascade process presented by Kolmogorov.

  14. 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

  15. Auto-correlation analysis of ocean surface wind vectors

    Indian Academy of Sciences (India)

    M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

    time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. ... A case study using the TRMM Microwave Imager (TMI) and ... parameter is essential when the values of the parameter ...

  16. 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

  17. Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

    Science.gov (United States)

    Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

    2014-10-01

    The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

  18. 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.

  19. [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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. Spatial-temporal cluster analysis of mortality from road traffic injuries using geographic information systems in West of Iran during 2009-2014.

    Science.gov (United States)

    Zangeneh, Alireza; Najafi, Farid; Karimi, Saeed; Saeidi, Shahram; Izadi, Neda

    2018-04-01

    Road traffic injuries (RTIs) are considered as one of the most important health problems endangering people's life. The examination of the geographical distribution of RTIs could help policymakers in better planning to reduce RTIs. This study, therefore, aimed to determine the spatial-temporal clustering of mortality from RTIs in West of Iran. Deaths from RTIs, registered in Forensic Medicine Organization of Kermanshah province over a period of six years (2009-2014), were used. Using negative binomial regression, the mortality trend was investigated. In order to investigate the spatial distribution of RTIs, we used ArcGIS. (Version 10.3). The median age of the 3231 people died in RTIs was 37 (IQR = 31) year, 78.4% were male. The 6-year average mortality rate from RTIs was 27.8/100,000 deaths, and the average rate had a declining trend. The dispersion of RTIs showed that most deaths occurred in Kermanshah, Islamabad, Bisotun, and Harsin road axes, respectively. The mean center of all deaths from RTIs occurred in Kermanshah province, the central area of Kermanshah district. The spatial trend of such deaths has moved to the northeast-southwest, and such deaths were geographically centralized. Results of Moran's I with respect to cluster analysis also indicated positive spatial autocorrelations. The results showed that the mortality rate from RTIs, despite the decline in recent years, is still high when compared with other countries. The clustering of accidents raises the concern that road infrastructure in certain locations may also be a factor. Regarding the results related to the temporal analysis, it is suggested that the enforcement of traffic rules be stricter at rush hours. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  5. Imbalance in Spatial Accessibility to Primary and Secondary Schools in China: Guidance for Education Sustainability

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2016-11-01

    Full Text Available Compulsory education is an important aspect of the societal development. Meanwhile, education equality safeguards the effectiveness of education systems and is an important part of social equality. This study analyzes the inequality of compulsory education from the perspective of imbalanced spatial distribution. Unlike previous studies that have measured the spatial distribution of education simply based on the spatial position of primary and secondary schools, we explore spatial accessibility based on the shortest travel distance from residents to schools, and then analyze the inequality of compulsory education through the distribution of spatial accessibility. We use 2873 Chinese counties as statistical units, and perform a statistical and graphical analysis of their spatial accessibility using the Theil index and spatial autocorrelation analyses. To analyze the differences in the spatial accessibility distribution on the national and regional levels, we use three partitioned modes: the terrain partitioned mode, the economic development partitioned mode, and the province-level partitioned mode. We then analyze the spatial agglomeration characteristics and distribution patterns of compulsory education accessibility through global autocorrelation, local autocorrelation, and hot-spot and cold-spot analysis. The results demonstrate an obvious imbalance in the distribution of spatial accessibility to compulsory education at the national level. Accessibility and equality in eastern and central regions are significantly better than those in the western region; both are significantly better in coastal regions than in inland regions; and equality alone is better in the municipalities, such as Shanghai, Tianjin, and Chongqing, than in other provinces and autonomous regions. The spatial pattern analysis shows significant global autocorrelation and obvious clusters. Counties in cold-spot areas (clusters of good spatial accessibility are large in number

  6. Covariance Estimation and Autocorrelation of NORAD Two-Line Element Sets

    National Research Council Canada - National Science Library

    Osweiler, Victor P

    2006-01-01

    This thesis investigates NORAD two-line element sets (TLE) containing satellite mean orbital elements for the purpose of estimating a covariance matrix and formulating an autocorrelation relationship...

  7. Intensity autocorrelation measurements of frequency combs in the terahertz range

    Science.gov (United States)

    Benea-Chelmus, Ileana-Cristina; Rösch, Markus; Scalari, Giacomo; Beck, Mattias; Faist, Jérôme

    2017-09-01

    We report on direct measurements of the emission character of quantum cascade laser based frequency combs, using intensity autocorrelation. Our implementation is based on fast electro-optic sampling, with a detection spectral bandwidth matching the emission bandwidth of the comb laser, around 2.5 THz. We find the output of these frequency combs to be continuous even in the locked regime, but accompanied by a strong intensity modulation. Moreover, with our record temporal resolution of only few hundreds of femtoseconds, we can resolve correlated intensity modulation occurring on time scales as short as the gain recovery time, about 4 ps. By direct comparison with pulsed terahertz light originating from a photoconductive emitter, we demonstrate the peculiar emission pattern of these lasers. The measurement technique is self-referenced and ultrafast, and requires no reconstruction. It will be of significant importance in future measurements of ultrashort pulses from quantum cascade lasers.

  8. A Comparison of Various Forecasting Methods for Autocorrelated Time Series

    Directory of Open Access Journals (Sweden)

    Karin Kandananond

    2012-07-01

    Full Text Available The accuracy of forecasts significantly affects the overall performance of a whole supply chain system. Sometimes, the nature of consumer products might cause difficulties in forecasting for the future demands because of its complicated structure. In this study, two machine learning methods, artificial neural network (ANN and support vector machine (SVM, and a traditional approach, the autoregressive integrated moving average (ARIMA model, were utilized to predict the demand for consumer products. The training data used were the actual demand of six different products from a consumer product company in Thailand. Initially, each set of data was analysed using Ljung‐Box‐Q statistics to test for autocorrelation. Afterwards, each method was applied to different sets of data. The results indicated that the SVM method had a better forecast quality (in terms of MAPE than ANN and ARIMA in every category of products.

  9. [Temporal and spatial characteristics of ecological risk in Shunyi, Beijing, China based on landscape structure.

    Science.gov (United States)

    Qing, Feng Ting; Peng, Yu

    2016-05-01

    Based on the remote sensing data in 1997, 2001, 2005, 2009 and 2013, this article classified the landscape types of Shunyi, and the ecological risk index was built based on landscape disturbance index and landscape fragility. The spatial auto-correlation and geostatistical analysis by GS + and ArcGIS was used to study temporal and spatial changes of ecological risk. The results showed that eco-risk degree in the study region had positive spatial correlation which decreased with the increasing grain size. Within a certain grain range (landscape, such as the banks of Chaobai River.

  10. The relationship between language and spatial ability an analysis of spatial language for reconstructing the solving of spatial tasks

    CERN Document Server

    Mizzi, Angel

    2017-01-01

    This work investigates how different fifth-grade students solve spatial-verbal tasks and the role of language in this process. Based on a synthesis of theoretical foundations and methodological issues for supporting the relationship between spatial ability and language, this present study examines and classifies strategies used by students as well as the obstacles they encounter when solving spatial tasks in the reconstruction method. Contents Theoretical Framework Design and Implementation Results and Discussion from the Inductive Data Analyses Target Groups Scholars and students of mathematics education Teachers of mathematics in primary and secondary schools About the Author Angel Mizzi works as a research assistant and lecturer at the University of Duisburg-Essen, where he has successfully completed his PhD studies in mathematics education.

  11. [Spatial analysis of autumn-winter type scrub typhus in Shandong province, 2006-2014].

    Science.gov (United States)

    Yang, H; Bi, Z W; Kou, Z Q; Zheng, L; Zhao, Z T

    2016-05-01

    To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province, and provide scientific evidence for further study for the prevention and control of the disease. The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System. The data was analyzed by using software ArcGIS 9.3(ESRI Inc., Redlands, CA, USA), GeoDa 0.9.5-i and SatScan 9.1.1. The Moran' s I, log-likelihood ratio(LLR), relative risk(RR)were calculated and the incidence choropleth maps, local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn. A total of 4 453 scrub typhus cases were reported during 2006-2014, and the annual incidence increased with year. Among the 17 prefectures(municipality)in Shandong, 13 were affected by scrub typhus. The global Moran's I index was 0.501 5(Pscrub typhus in Shandong. Since 2006, the epidemic area of the disease has expanded and the number of high-risk areas has increased. Moreover, the eastward moving and periodically expanding trends of high-risk clusters were detected.

  12. 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.

  13. Some notes concerning the fourier transformation of auto-correlation functions; Quelques notes sur la transformee de fourier des fonctions d'autocorrelation

    Energy Technology Data Exchange (ETDEWEB)

    Froelicher, B; Dalfes, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1968-07-01

    A study is made of the passage of the auto-correlation function to the frequency spectrum by a numerical Fourier transformation. Two principal characteristics of auto-correlation functions, the time between two points and the total time, are related to two oscillations which appear in the frequency spectrum and which deform it. Various methods are proposed for reducing the effect of these two parasitic oscillations and for re-obtaining the real spectrum. (authors) [French] On etudie le passage de la fonction d'autocorrelation au spectre de frequence par transformee de Fourier numerique. Deux caracteristiques principales des fonctions d'autocorrelation, la duree entre points et la duree totale sont reliees a deux oscillations qui apparaissent dans le spectre de frequence et le deforment. Diverses methodes sont proposees pour reduire l'effet de ces deux oscillations parasites, et retrouver le spectre reel. (auteurs)

  14. Integrating the statistical analysis of spatial data in ecology

    Science.gov (United States)

    A. M. Liebhold; J. Gurevitch

    2002-01-01

    In many areas of ecology there is an increasing emphasis on spatial relationships. Often ecologists are interested in new ways of analyzing data with the objective of quantifying spatial patterns, and in designing surveys and experiments in light of the recognition that there may be underlying spatial pattern in biotic responses. In doing so, ecologists have adopted a...

  15. Spatial prediction of landslide hazard using discriminant analysis and GIS

    Science.gov (United States)

    Peter V. Gorsevski; Paul Gessler; Randy B. Foltz

    2000-01-01

    Environmental attributes relevant for spatial prediction of landslides triggered by rain and snowmelt events were derived from digital elevation model (DEM). Those data in conjunction with statistics and geographic information system (GIS) provided a detailed basis for spatial prediction of landslide hazard. The spatial prediction of landslide hazard in this paper is...

  16. 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

  17. A Poisson-lognormal conditional-autoregressive model for multivariate spatial analysis of pedestrian crash counts across neighborhoods.

    Science.gov (United States)

    Wang, Yiyi; Kockelman, Kara M

    2013-11-01

    This work examines the relationship between 3-year pedestrian crash counts across Census tracts in Austin, Texas, and various land use, network, and demographic attributes, such as land use balance, residents' access to commercial land uses, sidewalk density, lane-mile densities (by roadway class), and population and employment densities (by type). The model specification allows for region-specific heterogeneity, correlation across response types, and spatial autocorrelation via a Poisson-based multivariate conditional auto-regressive (CAR) framework and is estimated using Bayesian Markov chain Monte Carlo methods. Least-squares regression estimates of walk-miles traveled per zone serve as the exposure measure. Here, the Poisson-lognormal multivariate CAR model outperforms an aspatial Poisson-lognormal multivariate model and a spatial model (without cross-severity correlation), both in terms of fit and inference. Positive spatial autocorrelation emerges across neighborhoods, as expected (due to latent heterogeneity or missing variables that trend in space, resulting in spatial clustering of crash counts). In comparison, the positive aspatial, bivariate cross correlation of severe (fatal or incapacitating) and non-severe crash rates reflects latent covariates that have impacts across severity levels but are more local in nature (such as lighting conditions and local sight obstructions), along with spatially lagged cross correlation. Results also suggest greater mixing of residences and commercial land uses is associated with higher pedestrian crash risk across different severity levels, ceteris paribus, presumably since such access produces more potential conflicts between pedestrian and vehicle movements. Interestingly, network densities show variable effects, and sidewalk provision is associated with lower severe-crash rates. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2011-11-01

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

  19. An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

    Science.gov (United States)

    Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

    2018-04-20

    Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

  20. A Quantized Analog Delay for an ir-UWB Quadrature Downconversion Autocorrelation Receiver

    NARCIS (Netherlands)

    Bagga, S.; Zhang, L.; Serdijn, W.A.; Long, J.R.; Busking, E.B.

    2005-01-01

    A quantized analog delay is designed as a requirement for the autocorrelation function in the quadrature downconversion autocorrelation receiver (QDAR). The quantized analog delay is comprised of a quantizer, multiple binary delay lines and an adder circuit. Being the foremost element, the quantizer

  1. Generalised partial autocorrelations and the mutual information between past and future

    DEFF Research Database (Denmark)

    Proietti, Tommaso; Luati, Alessandra

    the generalized partial autocorrelations as the partial autocorrelation coefficients of an auxiliary process, we derive their properties and relate them to essential features of the original process. Based on a parameterisation suggested by Barndorff-Nielsen and Schou (1973) and on Whittle likelihood, we develop...

  2. MATLAB-Based Program for Teaching Autocorrelation Function and Noise Concepts

    Science.gov (United States)

    Jovanovic Dolecek, G.

    2012-01-01

    An attractive MATLAB-based tool for teaching the basics of autocorrelation function and noise concepts is presented in this paper. This tool enhances traditional in-classroom lecturing. The demonstrations of the tool described here highlight the description of the autocorrelation function (ACF) in a general case for wide-sense stationary (WSS)…

  3. How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

    Science.gov (United States)

    Blumenthal, George R.; Johnston, Kathryn V.

    1994-01-01

    The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

  4. Study of academic achievements using spatial analysis tools

    Science.gov (United States)

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

    2012-04-01

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

  5. 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||.

  6. Spatial distribution and risk factors of influenza in Jiangsu province, China, based on geographical information system

    Directory of Open Access Journals (Sweden)

    Jia-Cheng Zhang

    2014-05-01

    Full Text Available Influenza poses a constant, heavy burden on society. Recent research has focused on ecological factors associated with influenza incidence and has also studied influenza with respect to its geographic spread at different scales. This research explores the temporal and spatial parameters of influenza and identifies factors influencing its transmission. A spatial autocorrelation analysis, a spatial-temporal cluster analysis and a spatial regression analysis of influenza rates, carried out in Jiangsu province from 2004 to 2011, found that influenza rates to be spatially dependent in 2004, 2005, 2006 and 2008. South-western districts consistently revealed hotspots of high-incidence influenza. The regression analysis indicates that railways, rivers and lakes are important predictive environmental variables for influenza risk. A better understanding of the epidemic pattern and ecological factors associated with pandemic influenza should benefit public health officials with respect to prevention and controlling measures during future epidemics.

  7. Autocorrelation Study of Solar Wind Plasma and IMF Properties as Measured by the MAVEN Spacecraft

    Science.gov (United States)

    Marquette, Melissa L.; Lillis, Robert J.; Halekas, J. S.; Luhmann, J. G.; Gruesbeck, J. R.; Espley, J. R.

    2018-04-01

    It has long been a goal of the heliophysics community to understand solar wind variability at heliocentric distances other than 1 AU, especially at ˜1.5 AU due to not only the steepening of solar wind stream interactions outside 1 AU but also the number of missions available there to measure it. In this study, we use 35 months of solar wind and interplanetary magnetic field (IMF) data taken at Mars by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft to conduct an autocorrelation analysis of the solar wind speed, density, and dynamic pressure, which is derived from the speed and density, as well as the IMF strength and orientation. We found that the solar wind speed is coherent, that is, has an autocorrelation coefficient above 1/e, over roughly 56 hr, while the density and pressure are coherent over smaller intervals of roughly 25 and 20 hr, respectively, and that the IMF strength is coherent over time intervals of approximately 20 hr, while the cone and clock angles are considerably less steady but still somewhat coherent up to time lags of roughly 16 hr. We also found that when the speed, density, pressure, or IMF strength is higher than average, the solar wind or IMF becomes uncorrelated more quickly, while when they are below average, it tends to be steadier. This analysis allows us to make estimates of the values of solar wind plasma and IMF parameters when they are not directly measured and provide an approximation of the error associated with that estimate.

  8. Persistent solar signatures in cloud cover: spatial and temporal analysis

    International Nuclear Information System (INIS)

    Voiculescu, M; Usoskin, I

    2012-01-01

    A consensus regarding the impact of solar variability on cloud cover is far from being reached. Moreover, the impact of cloud cover on climate is among the least understood of all climate components. This motivated us to analyze the persistence of solar signals in cloud cover for the time interval 1984–2009, covering two full solar cycles. A spatial and temporal investigation of the response of low, middle and high cloud data to cosmic ray induced ionization (CRII) and UV irradiance (UVI) is performed in terms of coherence analysis of the two signals. For some key geographical regions the response of clouds to UVI and CRII is persistent over the entire time interval indicating a real link. In other regions, however, the relation is not consistent, being intermittent or out of phase, suggesting that some correlations are spurious. The constant in phase or anti-phase relationship between clouds and solar proxies over some regions, especially for low clouds with UVI and CRII, middle clouds with UVI and high clouds with CRII, definitely requires more study. Our results show that solar signatures in cloud cover persist in some key climate-defining regions for the entire time period and supports the idea that, if existing, solar effects are not visible at the global level and any analysis of solar effects on cloud cover (and, consequently, on climate) should be done at the regional level. (letter)

  9. Signal Adaptive System for Space/Spatial-Frequency Analysis

    Directory of Open Access Journals (Sweden)

    Veselin N. Ivanović

    2009-01-01

    Full Text Available This paper outlines the development of a multiple-clock-cycle implementation (MCI of a signal adaptive two-dimensional (2D system for space/spatial-frequency (S/SF signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA circuit design, capable of performing S/SF analysis of 2D signals in real time.

  10. 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...

  11. Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis.

    Science.gov (United States)

    Lee, Seohyun; Cho, Yoon-Min; Kim, Sun-Young

    2017-08-22

    Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran's I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the

  12. 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 ...

  13. A single-shot nonlinear autocorrelation approach for time-resolved physics in the vacuum ultraviolet spectral range

    International Nuclear Information System (INIS)

    Rompotis, Dimitrios

    2016-02-01

    In this work, a single-shot temporal metrology scheme operating in the vacuum-extreme ultraviolet spectral range has been designed and experimentally implemented. Utilizing an anti-collinear geometry, a second-order intensity autocorrelation measurement of a vacuum ultraviolet pulse can be performed by encoding temporal delay information on the beam propagation coordinate. An ion-imaging time-of-flight spectrometer, offering micrometer resolution has been set-up for this purpose. This instrument enables the detection of a magnified image of the spatial distribution of ions exclusively generated by direct two-photon absorption in the combined counter-propagating pulse focus and thus obtain the second-order intensity autocorrelation measurement on a single-shot basis. Additionally, an intense VUV light source based on high-harmonic generation has been experimentally realized. It delivers intense sub-20 fs Ti:Sa fifth-harmonic pulses utilizing a loose-focusing geometry in a long Ar gas cell. The VUV pulses centered at 161.8 nm reach pulse energies of 1.1 μJ per pulse, while the corresponding pulse duration is measured with a second-order, fringe-resolved autocorrelation scheme to be 18 ± 1 fs on average. Non-resonant, two-photon ionization of Kr and Xe and three-photon ionization of Ne verify the fifth-harmonic pulse intensity and indicate the feasibility of multi-photon VUV pump/VUV probe studies of ultrafast atomic and molecular dynamics. Finally, the extended functionally of the counter-propagating pulse metrology approach is demonstrated by a single-shot VUV pump/VUV probe experiment aiming at the investigation of ultrafast dissociation dynamics of O 2 excited in the Schumann-Runge continuum at 162 nm.

  14. FTO Genotype and Type 2 Diabetes Mellitus: Spatial Analysis and Meta-Analysis of 62 Case-Control Studies from Different Regions

    Directory of Open Access Journals (Sweden)

    Ying Yang

    2017-02-01

    Full Text Available Type 2 diabetes mellitus (T2DM is a global health problem that results from the interaction of environmental factors with genetic variants. Although a number of studies have suggested that genetic polymorphisms in the fat mass and obesity-associated (FTO gene are associated with T2DM risk, the results have been inconsistent. To investigate whether FTO polymorphisms associate with T2DM risk and whether this association is region-related, we performed this spatial analysis and meta-analysis. More than 60,000 T2DM patients and 90,000 controls from 62 case-control studies were included in this study. Odds ratios (ORs, 95% confidence intervals (CIs and Moran’s I statistic were used to estimate the association between FTO rs9939609, rs8050136, rs1421085, and rs17817499, and T2DM risk in different regions. rs9939609 (OR = 1.15, 95% CI 1.11–1.19 and rs8050136 (OR = 1.14, 95% CI 1.10–1.18 conferred a predisposition to T2DM. After adjustment for body mass index (BMI, the association remained statistically significant for rs9939609 (OR = 1.11, 95% CI 1.05–1.17 and rs8050136 (OR = 1.08, 95% CI 1.03–1.12. In the subgroup analysis of rs9939609 and rs8050136, similar results were observed in East Asia, while no association was found in North America. In South Asia, an association for rs9939609 was revealed but not for rs8050136. In addition, no relationship was found with rs1421085 or rs17817499 regardless of adjustment for BMI. Moran’s I statistic showed that significant positive spatial autocorrelations existed in rs9939609 and rs8050136. Studies on rs9939609 and rs8050136 focused on East Asia and South Asia, whereas studies on rs1421085 and rs17817499 were distributed in North America and North Africa. Our data suggest that the associations between FTO rs9939609, rs8050136 and T2DM are region-related, and the two single-nucleotide polymorphisms contribute to an increased risk of T2DM. Future studies should investigate this issue in more regions.

  15. Analysis of Spatial Voting Patterns: An Approach in Political Socialization

    Science.gov (United States)

    Klimasewski, Ted

    1973-01-01

    Passage of the 26th Amendment gave young adults the right to vote. This study attempts to further student understanding of the electoral process by presenting a method for analyzing spatial voting patterns. The spatial emphasis adds another dimension to the temporal and behavioral-structural approaches in studying the American electoral system.…

  16. Fractal Dimension analysis for seismicity spatial and temporal ...

    Indian Academy of Sciences (India)

    23

    The research can further promote the application of fractal theory in the study ... spatial-temporal propagation characteristics of seismic activities, fractal theory is not ... provide a theoretical basis for the prevention and control of earthquakes. 2. ... random self-similar structure of the earthquake in the time series and the spatial.

  17. using gis for spatial exploratory analysis of borehole data

    African Journals Online (AJOL)

    PUBLICATIONS1

    Thus, understanding the spatial structure of aquifer characteristics could be used as a resourceful tool and as a .... x is position in one dimensional space. N(h) is Pairwise ... best fitted theoretical models, the spatial struc- ture of each variable ...

  18. A Principal Components Analysis of Dynamic Spatial Memory Biases

    Science.gov (United States)

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

    2008-01-01

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

  19. Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

    Directory of Open Access Journals (Sweden)

    Nicolas Chemidlin Prévost-Bouré

    Full Text Available Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2: i to examine their spatial structuring; ii to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landesanalysis. This study demonstrates significant community composition turnover rates for soil bacteria and fungi, which were dependent on the region. Bacterial and fungal community composition turnovers were mainly driven by environmental selection explaining from 10% to 20% of community composition variations, but spatial variables also explained 3% to 9% of total variance. These variables highlighted significant spatial autocorrelation of both communities unexplained by the environmental variables measured and could partly be explained by dispersal limitations. Although the identified filters and their hierarchy were dependent on the region and organism, selection was systematically based on a common group of environmental variables: pH, trophic resources, texture and land use. Spatial autocorrelation was also important at

  20. Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

    Science.gov (United States)

    Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

    2014-01-01

    Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landescommunities' composition turnovers. The relative importance of processes and filters was assessed by distance-based redundancy analysis. This study demonstrates significant community composition turnover rates for soil bacteria and fungi, which were dependent on the region. Bacterial and fungal community composition turnovers were mainly driven by environmental selection explaining from 10% to 20% of community composition variations, but spatial variables also explained 3% to 9% of total variance. These variables highlighted significant spatial autocorrelation of both communities unexplained by the environmental variables measured and could partly be explained by dispersal limitations. Although the identified filters and their hierarchy were dependent on the region and organism, selection was systematically based on a common group of environmental variables: pH, trophic resources, texture and land use. Spatial autocorrelation was also important at coarse (80 to 120 km radius) and/or medium (40 to 65 km radius) spatial scales, suggesting dispersal limitations at these scales.

  1. Spatial variability of microbial richness and diversity and relationships with soil organic carbon, texture and structure across an agricultural field

    DEFF Research Database (Denmark)

    Naveed, Muhammad; Herath, Lasantha; Møldrup, Per

    2016-01-01

    Highlights •Bacterial richness and Shannon diversity showed strong spatial autocorrelations. •Fungal richness and Shannon diversity did not show any clear spatial autocorrelations. •Ratio of clay to organic carbon was found a best predictor of bacterial richness and diversities. •Soil water...

  2. On the 2nd order autocorrelation of an XUV attosecond pulse train

    International Nuclear Information System (INIS)

    Tzallas, P.; Benis, E.; Nikolopoulos, L.A.A.; Tsakiris, G.D.; Witte, K.; Charalambidis, P

    2005-01-01

    Full text: We present the first direct measurement of sub-fs light bunching that has been achieved, extending well established fs optical metrology to XUV as pulses. A mean train pulse duration of 780 as has been extracted through a 2 nd order autocorrelation approach, utilizing a nonlinear effect that is induced solely by the XUV radiation to be characterized. The approach is based on (i) a bisected spherical mirror XUV wavefront divider used as an autocorrelator and (ii) the two photon ionization of atomic He by a superposition of the 7 th to the 15 th harmonic of a Ti:sapph laser. The measured temporal mean width is more than twice its Fourier transform limited (FTL) value, in contrast to the as train pulse durations measured through other approaches, which where found much closer to the FTL values. We have investigated, and discuss here the origin of this discrepancy. An assessment of the validity of the 2 nd order AC approach for the broad band XUV radiation of as pulses is implemented through ab initio calculations (solution of the 3D TDSE of He in the presence of the superposition of the harmonic superposition) modeling the spectral and temporal response of the two-XUV-photon He ionization detector employed. It is found that both the spectral and temporal response are not affecting the measured duration. The mean width of the as train bursts is estimated from the spectral phases of the individual harmonics as they result from the rescattering model, taking into account the spatially modulated temporal width of the radiation due to the spatiotemporal intensity distribution of the driving field during the harmonic generation process. The measured value is found in reasonable agreement with the estimated duration. The method used for the 2 nd order AC in itself initiates further XUV-pump-XUV-probe studies of sub-fs-scale dynamics and at the same time becomes highly pertinent in connection with nonlinear experiments using XUV free - electron laser sources. Refs

  3. Capacity analysis of spectrum sharing spatial multiplexing MIMO systems

    KAUST Repository

    Yang, Liang; Qaraqe, Khalid A.; Serpedin, Erchin; Alouini, Mohamed-Slim

    2014-01-01

    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

  4. A preliminary survey and analysis of the spatial distribution of ...

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River ... of taxa was recorded in marginal vegetation in the channels and lagoons, ... highlights the importance of maintaining a mosaic of aquatic habitats in the Delta.

  5. A preliminary survey and analysis of the spatial distribution of ...

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River Delta, ... seasonally-flooded pools and temporary rain-filled pools in MGR and CI. ... biodiversity of the Okavango Delta, thereby contributing to its conservation.

  6. Spatial analysis based on variance of moving window averages

    OpenAIRE

    Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J

    2006-01-01

    A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...

  7. [Spatial distribution of occupational disease prevalence in Guangzhou and Foshan city by geographic information system].

    Science.gov (United States)

    Tan, Q; Tu, H W; Gu, C H; Li, X D; Li, R Z; Wang, M; Chen, S G; Cheng, Y J; Liu, Y M

    2017-11-20

    Objective: To explore the occupational disease spatial distribution characteristics in Guangzhou and Foshan city in 2006-2013 with Geographic Information System and to provide evidence for making control strategy. Methods: The data on occupational disease diagnosis in Guangzhou and Foshan city from 2006 through 2013 were collected and linked to the digital map at administrative county level with Arc GIS12.0 software for spatial analysis. Results: The maps of occupational disease and Moran's spatial autocor-relation analysis showed that the spatial aggregation existed in Shunde and Nanhai region with Moran's index 1.727, -0.003. Local Moran's I spatial autocorrelation analysis pointed out the "positive high incidence re-gion" and the "negative high incidence region" during 2006~2013. Trend analysis showed that the diagnosis case increased slightly then declined from west to east, increase obviously from north to south, declined from? southwest to northeast, high in the middle and low on both sides in northwest-southeast direction. Conclusions: The occupational disease is obviously geographical distribution in Guangzhou and Foshan city. The corresponding prevention measures should be made according to the geographical distribution.

  8. Spatial Analysis of Case-Mix and Dialysis Modality Associations.

    Science.gov (United States)

    Phirtskhalaishvili, Tamar; Bayer, Florian; Edet, Stephane; Bongiovanni, Isabelle; Hogan, Julien; Couchoud, Cécile

    2016-01-01

    ♦ Health-care systems must attempt to provide appropriate, high-quality, and economically sustainable care that meets the needs and choices of patients with end-stage renal disease (ESRD). France offers 9 different modalities of dialysis, each characterized by dialysis technique, the extent of professional assistance, and the treatment site. The aim of this study was 1) to describe the various dialysis modalities in France and the patient characteristics associated with each of them, and 2) to analyze their regional patterns to identify possible unexpected associations between case-mixes and dialysis modalities. ♦ The clinical characteristics of the 37,421 adult patients treated by dialysis were described according to their treatment modality. Agglomerative hierarchical cluster analysis was used to aggregate the regions into clusters according to their use of these modalities and the characteristics of their patients. ♦ The gradient of patient characteristics was similar from home hemodialyis (HD) to in-center HD and from non-assisted automated peritoneal dialysis (APD) to assisted continuous ambulatory peritoneal dialysis (CAPD). Analyzing their spatial distribution, we found differences in the patient case-mix on dialysis across regions but also differences in the health-care provided for them. The classification of the regions into 6 different clusters allowed us to detect some unexpected associations between case-mixes and treatment modalities. ♦ The 9 modalities of treatment available make it theoretically possible to adapt treatment to patients' clinical characteristics and abilities. However, although we found an overall appropriate association of dialysis modalities to the case-mix, major inter-region heterogeneity and the low rate of peritoneal dialysis (PD) and home HD suggest that factors besides patients' clinical conditions impact the choice of dialysis modality. The French organization should now be evaluated in terms of patients' quality of

  9. 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

  10. 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)

  11. A broadly tunable autocorrelator for ultra-short, ultra-high power infrared optical pulses

    Energy Technology Data Exchange (ETDEWEB)

    Szarmes, E.B.; Madey, J.M.J. [Duke Univ., Durham, NC (United States)

    1995-12-31

    We describe the design of a crossed-beam, optical autocorrelator that uses an uncoated, birefringent beamsplitter to split a linearly polarized incident pulse into two orthogonally polarized pulses, and a Type II, SHG crystal to generate the intensity autocorrelation function. The uncoated beamsplitter accommodates extremely broad tunability while precluding any temporal distortion of ultrashort optical pulses at the dielectric interface, and the specific design provides efficient operation between 1 {mu}m and 4 {mu}m. Furthermore, the use of Type II SHG completely eliminates any single-beam doubling, so the autocorrelator can be operated at very shallow crossed-beam angles without generating a background pedestal. The autocorrelator has been constructed and installed in the Mark III laboratory at Duke University as a broadband diagnostic for ongoing compression experiments on the chirped-pulse FEL.

  12. Performing T-tests to Compare Autocorrelated Time Series Data Collected from Direct-Reading Instruments.

    Science.gov (United States)

    O'Shaughnessy, Patrick; Cavanaugh, Joseph E

    2015-01-01

    Industrial hygienists now commonly use direct-reading instruments to evaluate hazards in the workplace. The stored values over time from these instruments constitute a time series of measurements that are often autocorrelated. Given the need to statistically compare two occupational scenarios using values from a direct-reading instrument, a t-test must consider measurement autocorrelation or the resulting test will have a largely inflated type-1 error probability (false rejection of the null hypothesis). A method is described for both the one-sample and two-sample cases which properly adjusts for autocorrelation. This method involves the computation of an "equivalent sample size" that effectively decreases the actual sample size when determining the standard error of the mean for the time series. An example is provided for the one-sample case, and an example is given where a two-sample t-test is conducted for two autocorrelated time series comprised of lognormally distributed measurements.

  13. Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach

    Science.gov (United States)

    Salleh, R. M.; Zawawi, N. I.; Gan, Z. F.; Nor, M. E.

    2018-04-01

    Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jenkins method is too complicated and challenging which cause of time-consuming. Therefore, an alternative method which known as Geometric Brownian Motion (GBM) is introduced to monitor the autocorrelated process. One real case of furnace temperature data is conducted to compare the performance of Box-Jenkins and GBM methods in monitoring autocorrelation process. Both methods give the same results in terms of model accuracy and monitoring process control. Yet, GBM is superior compared to Box-Jenkins method due to its simplicity and practically with shorter computational time.

  14. Toward sub-femtosecond pump-probe experiments: a dispersionless autocorrelator with attosecond resolution

    Energy Technology Data Exchange (ETDEWEB)

    Constant, E.; Mevel, E.; Zair, A.; Bagnoud, V.; Salin, F. [Bordeaux-1 Univ., Talence (FR). Centre Lasers Intenses et Applications (CELIA)

    2001-07-01

    We designed a dispersionless autocorrelator with a sub-femtosecond resolution suitable for the characterization of ultrashort X-UV pulses. We present a proof of feasibility experiment with 11 fs infrared pulses. (orig.)

  15. Detecting land cover change using a sliding window temporal autocorrelation approach

    CSIR Research Space (South Africa)

    Kleynhans, W

    2012-07-01

    Full Text Available There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development...

  16. 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

  17. FROM UNEMPLOYMENT TO WORK: AN ECONOMETRIC ANALYSIS WITH SPATIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    Oana Calavrezo

    2009-03-01

    Full Text Available The aim of our research is to analyze how the urban organization affects the unemployment-to-work transitions by considering several spatial indicators. This permits to capture two separate effects: "spatial mismatch" and "neighbourhood effects". In order to study the unemployment-to-work transitions, we implement survival models. They are applied on a sample obtained by merging three French databases: the "Trajectoires des demandeurs d'emplois" survey, the 1999 French census and finally, a database containing town inventory information. More precisely, in this paper, we analyze the duration of the first observed employment episode by using spatial indicators and by controlling three potential biases (endogeneity bias, selection bias and attrition bias.

  18. A digital elevation analysis: Spatially distributed flow apportioning algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang-Hyun; Kim, Kyung-Hyun [Pusan National University, Pusan(Korea); Jung, Sun-Hee [Korea Environment Institute, (Korea)

    2001-06-30

    A flow determination algorithm is proposed for the distributed hydrologic model. The advantages of a single flow direction scheme and multiple flow direction schemes are selectively considered to address the drawbacks of existing algorithms. A spatially varied flow apportioning factor is introduced in order to accommodate the accumulated area from upslope cells. The channel initiation threshold area(CIT) concept is expanded and integrated into the spatially distributed flow apportioning algorithm in order to delineate a realistic channel network. An application of a field example suggests that the linearly distributed flow apportioning scheme provides some advantages over existing approaches, such as the relaxation of over-dissipation problems near channel cells, the connectivity feature of river cells, the continuity of saturated areas and the negligence of the optimization of few parameters in existing algorithms. The effects of grid sizes are explored spatially as well as statistically. (author). 28 refs., 7 figs.

  19. Spatial distribution of vehicle emission inventories in the Federal District, Brazil

    Science.gov (United States)

    Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer

    2015-07-01

    Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.

  20. Spatial analysis of root hemiparasitic shrubs and their hosts

    DEFF Research Database (Denmark)

    Dueholm, Bjørn; Bruce, David; Weinstein, Philip

    2017-01-01

    to as spatial signatures of the root hemiparasites. In order to search for such spatial signatures, we investigated a population of a predominant Acacia species in Australia co-occurring with established root hemiparasitic shrubs, using intensity estimates of the Acacia and dead shrubs to be indicators...... of parasite populations. We find evidence that the root hemiparasitic shrubs, like herbaceous root hemiparasites, prefer growing at distances from neighbouring plants that fulfil resource requirements both below-ground and above-ground. Assuming that root hemiparasites are limited by their hosts, we present...

  1. Spatially Explicit Analysis of Water Footprints in the UK

    Directory of Open Access Journals (Sweden)

    John Barrett

    2010-12-01

    Full Text Available The Water Footprint, as an indicator of water consumption has become increasingly popular for analyzing environmental issues associated with the use of water resources in the global supply chain of consumer goods. This is particularly relevant for countries like the UK, which increasingly rely on products produced elsewhere in the world and thus impose pressures on foreign water resources. Existing studies calculating water footprints are mostly based on process analysis, and results are mainly available at the national level. The current paper assesses the domestic and foreign water requirements for UK final consumption by applying an environmentally extended multi-regional input-output model in combination with geo-demographic consumer segmentation data. This approach allows us to calculate water footprints (both direct and indirect for different products as well as different geographies within the UK. We distinguished between production and consumption footprints where the former is the total water consumed from the UK domestic water resources by the production activities in the UK and the latter is the total water consumed from both domestic and global water resources to satisfy the UK domestic final consumption. The results show that the production water footprint is 439 m3/cap/year, 85% of which is for the final consumption in the UK itself. The average consumption water footprint of the UK is more than three times bigger than the UK production water footprint in 2006. About half of the UK consumption water footprints were associated with imports from Non-OECD countries (many of which are water-scarce, while around 19% were from EU-OECD countries, and only 3% from Non-EU-OECD countries. We find that the water footprint differs considerably across sub-national geographies in the UK, and the differences are as big as 273 m3/cap/year for the internal water footprint and 802 m3/cap/year for the external water footprint. Our results suggest

  2. Carbon Sequestration in Colorado's Lands: A Spatial and Policy Analysis

    Science.gov (United States)

    Brandt, N.; Brazeau, A.; Browning, K.; Meier, R.

    2017-12-01

    Managing landscapes to enhance terrestrial carbon sequestration has significant potential to mitigate climate change. While a previous carbon baseline assessment in Colorado has been published (Conant et al, 2007), our study pulls from the existing literature to conduct an updated baseline assessment of carbon stocks and a unique review of carbon policies in Colorado. Through a multi-level spatial analysis based in GIS and informed by a literature review, we established a carbon stock baseline and ran four land use and carbon stock projection scenarios using Monte Carlo simulations. We identified 11 key policy recommendations for improving Colorado's carbon stocks, and evaluated each using Bardach's policy matrix approach (Bardach, 2012). We utilized a series of case studies to support our policy recommendations. We found that Colorado's lands have a carbon stock of 3,334 MMT CO2eq, with Forests and Woodlands holding the largest stocks, at 1,490 and 774 MMT CO2eq respectively. Avoided conversion of all Grasslands, Forests, and Wetlands in Colorado projected over 40 years would increase carbon stocks by 32 MMT CO2eq, 1,053 MMT CO2eq, and 36 MMT CO2eq, respectively. Over the 40-year study period, Forests and Woodlands areas are projected to shrink while Shrublands and Developed areas are projected to grow. Those projections suggest sizable increases in area of future wildfires and development in Colorado. We found that numerous policy opportunities to sequester carbon exist at different jurisdictional levels and across land cover types. The largest opportunities were found in state-level policies and policies impacting Forests, Grasslands, and Wetlands. The passage of statewide emission reduction legislation has the highest potential to impact carbon sequestration, although political and administrative feasibility of this option are relatively low. This study contributes to the broader field of carbon sequestration literature by examining the nexus of carbon stocks

  3. SPATIALLY AUTOCORRELATED DEMOGRAPHY AND INTERPOND MIGRATION IN THE CALIFORNIA TIGER SALAMANDER (AMBYSTOME CALIFORNIENSE)

    Science.gov (United States)

    We investigated the metapopulation structure of the California tiger salamander (Ambystoma californiense) using a combination of indirect and direct methods to evaluate two key requirements of modern metapopulation models: 1) that patches support somewhat independent populations ...

  4. Analysis of spatial count data using Kalman smoothing

    DEFF Research Database (Denmark)

    Dethlefsen, Claus

    2007-01-01

    We consider spatial count data from an agricultural field experiment. Counts of weed plants in a field have been recorded in a project on precision farming. Interest is in mapping the weed intensity so that the dose of herbicide applied at any location can be adjusted to the amount of weed present...

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

    Science.gov (United States)

    Brunner, Robert L.; And Others

    1987-01-01

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

  6. Tucker tensor analysis of Matern functions in spatial statistics

    KAUST Repository

    Litvinenko, Alexander

    2018-04-20

    Low-rank Tucker tensor methods in spatial statistics 1. Motivation: improve statistical models 2. Motivation: disadvantages of matrices 3. Tools: Tucker tensor format 4. Tensor approximation of Matern covariance function via FFT 5. Typical statistical operations in Tucker tensor format 6. Numerical experiments

  7. Geometric anisotropic spatial point pattern analysis and Cox processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Toftaker, Håkon

    . In particular we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial...

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

    Science.gov (United States)

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

    2015-12-01

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

  9. Using GIS for spatial exploratory analysis of borehole data: a ...

    African Journals Online (AJOL)

    Groundwater is an inimitable resource that provides water to communities especially in arid and semi-arid regions. However, the spatial variability of the resource as well as the heterogeneity and complex nature of aquifer systems that store groundwater presents difficulties for groundwater development. Thus ...

  10. An analysis of trends in spatial mobility of Dutch graduates

    NARCIS (Netherlands)

    Venhorst, Viktor; Van Dijk, Jouke; Van Wissen, Leo

    Considerable attention in the literature has been devoted to spatial mobility as a mechanism in the transition from study to work. In this paper, the relationships between migration and both regional economic circumstances and individual characteristics are investigated using a micro-dataset on

  11. Rockfall hazard analysis using LiDAR and spatial modeling

    Science.gov (United States)

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

    2010-05-01

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

  12. 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.

  13. SPATIAL ANALYSIS OF RESIDENTS' FEAR AND FEELING OF ...

    African Journals Online (AJOL)

    Osondu

    Abstract. This study examined spatial pattern of crime and residents' fear and feeling of insecurity in Ile-Ife,. Nigeria. To obtain the primary data, Ile-Ife was stratified into four residential zones namely traditional town centre, middle income, high income and post-crisis residential areas. Sample was selected using systematic ...

  14. Analysis of spatial distribution of land cover maps accuracy

    Science.gov (United States)

    Khatami, R.; Mountrakis, G.; Stehman, S. V.

    2017-12-01

    Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain

  15. Analysis of a spatial orientation memory in Drosophila.

    Science.gov (United States)

    Neuser, Kirsa; Triphan, Tilman; Mronz, Markus; Poeck, Burkhard; Strauss, Roland

    2008-06-26

    Flexible goal-driven orientation requires that the position of a target be stored, especially in case the target moves out of sight. The capability to retain, recall and integrate such positional information into guiding behaviour has been summarized under the term spatial working memory. This kind of memory contains specific details of the presence that are not necessarily part of a long-term memory. Neurophysiological studies in primates indicate that sustained activity of neurons encodes the sensory information even though the object is no longer present. Furthermore they suggest that dopamine transmits the respective input to the prefrontal cortex, and simultaneous suppression by GABA spatially restricts this neuronal activity. Here we show that Drosophila melanogaster possesses a similar spatial memory during locomotion. Using a new detour setup, we show that flies can remember the position of an object for several seconds after it has been removed from their environment. In this setup, flies are temporarily lured away from the direction towards their hidden target, yet they are thereafter able to aim for their former target. Furthermore, we find that the GABAergic (stainable with antibodies against GABA) ring neurons of the ellipsoid body in the central brain are necessary and their plasticity is sufficient for a functional spatial orientation memory in flies. We also find that the protein kinase S6KII (ignorant) is required in a distinct subset of ring neurons to display this memory. Conditional expression of S6KII in these neurons only in adults can restore the loss of the orientation memory of the ignorant mutant. The S6KII signalling pathway therefore seems to be acutely required in the ring neurons for spatial orientation memory in flies.

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

    Directory of Open Access Journals (Sweden)

    Jianhua Ni

    2016-08-01

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

  18. Spatial pattern characteristics of water footprint for maize production in Northeast China.

    Science.gov (United States)

    Duan, Peili; Qin, Lijie; Wang, Yeqiao; He, Hongshi

    2016-01-30

    Water footprint (WF) methodology is essential for quantifying total water consumption of crop production and making efficient water management policies. This study calculated the green, blue, grey and total WFs of maize production in Northeast China from 1998 to 2012 and compared the values of the provinces. This study also analyzed the spatial variation and structure characteristics of the WFs at the prefecture level. The annual average WF of maize production was 1029 m(3) per ton, which was 51% green, 21% blue and 28% grey. The WF of maize production was highest in Liaoning Province, moderate in Heilongjiang Province and lowest in Jilin Province. The spatial differences of the WFs calculated for the 36 major maize production prefectures were significant in Northeast China. There was a moderate positive spatial autocorrelation among prefectures that had similar WFs. Local indicator of spatial autocorrelation index (LISA) analysis identified prefectures with higher WFs in the southeast region of Liaoning Province and the southwest region of Heilongjiang Province and prefectures with lower WFs in the middle of Jilin Province. Spatial differences in the WF of maize production were caused mainly by variations in climate conditions, soil quality, irrigation facilities and maize yield. The spatial distribution of WFs can help provide a scientific basis for optimizing maize production distribution and then formulate strategies to reduce the WF of maize production. © 2015 Society of Chemical Industry.

  19. Regional Disparities in Education Attainment Level in the European Union: A Spatial Approach

    Directory of Open Access Journals (Sweden)

    Chocholatá Michaela

    2017-10-01

    Full Text Available This article deals with the analysis of education attainment level across the 252 NUTS 2 regions of the European Union (EU with consideration of the spatial aspect. Since the individual EU regions cannot be seen as isolated, the main aim of this article is to assess the impact of location on the education attainment level (percentage of population aged 25–64 with at least upper secondary education during the period 2007–2015, as well as to investigate the impact of regional growth 2014/2007 on the education attainment level in 2015. The spatial analysis proved the existence of positive spatial autocorrelation and persistence of disparities in education attainment level across EU regions during the analysed period. The results of econometric analysis confirmed the expected positive impact of economic growth on education attainment level as well as the necessity to incorporate the spatial dimension into the model.

  20. Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

    Science.gov (United States)

    Baek, Eun Kyeng; Ferron, John M

    2013-03-01

    Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.

  1. 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.

  2. CMEIAS-Aided Microscopy of the Spatial Ecology of Individual Bacterial Interactions Involving Cell-to-Cell Communication within Biofilms

    Directory of Open Access Journals (Sweden)

    Frank B. Dazzo

    2012-05-01

    Full Text Available This paper describes how the quantitative analytical tools of CMEIAS image analysis software can be used to investigate in situ microbial interactions involving cell-to-cell communication within biofilms. Various spatial pattern analyses applied to the data extracted from the 2-dimensional coordinate positioning of individual bacterial cells at single-cell resolution indicate that microbial colonization within natural biofilms is not a spatially random process, but rather involves strong positive interactions between communicating cells that influence their neighbors’ aggregated colonization behavior. Geostatistical analysis of the data provide statistically defendable estimates of the micrometer scale and interpolation maps of the spatial heterogeneity and local intensity at which these microbial interactions autocorrelate with their spatial patterns of distribution. Including in situ image analysis in cell communication studies fills an important gap in understanding the spatially dependent microbial ecophysiology that governs the intensity of biofilm colonization and its unique architecture.

  3. Wave packet autocorrelation functions for quantum hard-disk and hard-sphere billiards in the high-energy, diffraction regime.

    Science.gov (United States)

    Goussev, Arseni; Dorfman, J R

    2006-07-01

    We consider the time evolution of a wave packet representing a quantum particle moving in a geometrically open billiard that consists of a number of fixed hard-disk or hard-sphere scatterers. Using the technique of multiple collision expansions we provide a first-principle analytical calculation of the time-dependent autocorrelation function for the wave packet in the high-energy diffraction regime, in which the particle's de Broglie wavelength, while being small compared to the size of the scatterers, is large enough to prevent the formation of geometric shadow over distances of the order of the particle's free flight path. The hard-disk or hard-sphere scattering system must be sufficiently dilute in order for this high-energy diffraction regime to be achievable. Apart from the overall exponential decay, the autocorrelation function exhibits a generally complicated sequence of relatively strong peaks corresponding to partial revivals of the wave packet. Both the exponential decay (or escape) rate and the revival peak structure are predominantly determined by the underlying classical dynamics. A relation between the escape rate, and the Lyapunov exponents and Kolmogorov-Sinai entropy of the counterpart classical system, previously known for hard-disk billiards, is strengthened by generalization to three spatial dimensions. The results of the quantum mechanical calculation of the time-dependent autocorrelation function agree with predictions of the semiclassical periodic orbit theory.

  4. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

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

    Science.gov (United States)

    2012-05-10

    econometrics. A companion to theoretical econometrics, pages 310-330, 1988. [5] L. Anselin, J. Cohen, D. Cook, W. Gorr, and G. Tita . Spatial analyses...52] G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita . Self-exciting point process modeling of crime. Journal of the American...Systems, 9:462, 2010. [69] M. Short, P. Brantingham, A. Bertozzi, and G. Tita . Dissipation and displacement of hotspots in reaction-diffusion models

  6. Automated defect spatial signature analysis for semiconductor manufacturing process

    Science.gov (United States)

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

    1999-01-01

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

  7. Analog model for analysis of spatial instability of neutron flux

    International Nuclear Information System (INIS)

    Radanovic, Lj.

    1964-12-01

    The objective of this task was to develop a model for analysing spatial instability of the neutron flux and defining the optimum number and position of regulating rods. The developed model enables calculation of higher harmonics to be taken into account for each type of reactor, to define zones for regulation rods, position and number of points for detecting reactor state, and number and position of the regulating rods

  8. Using geographical semi-variogram method to quantify the difference between NO2 and PM2.5 spatial distribution characteristics in urban areas.

    Science.gov (United States)

    Song, Weize; Jia, Haifeng; Li, Zhilin; Tang, Deliang

    2018-08-01

    Urban air pollutant distribution is a concern in environmental and health studies. Particularly, the spatial distribution of NO 2 and PM 2.5 , which represent photochemical smog and haze pollution in urban areas, is of concern. This paper presents a study quantifying the seasonal differences between urban NO 2 and PM 2.5 distributions in Foshan, China. A geographical semi-variogram analysis was conducted to delineate the spatial variation in daily NO 2 and PM 2.5 concentrations. The data were collected from 38 sites in the government-operated monitoring network. The results showed that the total spatial variance of NO 2 is 38.5% higher than that of PM 2.5 . The random spatial variance of NO 2 was 1.6 times than that of PM 2.5 . The nugget effect (i.e., random to total spatial variance ratio) values of NO 2 and PM 2.5 were 29.7 and 20.9%, respectively. This indicates that urban NO 2 distribution was affected by both local and regional influencing factors, while urban PM 2.5 distribution was dominated by regional influencing factors. NO 2 had a larger seasonally averaged spatial autocorrelation distance (48km) than that of PM 2.5 (33km). The spatial range of NO 2 autocorrelation was larger in winter than the other seasons, and PM 2.5 has a smaller range of spatial autocorrelation in winter than the other seasons. Overall, the geographical semi-variogram analysis is a very effective method to enrich the understanding of NO 2 and PM 2.5 distributions. It can provide scientific evidences for the buffering radius selection of spatial predictors for land use regression models. It will also be beneficial for developing the targeted policies and measures to reduce NO 2 and PM 2.5 pollution levels. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Using catchment areas analysis and GIS based spatial analysis for prioritising spatial investment in non-metro South Africa

    CSIR Research Space (South Africa)

    Green, Chéri A

    2016-09-01

    Full Text Available for social facility provision. A geo-spatially targeted hierarchy of places was also identified to prioritise investment of regional middle order facilities in “Service Malls” located in the most optimal towns to best serve non-metropolitan areas in South...

  10. 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

  11. 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 (...

  12. Spatial Dependence of Crime in Monterrey, Mexico

    Directory of Open Access Journals (Sweden)

    Ernesto Aguayo Téllez

    2014-06-01

    Full Text Available This paper studies the impact that the characteristics of the environment have on crime using neighborhood aggregate data of the Monterrey Metropolitan Area for the year 2010. Data spatial autocorrelation is corroborated, i.e. neighborhoods with high crime rates have a positive impact on the crime rates of its surrounding neighborhoods. Once it was controlled through the bias caused by spatial autocorrelation and data censoring, it is evidenced that the likelihood of being a crime victim and the probability of becoming an offender is positively related to variables such as unemployment, the percentage of young men and the existence of schools, hospitals or markets in the neighborhood.

  13. Integrating Spatial and Attribute Characteristics of Extended Voronoi Diagrams in Spatial Patterning Research: A Case Study of Wuhan City in China

    Directory of Open Access Journals (Sweden)

    Zuohua Miao

    2016-07-01

    Full Text Available Rapid urbanization has caused numerous problems, and the urban spatial structure has been a hot topic in sustainable development management. Urban spatial structure is affected by a series of factors. Thus, the research model should synthetically consider the spatial and non-spatial relationship of every element. Here, we propose an extended Voronoi diagram for exploring the urban land spatial pattern. In essence, we first used a principal component analysis method to construct attribute evaluation indicators and obtained the attribute distance for each indicator. Second, we integrated spatial and attribute distances to extend the comparison distance for Voronoi diagrams, and then, we constructed the Voronoi aggregative homogeneous map of the study area. Finally, we make a spatial autocorrelation analysis by using GeoDA and SPSS software. Results show that: (1 the residential land cover aggregation is not significant, but spatial diffusion is obvious; (2 the commercial land cover aggregation is considerable; and (3 the spatial agglomeration degree of the industrial land cover is increased and mainly located in urban fringes. According to the neo-Marxist theory, we briefly analyzed the driving forces for shaping the urban spatial structure. To summarize, our approach yields important insights into the urban spatial structure characterized by attribute similarity with geospatial proximity, which contributes to a better understanding of the urban growth mechanism. In addition, it explicitly identifies ongoing urban transformations, potentially supporting the planning for sustainable urban land use and protection.

  14. 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)

  15. 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.

  16. Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.

    Science.gov (United States)

    Fleming, C H; Fagan, W F; Mueller, T; Olson, K A; Leimgruber, P; Calabrese, J M

    2015-05-01

    Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.

  17. 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)

  18. 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.

  19. Perceptual interaction between carrier periodicity and amplitude modulation in broadband stimuli: A comparison of the autocorrelation and modulation-filterbank model

    DEFF Research Database (Denmark)

    Stein, A.; Ewert, Stephan; Wiegrebe, L.

    2005-01-01

    , autocorrelation is applied. Considering the large overlap in pitch and modulation perception, this is not parsimonious. Two experiments are presented to investigate the interaction between carrier periodicity, which produces strong pitch sensations, and envelope periodicity using broadband stimuli. Results show......Recent temporal models of pitch and amplitude modulation perception converge on a relatively realistic implementation of cochlear processing followed by a temporal analysis of periodicity. However, for modulation perception, a modulation filterbank is applied whereas for pitch perception...

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

    Science.gov (United States)

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

    2009-02-01

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

  1. Spectral Velocity Estimation using the Autocorrelation Function and Sparse data Sequences

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2005-01-01

    Ultrasound scanners can be used for displaying the distribution of velocities in blood vessels by finding the power spectrum of the received signal. It is desired to show a B-mode image for orientation and data for this has to be acquired interleaved with the flow data. Techniques for maintaining...... both the B-mode frame rate, and at the same time have the highest possible $f_{prf}$ only limited by the depth of investigation, are, thus, of great interest. The power spectrum can be calculated from the Fourier transform of the autocorrelation function $R_r(k)$. The lag $k$ corresponds...... of the sequence. The audio signal has also been synthesized from the autocorrelation data by passing white, Gaussian noise through a filter designed from the power spectrum of the autocorrelation function. The results show that both the full velocity range can be maintained at the same time as a B-mode image...

  2. Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

    Science.gov (United States)

    Ren, Shengwei; Zhang, Li; Zhang, Shibing

    2016-10-01

    Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

  3. 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.

  4. 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...

  5. [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.

  6. 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

  7. 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.

  8. Sum rule and hydrodynamic analyses of the velocity autocorrelation function in strongly coupled plasmas

    International Nuclear Information System (INIS)

    Nagano, Seido; Ichimaru, Setsuo

    1980-01-01

    The memory function for the velocity autocorrelation function in a strongly coupled, one-component plasma is analyzed in the short time and long time domains, respectively, with the aid of the frequency-moment sum rules and the hydrodynamic consideration evoking the idea of the generalized Stokes friction. A series of interpolation schemes with successively improved accuracies are then introduced. Numerical investigations of those interpolation schemes clarify the physical origin of the three different types of the velocity autocorrelation function observed in the molecular dynamics simulation at different regimes of the coupling constant. (author)

  9. Area-to-Area Poisson Kriging and Spatial Bayesian Analysis

    Science.gov (United States)

    Asmarian, Naeimehossadat; Jafari-Koshki, Tohid; Soleimani, Ali; Taghi Ayatollahi, Seyyed Mohammad

    2016-10-01

    Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Areato- area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran. Creative Commons Attribution License

  10. Spatial and temporal analysis of lake sedimentation under reforestation

    Directory of Open Access Journals (Sweden)

    C.M. Pilgrim

    2015-10-01

    Full Text Available Spatial and temporal land cover changes can reduce or accelerate lake sedimentation. This study was conducted to examine morphometry and bathymetry, and the long-term changes (over 75 years in sedimentation in the Lake Issaqueena reservoir, South Carolina. The watershed and catchment areas were delineated using Light Detection and Ranging (LiDAR based data. Trends in lake surface area and riparian buffer condition (vegetated or unvegetated were determined from historical aerial photography. From 1938 to 2009, the lake experienced a decrease in surface area of approximately 11.33 ha while catchment area increased by 6.99 ha, and lake volume decreased by 320,800.00 m3. Lake surface area decreased in years corresponding to equal coverage or largely unvegetated riparian buffers. Surface area and average annual precipitation were not correlated; therefore other factors such as soil type, riparian buffer condition and changes in land use likely contributed to sedimentation. Shift from agricultural land to forestland in this watershed resulted in a decrease in sedimentation rates by 88.28%. Keywords: Bathymetry, Erosion, Geographic Information Systems (GIS, Land cover, Riparian buffer, Soils

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

    Science.gov (United States)

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

    2013-11-01

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

  12. 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

  13. Problems in implementation of the spatial plan of the Republic of Srpska until 2015: Quantitative analysis

    Directory of Open Access Journals (Sweden)

    Bijelić Branislav

    2017-01-01

    Full Text Available The implementation of spatial plans in the Republic of Srpska is certainly the weakest phase of the process of spatial planning in this entity. It is particularly evident in the case of the Spatial Plan of the Republic of Srpska until 2015 which is the highest strategic spatial planning document in the Republic of Srpska. More precisely, the implementation of spatial plans has been defined as the carrying out of spatial planning documents, i.e. planning propositions as defined in the spatial plans. For the purpose of this paper, a quantitative analysis of the implementation of the planning propositions envisioned by this document has been carried out. The difference between what was planned and what was implemented at the end of the planning period (ex-post evaluation of planning decisions is presented in this paper. The weighting factor is defined for each thematic field and planning proposition, where the main criterion for determining the weighting factor is the share of the planning proposition and thematic field in the estimated total costs of the plan (financial criterion. The paper has also tackled the issue of the implementation of the Spatial Plan of Bosnia and Herzegovina for the period 1981 - 2000, as well as of the Spatial Plan of the Republic of Srpska 1996 - 2001 - Phased Plan for the period 1996 - 2001, as the previous strategic spatial planning documents of the highest rank covering the area of the Republic of Srpska. The research results have proven primary hypothesis of the paper that the level of the implementation of Spatial Plan of the Republic of Srpska until 2015 is less than 10%.

  14. Spatial analysis of bus transport networks using network theory

    Science.gov (United States)

    Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

    2018-07-01

    In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

  15. 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.

  16. Error propagation in spatial modeling of public health data: a simulation approach using pediatric blood lead level data for Syracuse, New York.

    Science.gov (United States)

    Lee, Monghyeon; Chun, Yongwan; Griffith, Daniel A

    2018-04-01

    Lead poisoning produces serious health problems, which are worse when a victim is younger. The US government and society have tried to prevent lead poisoning, especially since the 1970s; however, lead exposure remains prevalent. Lead poisoning analyses frequently use georeferenced blood lead level data. Like other types of data, these spatial data may contain uncertainties, such as location and attribute measurement errors, which can propagate to analysis results. For this paper, simulation experiments are employed to investigate how selected uncertainties impact regression analyses of blood lead level data in Syracuse, New York. In these simulations, location error and attribute measurement error, as well as a combination of these two errors, are embedded into the original data, and then these data are aggregated into census block group and census tract polygons. These aggregated data are analyzed with regression techniques, and comparisons are reported between the regression coefficients and their standard errors for the error added simulation results and the original results. To account for spatial autocorrelation, the eigenvector spatial filtering method and spatial autoregressive specifications are utilized with linear and generalized linear models. Our findings confirm that location error has more of an impact on the differences than does attribute measurement error, and show that the combined error leads to the greatest deviations. Location error simulation results show that smaller administrative units experience more of a location error impact, and, interestingly, coefficients and standard errors deviate more from their true values for a variable with a low level of spatial autocorrelation. These results imply that uncertainty, especially location error, has a considerable impact on the reliability of spatial analysis results for public health data, and that the level of spatial autocorrelation in a variable also has an impact on modeling results.

  17. 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

  18. 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...

  19. Analysis of spatial thermal field in a magnetic bearing

    Science.gov (United States)

    Wajnert, Dawid; Tomczuk, Bronisław

    2018-03-01

    This paper presents two mathematical models for temperature field analysis in a new hybrid magnetic bearing. Temperature distributions have been calculated using a three dimensional simulation and a two dimensional one. A physical model for temperature testing in the magnetic bearing has been developed. Some results obtained from computer simulations were compared with measurements.

  20. Spatial Analysis of Human Exposure and Vulnerability to Coastal ...

    African Journals Online (AJOL)

    Disasters in coastal cities have shown an ever-increasing frequency of occurrence. Population growth and urbanisation have increased the vulnerability of properties and societies in coastal flood-prone areas. Analysis of human exposure and vulnerability is one of the main strategies used to determine the necessary ...

  1. 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.

  2. Spatial analysis of elderly access to primary care services

    Directory of Open Access Journals (Sweden)

    Lozano-Gracia Nancy

    2006-05-01

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

  3. An exploratory spatial analysis of social vulnerability and smoke plum dispersion in the U.S

    Science.gov (United States)

    Cassandra Johnson Gaither; Scott Goodrick; Bryn Elise Murphy; Neelam Poudyal

    2015-01-01

    This study explores the spatial association between social vulnerability and smoke plume dispersion at the census block group level for the 13 southern states in the USDA Forest Service’s Region 8. Using environmental justice as a conceptual basis, we use Exploratory Spatial Data Analysis to identify clusters or “hot spots” for the incidence of both higher than average...

  4. 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)

  5. 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...

  6. Uplink Interference Analysis for Two-tier Cellular Networks with Diverse Users under Random Spatial Patterns

    OpenAIRE

    Bao, Wei; Liang, Ben

    2013-01-01

    Multi-tier architecture improves the spatial reuse of radio spectrum in cellular networks, but it introduces complicated heterogeneity in the spatial distribution of transmitters, which brings new challenges in interference analysis. In this work, we present a stochastic geometric model to evaluate the uplink interference in a two-tier network considering multi-type users and base stations. Each type of tier-1 users and tier-2 base stations are modeled as independent homogeneous Poisson point...

  7. Spatial Heterogeneity of Sustainable Transportation Offer Values: A Comparative Analysis of Nantes Urban and Periurban/Rural Areas (France

    Directory of Open Access Journals (Sweden)

    Julie Bulteau

    2018-02-01

    Full Text Available Innovative solutions have been implemented to promote sustainable mobility in urban areas. In the Nantes area (northwestern part of France, alternatives to single-occupant car use have increased in the past few years. In the urban area, there is an efficient public transport supply, including tramways and a “busway” (Bus Rapid Transit, as well as bike-sharing services. In periurban and rural areas, there are carpool areas, regional buses and the new “tram-train” lines. In this article, we focus on the impact on house prices of these “sustainable” transportation infrastructures and policies, in order to evaluate their values. The implicit price of these sustainable transport offers was estimated through hedonic price functions describing the Nantes urban and periurban/rural housing markets. Spatial regression models (SAR, SEM, SDM and GWR were carried out to capture the effect of both spatial autocorrelation and spatial heterogeneity. The results show patterns of spatial heterogeneity of transportation offer implicit prices at two scales: (i between urban and periurban/rural areas, as well as (ii within each territory. In the urban area, the distance to such offers was significantly associated with house prices. These associations varied by type of transportation system (positive for tramway and railway stations and negative for bike-sharing stations. In periurban and rural areas, having a carpool area in a 1500-m buffer around the home was negatively associated with house prices, while having a regional bus station in a 500-m buffer was non-significant. Distance to the nearest railway station was negatively associated with house prices. These findings provide research avenues to help public policy-makers promote sustainable mobility and pave the way for more locally targeted interventions.

  8. Spatial Characterization of Landscapes through Multifractal Analysis of DEM

    Directory of Open Access Journals (Sweden)

    P. L. Aguado

    2014-01-01

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

  9. Robustness of variance and autocorrelation as indicators of critical slowing down

    NARCIS (Netherlands)

    Dakos, V.; Nes, van E.H.; Odorico, D' P.; Scheffer, M.

    2012-01-01

    Ecosystems close to a critical threshold lose resilience, in the sense that perturbations can more easily push them into an alternative state. Recently, it has been proposed that such loss of resilience may be detected from elevated autocorrelation and variance in the fluctuations of the state of an

  10. Partial autocorrelation functions of the fractional ARIMA processes with negative degree of differencing

    OpenAIRE

    Inoue, Akihiko; Kasahara, Yukio

    2004-01-01

    Let {Xn : ∈Z} be a fractional ARIMA(p,d,q) process with partial autocorrelation function α(·). In this paper, we prove that if d∈(−1/2,0) then |α(n)|~|d|/n as n→∞. This extends the previous result for the case 0

  11. Limit theory for the sample autocorrelations and extremes of a GARCH (1,1) process

    NARCIS (Netherlands)

    Mikosch, T; Starica, C

    2000-01-01

    The asymptotic theory for the sample autocorrelations and extremes of a GARCH(I, 1) process is provided. Special attention is given to the case when the sum of the ARCH and GARCH parameters is close to 1, that is, when one is close to an infinite Variance marginal distribution. This situation has

  12. Operator theory of angular momentum nad orientational auto-correlation functions

    International Nuclear Information System (INIS)

    Evans, M.W.

    1982-01-01

    The rigorous relation between the orientational auto-correlation function and the angular momentum autocorrelation function is described in two cases of interest. First when description of the complete zero THz- spectrum is required from the Mori continued fraction expansion for the angular momentum autocorrelation function and second when rotation/translation effects are important. The Mori-Evans theory of 1976, relying on the simple Shimizu relation is found to be essentially unaffected by the higher order corrections recently worked out by Ford and co-workers in the Markov limit. The mutual interaction of rotation and translation is important in determining the details of both the orientational and angular momentum auto-correlation function's (a.c.f.'s) in the presence of sample anisotropy or a symmetry breaking field. In this case it is essential to regard the angular momentum a.c.f. as non-Markovian and methods are developed to relate this to the orientational a.c.f. in the presence of rotation/translation coupling. (author)

  13. A simulation-based approach to capturing auto-correlated demand parameter uncertainty in inventory management

    NARCIS (Netherlands)

    Akçay, A.E.; Biller, B.; Tayur, S.

    2012-01-01

    We consider a repeated newsvendor setting where the parameters of the demand distribution are unknown, and we study the problem of setting inventory targets using only a limited amount of historical demand data. We assume that the demand process is autocorrelated and represented by an

  14. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  15. Velocity-Autocorrelation Function in Liquids, Deduced from Neutron Incoherent Scattering Results

    DEFF Research Database (Denmark)

    Carneiro, Kim

    1976-01-01

    The Fourier transform p(ω) of the velocity-autocorrelation function is derived from neutron incoherent scattering results, obtained from the two liquids Ar and H2. The quality and significance of the results are discussed with special emphasis on the long-time t-3/2 tail, found in computer simula...

  16. 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.

  17. 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

  18. 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

  19. Spatial Analysis of Linear Structures in the Exploration of Groundwater

    Directory of Open Access Journals (Sweden)

    Abdramane Dembele

    2017-11-01

    Full Text Available The analysis of linear structures on major geological formations plays a crucial role in resource exploration in the Inner Niger Delta. Highlighting and mapping of the large lithological units were carried out using image fusion, spectral bands (RGB coding, Principal Component Analysis (PCA, and band ratio methods. The automatic extraction method of linear structures has permitted the obtaining of a structural map with 82,659 linear structures, distributed on different stratigraphic stages. The intensity study shows an accentuation in density over 12.52% of the total area, containing 22.02% of the linear structures. The density and nodes (intersections of fractures formed by the linear structures on the different lithologies allowed to observe the behavior of the region’s aquifers in the exploration of subsoil resources. The central density, in relation to the hydrographic network of the lowlands, shows the conditioning of the flow and retention of groundwater in the region, and in-depth fluids. The node areas and high-density linear structures, have shown an ability to have rejections in deep (pores that favor the formation of structural traps for oil resources.

  20. 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)

  1. Spatial Analysis and Safety Assessment of Social and Economic Development of Small and Medium Cities

    Directory of Open Access Journals (Sweden)

    Elena Anatolyevna Orekhova

    2016-12-01

    Full Text Available The article discusses the spatial patterns of socio-economic development of small and medium-sized cities in the Volgograd region. We know that small and medium-sized cities as spatial socio-economic systems are not only the support frame of settlement, but the main “engine” of innovative impulses for the surrounding periphery. The scientific novelty of the study consists in the effort to implement a spatial approach to the assessment of the economic security of small and medium-sized cities (SCR. The content of the economic security of cities is determined by two system characteristics of the socio-economic system: economic activity (EA and quality of life (QL of the urban population, or SCR = F (EA; QL. For finding spatial patterns in GIS, great interest is in investigating the environment of each city by calculating the local statistical characteristics of geo-variability which allow assessing trends of spatial variation of the six components of security (human security, technosphere safety, environmental safety, etc., local variations in emissions and their values indicators Ki. The successful solution of these problems is possible with the use of tools of exploratory spatial data analysis (ESDA in ARCGIS, and in particular, the Voronoy maps. The spatial approach has allowed to perform an integrated assessment of the economic security and to evaluate safety risks in small and medium-sized cities of the Volgograd region with the security system of indicators.

  2. Spatial and temporal analysis of dry spells in Greece

    Science.gov (United States)

    Anagnostopoulou, Chr.; Maheras, P.; Karacostas, T.; Vafiadis, M.

    A spatio-temporal analysis of the dry spells that occur in the Greek area is carried out for an extended period of 40 years (1958-1997). The dry spells can be defined as a number of consecutive days with no rain. The number of days defines the length of the dry spells. The longest spells are identified in central (Cyclades) and the south-east Aegean Sea whereas dry spells with the minimum length are shown over the north-west of the Greek area that reflects the significance of the latitude and the topography. Negative Binomial Distribution and Markov Chains of second order have been used to fit the duration of the dry spells of different lengths. The study of the seasonal and annual distribution of the frequency of occurrence of dry spells revealed that the dry spells in Greece depict a seasonal character, while medium and long sequences are associated with the duration and hazards of drought.

  3. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  4. Application of Spatial Regression Models to Income Poverty Ratios in Middle Delta Contiguous Counties in Egypt

    Directory of Open Access Journals (Sweden)

    Sohair F Higazi

    2013-02-01

    Full Text Available Regression analysis depends on several assumptions that have to be satisfied. A major assumption that is never satisfied when variables are from contiguous observations is the independence of error terms. Spatial analysis treated the violation of that assumption by two derived models that put contiguity of observations into consideration. Data used are from Egypt's 2006 latest census, for 93 counties in middle delta seven adjacent Governorates. The dependent variable used is the percent of individuals classified as poor (those who make less than 1$ daily. Predictors are some demographic indicators. Explanatory Spatial Data Analysis (ESDA is performed to examine the existence of spatial clustering and spatial autocorrelation between neighboring counties. The ESDA revealed spatial clusters and spatial correlation between locations. Three statistical models are applied to the data, the Ordinary Least Square regression model (OLS, the Spatial Error Model (SEM and the Spatial Lag Model (SLM.The Likelihood Ratio test and some information criterions are used to compare SLM and SEM to OLS. The SEM model proved to be better than the SLM model. Recommendations are drawn regarding the two spatial models used.

  5. Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

    Science.gov (United States)

    Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

    2016-01-01

    Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

  6. Investigation of the marked and long-standing spatial inhomogeneity of the Hungarian suicide rate: a spatial regression approach.

    Science.gov (United States)

    Balint, Lajos; Dome, Peter; Daroczi, Gergely; Gonda, Xenia; Rihmer, Zoltan

    2014-02-01

    In the last century Hungary had astonishingly high suicide rates characterized by marked regional within-country inequalities, a spatial pattern which has been quite stable over time. To explain the above phenomenon at the level of micro-regions (n=175) in the period between 2005 and 2011. Our dependent variable was the age and gender standardized mortality ratio (SMR) for suicide while explanatory variables were factors which are supposed to influence suicide risk, such as measures of religious and political integration, travel time accessibility of psychiatric services, alcohol consumption, unemployment and disability pensionery. When applying the ordinary least squared regression model, the residuals were found to be spatially autocorrelated, which indicates the violation of the assumption on the independence of error terms and - accordingly - the necessity of application of a spatial autoregressive (SAR) model to handle this problem. According to our calculations the SARlag model was a better way (versus the SARerr model) of addressing the problem of spatial autocorrelation, furthermore its substantive meaning is more convenient. SMR was significantly associated with the "political integration" variable in a negative and with "lack of religious integration" and "disability pensionery" variables in a positive manner. Associations were not significant for the remaining explanatory variables. Several important psychiatric variables were not available at the level of micro-regions. We conducted our analysis on aggregate data. Our results may draw attention to the relevance and abiding validity of the classic Durkheimian suicide risk factors - such as lack of social integration - apropos of the spatial pattern of Hungarian suicides. © 2013 Published by Elsevier B.V.

  7. 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.

  8. Neural activity associated with metaphor comprehension: spatial analysis.

    Science.gov (United States)

    Sotillo, María; Carretié, Luis; Hinojosa, José A; Tapia, Manuel; Mercado, Francisco; López-Martín, Sara; Albert, Jacobo

    2005-01-03

    Though neuropsychological data indicate that the right hemisphere (RH) plays a major role in metaphor processing, other studies suggest that, at least during some phases of this processing, a RH advantage may not exist. The present study explores, through a temporally agile neural signal--the event-related potentials (ERPs)--, and through source-localization algorithms applied to ERP recordings, whether the crucial phase of metaphor comprehension presents or not a RH advantage. Participants (n=24) were submitted to a S1-S2 experimental paradigm. S1 consisted of visually presented metaphoric sentences (e.g., "Green lung of the city"), followed by S2, which consisted of words that could (i.e., "Park") or could not (i.e., "Semaphore") be defined by S1. ERPs elicited by S2 were analyzed using temporal principal component analysis (tPCA) and source-localization algorithms. These analyses revealed that metaphorically related S2 words showed significantly higher N400 amplitudes than non-related S2 words. Source-localization algorithms showed differential activity between the two S2 conditions in the right middle/superior temporal areas. These results support the existence of an important RH contribution to (at least) one phase of metaphor processing and, furthermore, implicate the temporal cortex with respect to that contribution.

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

    Science.gov (United States)

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

    2016-11-01

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

  10. Is analysis of biological materials with nm spatial resolution possible?

    International Nuclear Information System (INIS)

    Warley, Alice

    2006-01-01

    Cells are bounded by a membrane, the plasma membrane, subcompartments within cells are also delineated by membranes, these membranes contain transporters that regulate the flow of ions across them. Fluxes of ions across the membranes underlie many of the basic properties of living material such as excitability and movement. Breakdown of membrane function ultimately leads to cell death. EM microanalysis has been instrumental in gaining understanding of how changes in element distribution affect cell behaviour and cell survival. The main problem that biologists face in undertaking such studies is that of specimen preparation. Cells consist mainly of water that needs to be either removed or stabilised before analysis can take place. Cryotechniques, fixation by rapid freezing followed by sectioning at low temperatures and freeze-drying of the sections have proved to be a reliable method for the study of intracellular element concentrations. These techniques have been used to show that elements are confined in different compartments within cells and produced results to support a new theory on the mechanism by which neutrophils kill bacteria. They have also shown that disturbance of the ionic content of mitochondria is one of the first signs in the pathway to cell death

  11. Promotional archipelagoes of change. Spatial analysis of Dinosauro

    International Nuclear Information System (INIS)

    Fratini, Noemi; Nieto, Silvia

    2009-01-01

    During the last decades, the post industrial Latin American cities have become important economic centers in the world. Their integration into the world economy helped those cities become in the favorite places for the linking functions and activities to the world nets of commerce, productions culture, etc. These urban centers which are expanding gradually into segmented developing areas have caused an apparent space duality between the private and public activities as it can be seen though the differential access to goods and services by the society. At present, there has been an increase in cultural activities which form change promoting archipelagoes subject to several dimensions of analysis. The inequity in the distribution of economic and educational resources causes unequal ways of access to consumption of these areas of cultural production, and of goods and services, what gives place to situations of social exclusion and inclusion. To understand this fact related to money behavior, we have selected an area situated in the northwest of Cordoba capital city, in Argentina, which is a shopping mall called Dinosaurio Group. In this essay we present an exploration into the conflicts caused to the cities through the expansion of the segmented urban centers, promoters of change, and its relationship with the public and private space.

  12. Spatial Analysis of Macro Economic in Central Java (PDRB Analysis in Year 1993-2003

    Directory of Open Access Journals (Sweden)

    Eddy Kiswanto

    2016-12-01

    Full Text Available This paper aims to study the spatial analysis macroeconomics condition in central Java from 1993-2001 base on PDRB analysis. Central Java stands in the last position in the economic in Central Java based on PDRB variable and economic growth is in the lowest category in the comparation with another provinces in Java. This is reason why Central Java is categorized as "LL" (Low low. One of the prime sectors in Central Java is small medium scale enterprises which is dominated 30% of national market, but since the economic crisis stroke in 1997 the manufacture sector, especially industry and processing had collapse. In 1996-1997, the level of manufacture growth increased to 14.4% but then decreased until minus 19.3%. This condition caused by bankruptcy to many of the industries. The poverty profile in Central Java from 1999-2003 is average 23.3% from the total population every years. Central Java stepping to number 2 in level of poverty absolute number 1. In poverty relativity level, Central Java became number 1 in Java from 2002-2003 with the level of poverty reached above the national average. This fact shows the unsuccessfully effort in reducing the poverty level.

  13. 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.

  14. Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

    Science.gov (United States)

    Franklin, Rima B.; Mills, Aaron L.

    2003-01-01

    To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

  15. 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.

  16. 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.

  17. A Change Oriented Extension of EOF Analysis Applied to the 1996-1997 AVHRR Sea Surface Temperature Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut; Andersen, Ole Baltazar

    2002-01-01

    correlation analysis, and maximum autocorrelation factors (MAFs). The method described can be considered as an extension to EOF analysis that is specially tailored for change detection in spatial data since it first maximises differences in the data between two points in time and then maximises...... autocorrelation between neighbouring observations. The results show that the large scale ocean events associated with the El Nino/Southern Oscillation (ENSO) related changes are concentrated in the first SST MAF/MAD mode and the two first SSH MAF/MAD modes. The MAD/MAF analysis also revealed a spatially...... correlated structure in the Western Mediterranean Sea that turned out to be related to a strong semi-annual variation in the SST for 1997 which was difficult to resolve from a traditional principal component analysis....

  18. 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)

  19. 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.

  20. Autocorrelation studies of the arrival directions of UHECRs measured by the surface detector of the Pierre Auger Observatory

    Energy Technology Data Exchange (ETDEWEB)

    Schulte, Stephan

    2011-07-11

    The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km{sup 2}. In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each

  1. Autocorrelation studies of the arrival directions of UHECRs measured by the surface detector of the Pierre Auger Observatory

    International Nuclear Information System (INIS)

    Schulte, Stephan

    2011-01-01

    The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km 2 . In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each

  2. 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.

  3. 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.

  4. Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

    Science.gov (United States)

    Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

    2014-03-01

    Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

  5. 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.

  6. 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.

  7. Lead Emissions and Population Vulnerability in the Detroit (Michigan, USA Metropolitan Area, 2006–2013: A Spatial and Temporal Analysis

    Directory of Open Access Journals (Sweden)

    Heather Moody

    2017-11-01

    Full Text Available Objective: The purpose of this research is to geographically model airborne lead emission concentrations and total lead deposition in the Detroit Metropolitan Area (DMA from 2006 to 2013. Further, this study characterizes the racial and socioeconomic composition of recipient neighborhoods and estimates the potential for IQ (Intelligence Quotient loss of children residing there. Methods: Lead emissions were modeled from emitting facilities in the DMA using AERMOD (American Meteorological Society/Environmental Protection Agency Regulatory Model. Multilevel modeling was used to estimate local racial residential segregation, controlling for poverty. Global Moran’s I bivariate spatial autocorrelation statistics were used to assess modeled emissions with increasing segregation. Results: Lead emitting facilities were primarily located in, and moving to, highly black segregated neighborhoods regardless of poverty levels—a phenomenon known as environmental injustice. The findings from this research showed three years of elevated airborne emission concentrations in these neighborhoods to equate to a predicted 1.0 to 3.0 reduction in IQ points for children living there. Across the DMA there are many areas where annual lead deposition was substantially higher than recommended for aquatic (rivers, lakes, etc. and terrestrial (forests, dunes, etc. ecosystems. These lead levels result in decreased reproductive and growth rates in plants and animals, and neurological deficits in vertebrates. Conclusions: This lead-hazard and neighborhood context assessment will inform future childhood lead exposure studies and potential health consequences in the DMA.

  8. Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

    Science.gov (United States)

    Krawczyk, Christopher; Gradziel, Pat; Geraghty, Estella M.

    2014-01-01

    Objectives. We used a geographic information system and cluster analyses to determine locations in need of enhanced Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program services. Methods. We linked documented births in the 2010 California Birth Statistical Master File with the 2010 data from the WIC Integrated Statewide Information System. Analyses focused on the density of pregnant women who were eligible for but not receiving WIC services in California’s 7049 census tracts. We used incremental spatial autocorrelation and hot spot analyses to identify clusters of WIC-eligible nonparticipants. Results. We detected clusters of census tracts with higher-than-expected densities, compared with the state mean density of WIC-eligible nonparticipants, in 21 of 58 (36.2%) California counties (P Hot spot analyses provided a rigorous and objective approach to determine the locations of statistically significant clusters of WIC-eligible nonparticipants. Results helped inform WIC program and funding decisions, including the opening of new WIC centers, and offered a novel approach for targeting public health services. PMID:24354821

  9. Lead Emissions and Population Vulnerability in the Detroit (Michigan, USA) Metropolitan Area, 2006-2013: A Spatial and Temporal Analysis.

    Science.gov (United States)

    Moody, Heather; Grady, Sue C

    2017-11-23

    Objective : The purpose of this research is to geographically model airborne lead emission concentrations and total lead deposition in the Detroit Metropolitan Area (DMA) from 2006 to 2013. Further, this study characterizes the racial and socioeconomic composition of recipient neighborhoods and estimates the potential for IQ (Intelligence Quotient) loss of children residing there. Methods : Lead emissions were modeled from emitting facilities in the DMA using AERMOD (American Meteorological Society/Environmental Protection Agency Regulatory Model). Multilevel modeling was used to estimate local racial residential segregation, controlling for poverty. Global Moran's I bivariate spatial autocorrelation statistics were used to assess modeled emissions with increasing segregation. Results : Lead emitting facilities were primarily located in, and moving to, highly black segregated neighborhoods regardless of poverty levels-a phenomenon known as environmental injustice. The findings from this research showed three years of elevated airborne emission concentrations in these neighborhoods to equate to a predicted 1.0 to 3.0 reduction in IQ points for children living there. Across the DMA there are many areas where annual lead deposition was substantially higher than recommended for aquatic (rivers, lakes, etc.) and terrestrial (forests, dunes, etc.) ecosystems. These lead levels result in decreased reproductive and growth rates in plants and animals, and neurological deficits in vertebrates. Conclusions : This lead-hazard and neighborhood context assessment will inform future childhood lead exposure studies and potential health consequences in the DMA.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. A Bayesian multidimensional scaling procedure for the spatial analysis of revealed choice data

    NARCIS (Netherlands)

    DeSarbo, WS; Kim, Y; Fong, D

    1999-01-01

    We present a new Bayesian formulation of a vector multidimensional scaling procedure for the spatial analysis of binary choice data. The Gibbs sampler is gainfully employed to estimate the posterior distribution of the specified scalar products, bilinear model parameters. The computational procedure

  16. 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

  17. Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change

    Science.gov (United States)

    Wang, Ninghua Nathan

    2013-01-01

    Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…

  18. Spatial analysis of fuel treatment options for chaparral on the Angeles national forest

    Science.gov (United States)

    G. Jones; J. Chew; R. Silverstein; C. Stalling; J. Sullivan; J. Troutwine; D. Weise; D. Garwood

    2008-01-01

    Spatial fuel treatment schedules were developed for the chaparral vegetation type on the Angeles National Forest using the Multi-resource Analysis and Geographic Information System (MAGIS). Schedules varied by the priority given to various wildland urban interface areas and the general forest, as well as by the number of acres treated per decade. The effectiveness of...

  19. Gender, Space, and the Location Changes of Jobs and People : A Spatial Simultaneous Equations Analysis

    NARCIS (Netherlands)

    Hoogstra, Gerke J.

    This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes

  20. 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

  1. Spatial Spread of the Root Parasitic Weed Phelipanche aegyptiaca in Processing Tomatoes by Using Ecoinformatics and Spatial Analysis.

    Science.gov (United States)

    Cohen, Yafit; Roei, Itai; Blank, Lior; Goldshtein, Eitan; Eizenberg, Hanan

    2017-01-01

    Egyptian broomrape ( Phelipanche aegyptiaca ) is one of the main threats to tomato production in Israel. The seed bank of P. aegyptiaca rapidly develops and spreads in the field. Knowledge about the spatio-temporal distribution of such weeds is required in advance of emergence, as they emerge late in their life cycle when they have already caused major crop damage. The aim of this study is to reveal the effects of two major internal infestation sources: crop rotation and infestation history; and one external source: proximity to infested tomato fields; on infestation of P. aegyptiaca in processing tomatoes. Ecoinformatics, spatial analysis and geostatistics were used to examine these effects. A regional survey was conducted to collect data on field history from 238 tomato fields between 2000 and 2012, in a major tomato-growing region in Israel. Multivariate logistic regression in the framework of generalized linear models (GLM) has demonstrated the importance of all three variables in predicting infestation in tomato fields. The parameters of the overall model indicated a high specificity between tomatoes and P. aegyptiaca , which is potentially responsible for aggravating infestation. In addition, P. aegyptiaca infestation levels were intensively mapped in 43 of the 238 tomato fields in the years 2010-2012. Geostatistical measures showed that 40% of the fields had clustered infestation spatial patterns with infestation clusters located along the fields' borders. Strong linear and negative relationships were found between infestation level and distance from a neighboring infested field, strengthening the role of infested tomato fields in P. aegyptiaca spread. An experiment specifically designed for this study showed that during harvest, P. aegyptiaca seeds are blown from an infested field to a distance of at least 90 m, and may initiate infestation in neighboring fields. Integrating current knowledge about the role of agricultural practices on the spread of P

  2. Autocorrelation as a source of truncated Lévy flights in foreign exchange rates

    Science.gov (United States)

    Figueiredo, Annibal; Gleria, Iram; Matsushita, Raul; Da Silva, Sergio

    2003-05-01

    We suggest that the ultraslow speed of convergence associated with truncated Lévy flights (Phys. Rev. Lett. 73 (1994) 2946) may well be explained by autocorrelations in data. We show how a particular type of autocorrelation generates power laws consistent with a truncated Lévy flight. Stock exchanges have been suggested to be modeled by a truncated Lévy flight (Nature 376 (1995) 46; Physica A 297 (2001) 509; Econom. Bull. 7 (2002) 1). Here foreign exchange rate data are taken instead. Scaling power laws in the “probability of return to the origin” are shown to emerge for most currencies. A novel approach to measure how distant a process is from a Gaussian regime is presented.

  3. Effect of nonlinear crystal thickness on the parameters of the autocorrelator of femtosecond light pulses

    International Nuclear Information System (INIS)

    Masalov, Anatolii V; Chudnovsky, Aleksandr V

    2004-01-01

    It is shown that the finite thickness of the second-harmonic crystal distorts the results of measurements in nonlinear autocorrelators intended for measuring the durations and fields of femtosecond light pulses mainly due to dispersive broadening (or compression) of the pulses being measured, as well as due to the group velocity mismatch between the fundamental and sum-frequency pulses. The refractive index dispersion of the crystal, scaled by half its thickness, distorts the pulse duration to a certain extent depending on its initial chirp and thus determines the width of the energy distribution recorded in the autocorrelator. As the crystal thickness increases, the group velocity mismatch leads to a transformation of the recorded distribution from the correlation function of intensity to the squared modulus of the field correlation function. In the case of Gaussian pulses, such a transformation does not affect significantly the recorded distribution. Errors of pulse duration measurements are estimated. (nonlinear optical phenomena)

  4. The Effect of Autocorrelation on the Hotelling T-2 Control Chart

    DEFF Research Database (Denmark)

    Vanhatalo, Erik; Kulahci, Murat

    2015-01-01

    One of the basic assumptions for traditional univariate and multivariate control charts is that the data are independent in time. For the latter, in many cases, the data are serially dependent (autocorrelated) and cross-correlated because of, for example, frequent sampling and process dynamics......- correlation structures for different magnitudes of shifts in the process mean is not fully explored in the literature. In this article, the performance of the Hotelling T-2 control chart for different shift sizes and various autocorrelation and cross- correlation structures are compared based on the average...... and using the raw data with adjusted control limits calculated through Monte Carlo simulations; and (iii) constructing the control chart for the residuals from a multivariate time series model fitted to the raw data. To limit the complexity, we use a first-order vector autoregressive process and focus...

  5. First measurements of subpicosecond electron beam structure by autocorrelation of coherent diffraction radiation

    CERN Document Server

    Lumpkin, Alex H; Rule, D W

    2001-01-01

    We report the initial measurements of subpicosecond electron beam structure using a nonintercepting technique based on the autocorrelation of coherent diffraction radiation (CDR). A far infrared (FIR) Michelson interferometer with a Golay detector was used to obtain the autocorrelation. The radiation was generated by a thermionic rf gun beam at 40 MeV as it passed through a 5-mm-tall slit/aperture in a metal screen whose surface was at 45 deg. to the beam direction. For the observed bunch lengths of about 450 fs (FWHM) with a shorter time spike on the leading edge, peak currents of about 100 A are indicated. Also a model was developed and used to calculate the CDR from the back of two metal strips separated by a 5-mm vertical gap. The demonstrated nonintercepting aspect of this method could allow on-line bunch length characterizations to be done during free-electron laser experiments.

  6. OFDM Signal Detector Based on Cyclic Autocorrelation Function and its Properties

    Directory of Open Access Journals (Sweden)

    Z. Fedra

    2011-12-01

    Full Text Available This paper is devoted to research of the general and particular properties of the OFDM signal detector based on the cyclic autocorrelation function. The cyclic autocorrelation function is estimated using DFT. The parameters of the testing signal have been chosen according to 802.11g WLAN. Some properties are described analytically; all events are examined via computer simulations. It is shown that the detector is able to detect an OFDM signal in the case of multipath propagation, inexact frequency synchronization and without time synchronization. The sensitivity of the detector could be decreased in the above cases. An important condition for proper value of the detector sampling interval was derived. Three types of the channels were studied and compared. Detection threshold SNR=-9 dB was found for the signal under consideration and for two-way propagation.

  7. Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study.

    Science.gov (United States)

    Shanahan, Daniel R

    2016-01-01

    Background. The Journal Citation Reports journal impact factors (JIFs) are widely used to rank and evaluate journals, standing as a proxy for the relative importance of a journal within its field. However, numerous criticisms have been made of use of a JIF to evaluate importance. This problem is exacerbated when the use of JIFs is extended to evaluate not only the journals, but the papers therein. The purpose of this study was therefore to investigate the relationship between the number of citations and journal IF for identical articles published simultaneously in multiple journals. Methods. Eligible articles were consensus research reporting statements listed on the EQUATOR Network website that were published simultaneously in three or more journals. The correlation between the citation count for each article and the median journal JIF over the published period, and between the citation count and number of article accesses was calculated for each reporting statement. Results. Nine research reporting statements were included in this analysis, representing 85 articles published across 58 journals in biomedicine. The number of citations was strongly correlated to the JIF for six of the nine reporting guidelines, with moderate correlation shown for the remaining three guidelines (median r = 0.66, 95% CI [0.45-0.90]). There was also a strong positive correlation between the number of citations and the number of article accesses (median r = 0.71, 95% CI [0.5-0.8]), although the number of data points for this analysis were limited. When adjusted for the individual reporting guidelines, each logarithm unit of JIF predicted a median increase of 0.8 logarithm units of citation counts (95% CI [-0.4-5.2]), and each logarithm unit of article accesses predicted a median increase of 0.1 logarithm units of citation counts (95% CI [-0.9-1.4]). This model explained 26% of the variance in citations (median adjusted r (2) = 0.26, range 0.18-1.0). Conclusion. The impact factor of the

  8. Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study

    Directory of Open Access Journals (Sweden)

    Daniel R. Shanahan

    2016-03-01

    Full Text Available Background. The Journal Citation Reports journal impact factors (JIFs are widely used to rank and evaluate journals, standing as a proxy for the relative importance of a journal within its field. However, numerous criticisms have been made of use of a JIF to evaluate importance. This problem is exacerbated when the use of JIFs is extended to evaluate not only the journals, but the papers therein. The purpose of this study was therefore to investigate the relationship between the number of citations and journal IF for identical articles published simultaneously in multiple journals. Methods. Eligible articles were consensus research reporting statements listed on the EQUATOR Network website that were published simultaneously in three or more journals. The correlation between the citation count for each article and the median journal JIF over the published period, and between the citation count and number of article accesses was calculated for each reporting statement. Results. Nine research reporting statements were included in this analysis, representing 85 articles published across 58 journals in biomedicine. The number of citations was strongly correlated to the JIF for six of the nine reporting guidelines, with moderate correlation shown for the remaining three guidelines (median r = 0.66, 95% CI [0.45–0.90]. There was also a strong positive correlation between the number of citations and the number of article accesses (median r = 0.71, 95% CI [0.5–0.8], although the number of data points for this analysis were limited. When adjusted for the individual reporting guidelines, each logarithm unit of JIF predicted a median increase of 0.8 logarithm units of citation counts (95% CI [−0.4–5.2], and each logarithm unit of article accesses predicted a median increase of 0.1 logarithm units of citation counts (95% CI [−0.9–1.4]. This model explained 26% of the variance in citations (median adjusted r2 = 0.26, range 0.18–1.0. Conclusion

  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. Sensitive rapid analysis of iodine-labelled protein mixture on flat substrates with high spatial resolution

    International Nuclear Information System (INIS)

    Zanevskij, Yu.V.; Ivanov, A.B.; Movchan, S.A.; Peshekhonov, V.D.; Chan Dyk Tkhan'; Chernenko, S.P.; Kaminir, L.B.; Krejndlin, Eh.Ya.; Chernyj, A.A.

    1983-01-01

    Usability of rapid analysis by electrophoresis of the admixture of I 125 -labelled proteins on flat samples by means of URAN type installation developed using a multiwire proportional chamber is studied. The sensitivity of the method is better than 200 cpm/cm 2 and the spatial resolution is approximately 1 mm. The procedure of the rapid analysis is no longer than several tens of minutes

  11. 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.

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

    International Nuclear Information System (INIS)

    Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

    2006-01-01

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

  13. 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.

  14. 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.)

  15. 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.

  16. 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

  17. Modified Exponential Weighted Moving Average (EWMA) Control Chart on Autocorrelation Data

    Science.gov (United States)

    Herdiani, Erna Tri; Fandrilla, Geysa; Sunusi, Nurtiti

    2018-03-01

    In general, observations of the statistical process control are assumed to be mutually independence. However, this assumption is often violated in practice. Consequently, statistical process controls were developed for interrelated processes, including Shewhart, Cumulative Sum (CUSUM), and exponentially weighted moving average (EWMA) control charts in the data that were autocorrelation. One researcher stated that this chart is not suitable if the same control limits are used in the case of independent variables. For this reason, it is necessary to apply the time series model in building the control chart. A classical control chart for independent variables is usually applied to residual processes. This procedure is permitted provided that residuals are independent. In 1978, Shewhart modification for the autoregressive process was introduced by using the distance between the sample mean and the target value compared to the standard deviation of the autocorrelation process. In this paper we will examine the mean of EWMA for autocorrelation process derived from Montgomery and Patel. Performance to be investigated was investigated by examining Average Run Length (ARL) based on the Markov Chain Method.

  18. What autocorrelation tells us about motor variability: insights from dart throwing.

    Directory of Open Access Journals (Sweden)

    Robert J van Beers

    Full Text Available In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Prevalence, risk factors and spatial analysis of liver fluke infections in Danish cattle herds

    DEFF Research Database (Denmark)

    Olsen, Abbey; Frankena, Klaas; Bødker, Rene

    2015-01-01

    Background: Fasciola hepatica, a trematode parasite (liver fluke), infects a wide range of host species causing fasciolosis. The disease is prevalent world-wide and causes considerable economic losses to the livestock industry. Fasciolosis is regarded as an emerging food-borne zoonosis. To promote...... awareness among farmers and to implement strategies to control the infection, this study examined the prevalence, spatial distribution and risk factors for Fasciola hepatica infection in Danish cattle herds. Methods: A retrospective population based study was performed using meat inspection data...... of approximately 1.5 million cattle slaughtered in the period 2011 to 2013. Annual cumulative prevalence of recorded liver fluke findings was calculated for each year. Global and local spatial cluster analysis was used to identify and map spatial patterns of Fasciola hepatica positive and negative herds to explore...

  6. 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.

  7. 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.

  8. Prevalence, risk factors and spatial analysis of liver fluke infections in Danish cattle herds

    DEFF Research Database (Denmark)

    Olsen, Abbey; Frankena, Klaas; Bødker, Rene

    2015-01-01

    fitted the observed spatial pattern. Results: During the investigated period (2011-2013), an increase in annual herd prevalence was noted (2011-25.6%; 2012-28.4%; 2013-29.3%). The spatial analysis suggested significant clustering of positive and negative herds. Presence of streams, wetlands and pastures...... on farms showed a significant association with the presence of infection in cattle herds. Buying animals from positive herds was a risk factor on conventional farms. Additionally, risk of being infected with Fasciola hepatica was higher in non-dairy herds of medium size (>= 30 and ... to dairy and large (>= 100) cattle herds. The observed spatial pattern could be reproduced by predictions of the risk factor model. Conclusions: This study showed an increase in annual herd level prevalence (2011 to 2013) indicating that an increasing proportion of herds are infected with Fasciola hepatica...

  9. 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.

  10. Gender, space, and the location changes of jobs and people: a spatial simultaneous equations analysis.

    Science.gov (United States)

    Hoogstra, Gerke J

    2012-01-01

    This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes autoregressive and cross-regressive spatial lags to detect relations both within and among these groups. Spatial weights matrices reflecting different bands of travel times are used to calculate the spatial lags and to gauge the spatial nature of these relations. The empirical results show that although population–employment interaction is more localized for women's employment, no gender difference exists in the direction of interaction. Employment growth for both men and women is more influenced by population growth than vice versa. The interaction within employment groups is even more important than population growth. Women's, and especially men's, local employment growth mostly benefits from the same employment growth in neighboring locations. Finally, interaction between these groups is practically absent, although men's employment growth may have a negative impact on women's employment growth within small geographic areas. In summary, the results confirm the crucial roles of gender and space, and offer important insights into possible relations within and among subgroups of jobs and people.

  11. Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis.

    Science.gov (United States)

    Liu, Chuanjun; Xiao, Chengli

    2018-01-01

    The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

  12. Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis

    Directory of Open Access Journals (Sweden)

    Chuanjun Liu

    2018-02-01

    Full Text Available The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

  13. 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.

  14. 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.

  15. 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

  16. Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

    Science.gov (United States)

    Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

    2018-03-01

    In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

  17. Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta

    Directory of Open Access Journals (Sweden)

    KUSUM J NAITHANI

    2014-07-01

    Full Text Available This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress, a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion and Solidago missouriensis (goldenrod found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

  18. 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)

  19. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    International Nuclear Information System (INIS)

    Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.; Sales, Brian C.; Sefat, Athena S.

    2014-01-01

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe 0.55 Se 0.45 (T c = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe 1−x Se x structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces

  20. 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. 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.

  2. Ancestry inference using principal component analysis and spatial analysis: a distance-based analysis to account for population substructure.

    Science.gov (United States)

    Byun, Jinyoung; Han, Younghun; Gorlov, Ivan P; Busam, Jonathan A; Seldin, Michael F; Amos, Christopher I

    2017-10-16

    Accurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies. In this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships. We demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations. Our results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.

  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. 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

  5. Fine-scale spatial distribution of plants and resources on a sandy soil in the Sahel

    NARCIS (Netherlands)

    Rietkerk, M.G.; Ouedraogo, T.; Kumar, L.; Sanou, S.; Langevelde, F. van; Kiema, A.; Koppel, J. van de; Andel, J. van; Hearne, J.; Skidmore, A.K.; Ridder, N. de; Stroosnijder, L.; Prins, H.H.T.

    2002-01-01

    We studied fine-scale spatial plant distribution in relation to the spatial distribution of erodible soil particles, organic matter, nutrients and soil water on a sandy to sandy loam soil in the Sahel. We hypothesized that the distribution of annual plants would be highly spatially autocorrelated

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Landslide susceptibility assessment using Spatial Analysis and GIS modeling in Cluj-Napoca Metropolitan Area, Romania

    Directory of Open Access Journals (Sweden)

    Bogdan Eugen Dolean

    2017-06-01

    Full Text Available In Romania, landslides together with the multitude geomorphological processes linked to them are some of the most common hazards which manifested in vulnerable areas with important human activities can induce many negative effects. From this perspective, identifying the areas affected by landslides, based on GIS spatial analysis models and statistical methods, is a subject frequently discussed in the national and international literature. This research was focused on the methods and practices of GIS spatial analysis, with a target of creating a complex model and a viable methodology of assessment the probability of occurrence of landslides, applicable within any territory. The study was based on the identification and analysis in a bivariate systemic manner of the numerous factors involved in the production of landslides, such as topography, morphology, hydrography, geological, lithology, weather, land use. The area in which the analysis has been conducted, The Metropolitan Area of Cluj-Napoca, was chosen due to the exacerbated urbanization of the recent years, coupled with a massive increase in the number of inhabitants, thus being a space of socioeconomic importance and a real challenge regarding spatial planning. Applying the model in this area has generated relatively good results, with a power of predictability of over 80%, measured in landslides sample areas used for the validation of the results, fact which attest the viability of the model and the fact that the model can be used in different areas with related morphometric and environmental characteristics.

  12. Análise espacial dos determinantes socioeconômicos dos homicídios no Estado de Pernambuco Spatial analysis of socioeconomic determinants of homicide in Brazil

    Directory of Open Access Journals (Sweden)

    Maria Luiza C de Lima

    2005-04-01

    income of the head of the family, poverty index, rate of illiteracy, and demographic density. The following techniques were used in the analysis: a spatial autocorrelation test determined by the Moran index, multiple linear regression, a spatial regression model (CAR and a generalized additive model for the detection of spatial trend (LOESS. RESULTS: The illiteracy and the poverty index explained 24.6% of the total variability of the homicide rates and there was an inverse relationship. Moran´s I statistics indicated spatial autocorrelation between municipalities. The multiple linear regression model best fitted for the purposes of this study was the Conditional Auto Regressive (CAR model. The latter confirmed the association between the poverty index, illiteracy and homicide rates. CONCLUSIONS: The inverse association observed between socio-economic indicators and homicides may be expressing a process that propitiates improvement in living conditions and that is linked predominantly to conditions that generate violence, such as drug traffic.

  13. Research on the Spatial-Temporal Distribution Pattern of the Network Attention of Fog and Haze in China

    Science.gov (United States)

    Weng, Lingyan; Han, Xugao

    2018-01-01

    Understanding the spatial-temporal distribution pattern of fog and haze is the base to deal with them by adjusting measures to local conditions. Taking 31 provinces in China mainland as the research areas, this paper collected data from Baidu index on the network attention of fog and haze in relevant areas from 2011 to 2016, and conducted an analysis of their spatial-temporal distribution pattern by using autocorrelation analysis. The results show that the network attention of fog and haze has an overall spatial distribution pattern of “higher in the eastern and central, lower in the western China”. There are regional differences in different provinces in terms of network attention. Network attention of fog and haze indicates an obvious geographical agglomeration phenomenon, which is a gradual enlargement of the agglomeration area of higher value with a slight shrinking of those lower value agglomeration areas.

  14. 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

  15. The Evolution of Spatial Representation During Complex Visual Data Analysis: Knowing When and How to be Exact

    National Research Council Canada - National Science Library

    Schunn, Christian D; Saner, Lelyn D; Trafton, J. G; Trickett, Susan B; Kirschenbaum, Susan K; Knepp, Michael; Shoup, Melanie

    2005-01-01

    ... (weather forecasting, submarine target motion analysis, and fMRI data analysis). Internal spatial representations are coded from spontaneous gestures made during cued-recall summaries of problem solving activities...

  16. 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.

  17. 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

  18. 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.

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

    Science.gov (United States)

    Statham, P.; Holland, J.

    2014-03-01

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

  20. Spatial analysis of hemorrhagic fever with renal syndrome in Zibo City, China, 2009-2012.

    Directory of Open Access Journals (Sweden)

    Feng Cui

    Full Text Available BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS is highly endemic in mainland China, where human cases account for 90% of the total global cases. Zibo City is one of the most serious affected areas in Shandong Province China with the HFRS incidence increasing sharply from 2009 to 2012. However, the hotspots of HFRS in Zibo remained unclear. Thus, a spatial analysis was conducted with the aim to explore the spatial, spatial-temporal and seasonal patterns of HFRS in Zibo from 2009 to 2012, and to provide guidance for formulating regional prevention and control strategies. METHODS: The study was based on the reported cases of HFRS from the National Notifiable Disease Surveillance System. Annualized incidence maps and seasonal incidence maps were produced to analyze the spatial and seasonal distribution of HFRS in Zibo City. Then spatial scan statistics and space-time scan statistics were conducted to identify clusters of HFRS. RESULTS: There were 200 cases reported in Zibo City during the 4-year study period. One most likely cluster and one secondary cluster for high incidence of HFRS were identified by the space-time analysis. And the most likely cluster was found to exist at Yiyuan County in October to December 2012. The human infections in the fall and winter reflected a seasonal characteristic pattern of Hantaan virus (HTNV transmission. The secondary cluster was detected at the center of Zibo in May to June 2009, presenting a seasonal characteristic of Seoul virus (SEOV transmission. CONCLUSION: To control and prevent HFRS in Zibo city, the comprehensive preventive strategy should be implemented in the southern areas of Zibo in autumn and in the northern areas of Zibo in spring.

  1. Preliminary spatial analysis of combined BATSE/Ulysses gamma-ray burst locations

    International Nuclear Information System (INIS)

    Kippen, R. Marc; Hurley, Kevin; Pendleton, Geoffrey N.

    1998-01-01

    We present the preliminary spatial analysis of 278 bursts that have been localized by BATSE and the two-spacecraft Compton/Ulysses Interplanetary Network. The large number and superior accuracy of the combined BATSE/Ulysses locations provides improved sensitivity to small-angle source properties. We find that the locations are consistent with large- and small-scale isotropy, with no significant small-angle clustering. We constrain the fraction of sources in clusters and discuss the implications for burst repetition

  2. 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.

  3. The spatial metaphor of Utopia in Russian culture and in analysis.

    Science.gov (United States)

    Tsivinsky, Vladimir

    2014-02-01

    The spatial metaphor of Utopia is considered from a Jungian perspective along with its role in Russian culture and in analysis. Such post-Jungian concepts as the cultural complex and the archetypal story pattern of a victim are used in considering the desperate longing for a rescuer in patients' narratives and in Russian society. A clinical vignette is provided to illustrate these ideas. © 2014, The Society of Analytical Psychology.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

    Directory of Open Access Journals (Sweden)

    Gilney Figueira Zebende

    Full Text Available In this paper we analyzed, by the FDFA root mean square fluctuation (rms function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG. We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head and P349, P654 (parietal region of the head. We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

  9. Quantitative spatial analysis of the mouse brain lipidome by pressurized liquid extraction surface analysis

    DEFF Research Database (Denmark)

    Almeida, Reinaldo; Berzina, Zane; Christensen, Eva Arnspang

    2015-01-01

    extracted directly from tissue sections. PLESA uses a sealed and pressurized sampling probe that enables the use of chloroform-containing extraction solvents for efficient in situ lipid microextraction with a spatial resolution of 400 μm. Quantification of lipid species is achieved by the inclusion...

  10. Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks

    International Nuclear Information System (INIS)

    Ouyang, Min

    2016-01-01

    Infrastructure systems are usually spatially distributed in a wide area and are subject to many types of hazards. For each type of hazards, modeling their direct impact on infrastructure components and analyzing their induced system-level vulnerability are important for identifying mitigation strategies. This paper mainly studies spatially localized attacks that a set of infrastructure components located within or crossing a circle shaped spatially localized area is subject to damage while other components do not directly fail. For this type of attacks, taking interdependent power and gas systems in Harris County, Texas, USA as an example, this paper proposes an approach to exactly identify critical locations in interdependent infrastructure systems and make pertinent vulnerability analysis. Results show that (a) infrastructure interdependencies and attack radius largely affect the position of critical locations; (b) spatially localized attacks cause less vulnerability than equivalent random failures; (c) in most values of attack radius critical locations identified by considering only node failures do not change when considering both node and edge failures in the attack area; (d) for many values of attack radius critical locations identified by topology-based model are also critical from the flow-based perspective. - Highlights: • We propose a method to identify critical locations in interdependent infrastructures. • Geographical interdependencies and attack radius largely affect critical locations. • Localized attacks cause less vulnerability than equivalent random failures. • Whether considering both node and edge failures affects critical locations. • Topology-based critical locations are also critical from flow-based perspective.

  11. 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.

  12. 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.

  13. 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.

  14. Damage detection and isolation via autocorrelation: a step toward passive sensing

    Science.gov (United States)

    Chang, Y. S.; Yuan, F. G.

    2018-03-01

    Passive sensing technique may eliminate the need of expending power from actuators and thus provide a means of developing a compact and simple structural health monitoring system. More importantly, it may provide a solution for monitoring the aircraft subjected to environmental loading from air flow during operation. In this paper, a non-contact auto-correlation based technique is exploited as a feasibility study for passive sensing application to detect damage and isolate the damage location. Its theoretical basis bears some resemblance to reconstructing Green's function from diffusive wavefield through cross-correlation. Localized high pressure air from air compressor are randomly and continuously applied on the one side surface of the aluminum panels through the air blow gun. A laser Doppler vibrometer (LDV) was used to scan a 90 mm × 90 mm area to create a 6 × 6 2D-array signals from the opposite side of the panels. The scanned signals were auto-correlated to reconstruct a "selfimpulse response" (or Green's function). The premise for stably reconstructing the accurate Green's function requires long sensing times. For a 609.6 mm × 609.6 mm flat aluminum panel, the sensing times roughly at least four seconds is sufficient to establish converged Green's function through correlation. For the integral stiffened aluminum panel, the geometrical features of the panel expedite the formation of the diffusive wavefield and thus shorten the sensing times. The damage is simulated by gluing a magnet onto the panels. Reconstructed Green's functions (RGFs) are used for damage detection and damage isolation based on an imaging condition with mean square deviation of the RGFs from the pristine and the damaged structure and the results are shown in color maps. The auto-correlation based technique is shown to consistently detect the simulated damage, image and isolate the damage in the structure subjected to high pressure air excitation. This technique may be transformed into

  15. Auto-correlation of velocity-fluctuations and frequency-dependent diffusion constant for hot electrons

    International Nuclear Information System (INIS)

    Roy, M.D.; Nag, B.R.

    1981-01-01

    A method has been developed for determining the auto-correlation functions of the fluctuations in the transverse and the parallel components of hot carrier-velocity in a semiconductor by Monte Carlo simulation. The functions for electrons in InSb are determined by this method for applied electric fields of 50 V/cm, 75 V/cm, and 100 V/cm. With increasing value of the time interval the transverse auto-correlation function fall nearly exponentially to zero, but the parallel function falls sharply to a negative peak, then rises to positive values and finally becomes zero. The interval beyond which the auto-correlation function is zero and the correlation time are also evaluated. The correlation time is found to be approximately 1.6 times the relaxation time calculated from the chord mobility. The effect of the flight sampling time on the value of variance of the displacement, is investigated in terms of the low frequency diffusion constants, determined from the variation of the correlation functions. It is found that the diffusion constants become independent of the sampling time if it is of the order of one hundred times the relaxation time. The frequency-dependent diffusion constants are calculated from the correlation functions. The transverse diffusion constant falls monotonically with frequency for all the field strengths studied. The parallel diffusion constant has similar variation for the lower fields (50 V/cm and 75 V/cm) but it has a peak at about 44 GHz for the field of 100 V/cm. (orig.)

  16. On the analysis of spatial chaos and Hopf bifurcation in an optical open flow

    International Nuclear Information System (INIS)

    Saha, Papri; Rakshit, B.; Chowdhury, A. Roy

    2005-01-01

    Spatial chaos in a system of copropagating nonlinear beam, interacting mutually, is explored. The case of four beams belonging to two weakly degenerate mode in a multimode fibre is analysed. The modulation of the waves due to mutual energy exchange is shown to give rise to chaos. We characterize the chaos with the help of Lyapunov exponent and phase space analysis. The case of centre manifold with imaginary eigenvalue is separated with the help of normal form analysis, when the system is reduced to a two component one. The reduced problem is then analysed with the help of a tangent field diagram

  17. Analysis of spatial distribution and marketing area of boutique hotels in Shanghai

    Directory of Open Access Journals (Sweden)

    Chu Xueqin

    2017-08-01

    Full Text Available Basing on data collected from Google Earth and Baidu Map,we inputed the coordinates of the address of boutique hotels,five-star hotels in Shanghai,scenic spots above 3A in the urban area of Shanghai and historical relics protection units in Shanghai et al into the Arc GIS,which locates these units in accurate position.We measured some distance data by the tool of spatial analysis.The distribution map and marketing area analysis of boutique hotel were made.

  18. OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

    DEFF Research Database (Denmark)

    de Raad, Markus; de Rond, Tristan; Rübel, Oliver

    2017-01-01

    ://openmsinersc.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...... processing tools for the analysis of large arrayed MSI sample sets. 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...

  19. New autocorrelation technique for the IR FEL optical pulse width measurements

    Energy Technology Data Exchange (ETDEWEB)

    Amirmadhi, F.; Brau, K.A.; Becker, C. [Vanderbilt Univ., Nashville, TN (United States)] [and others

    1995-12-31

    We have developed a new technique for the autocorrelation measurement of optical pulse width at the Vanderbilt University FEL center. This method is based on nonlinear absorption and transmission characteristics of semiconductors such as Ge, Te and InAs suitable for the wavelength range from 2 to over 6 microns. This approach, aside being simple and low cost, removes the phase matching condition that is generally required for the standard frequency doubling technique and covers a greater wavelength range per nonlinear material. In this paper we will describe the apparatus, explain the principal mechanism involved and compare data which have been acquired with both frequency doubling and two-photon absorption.

  20. A comparison of two least-squared random coefficient autoregressive models: with and without autocorrelated errors

    OpenAIRE

    Autcha Araveeporn

    2013-01-01

    This paper compares a Least-Squared Random Coefficient Autoregressive (RCA) model with a Least-Squared RCA model based on Autocorrelated Errors (RCA-AR). We looked at only the first order models, denoted RCA(1) and RCA(1)-AR(1). The efficiency of the Least-Squared method was checked by applying the models to Brownian motion and Wiener process, and the efficiency followed closely the asymptotic properties of a normal distribution. In a simulation study, we compared the performance of RCA(1) an...

  1. Autocorrelation exponent of conserved spin systems in the scaling regime following a critical quench.

    Science.gov (United States)

    Sire, Clément

    2004-09-24

    We study the autocorrelation function of a conserved spin system following a quench at the critical temperature. Defining the correlation length L(t) approximately t(1/z), we find that for times t' and t satisfying L(t')infinity limit, we show that lambda(')(c)=d+2 and phi=z/2. We give a heuristic argument suggesting that this result is, in fact, valid for any dimension d and spin vector dimension n. We present numerical simulations for the conserved Ising model in d=1 and d=2, which are fully consistent with the present theory.

  2. Influence of the nuclear autocorrelation function on the positron production in heavy-ion collisions

    International Nuclear Information System (INIS)

    Tomoda, T.; Weidenmueller, H.A.

    1983-01-01

    The influence of a nuclear reaction on atomic positron production in heavy-ion collisions is investigated. Using statistical concepts, we describe the nuclear S matrix for a heavy-ion induced reaction as a statistically fluctuating function of energy. The positron production rate is then dependent on the autocorrelation function of this S matrix, and on the ratio of the ''direct'' versus the ''fluctuating'' part of the nuclear cross section. Numerical calculations show that in this way, current experimental results on positron production in heavy-ion collisions can be reproduced in a semiquantitative fashion

  3. Transforming the autocorrelation function of a time series to detect land cover change

    CSIR Research Space (South Africa)

    Salmon

    2015-07-01

    Full Text Available stream_source_info Salmon_2016.pdf.txt stream_content_type text/plain stream_size 1090 Content-Encoding ISO-8859-1 stream_name Salmon_2016.pdf.txt Content-Type text/plain; charset=ISO-8859-1 International Geoscience... and Remote Sensing Symposium (IEEE IGARSS), 10-15 July 2016, Beijing Transforming the autocorrelation function of a time series to detect land cover change Salmon, B.P., Kleynhans, W., Olivier, J.C. and Schwegmann, C.P. ABSTRACT Regional...

  4. Sign reversals of the output autocorrelation function for the stochastic Bernoulli-Verhulst equation

    Energy Technology Data Exchange (ETDEWEB)

    Lumi, N., E-mail: Neeme.Lumi@tlu.ee; Mankin, R., E-mail: Romi.Mankin@tlu.ee [Institute of Mathematics and Natural Sciences, Tallinn University, 29 Narva Road, 10120 Tallinn (Estonia)

    2015-10-28

    We consider a stochastic Bernoulli-Verhulst equation as a model for population growth processes. The effect of fluctuating environment on the carrying capacity of a population is modeled as colored dichotomous noise. Relying on the composite master equation an explicit expression for the stationary autocorrelation function (ACF) of population sizes is found. On the basis of this expression a nonmonotonic decay of the ACF by increasing lag-time is shown. Moreover, in a certain regime of the noise parameters the ACF demonstrates anticorrelation as well as related sign reversals at some values of the lag-time. The conditions for the appearance of this highly unexpected effect are also discussed.

  5. 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

  6. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Science.gov (United States)

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

  7. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Directory of Open Access Journals (Sweden)

    Hongoh Valerie

    2011-12-01

    Full Text Available Abstract The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector

  8. Analysis Framework of China’s Grain Production System: A Spatial Resilience Perspective

    Directory of Open Access Journals (Sweden)

    Dazhuan Ge

    2017-12-01

    Full Text Available China’s grain production has transformed from absolute shortage to a current structural oversupply. High-intensity production introduced further challenges for the eco-environment, smallholder livelihood, and the man-land interrelationship. Driven by urban-rural transformation, research on food security patterns and grain production has expanded into a new field. To analyze the challenges and required countermeasures for China’s grain production system (GPS, this study constructed a theoretical GPS framework based on space resilience. Firstly, a new GPS concept was proposed and a functional system was established for protecting the regional food security, thus guaranteeing smallholder livelihood, stabilizing urban-rural transformation, and sustaining the eco-environment in terms of economic, social, and ecological attributes of the GPS. Secondly, based on a cross-scale interaction analysis that varied from a smallholder scale to a global scale, the systematic crisis of the GPS was analyzed. Thirdly, a cross-scale analytic framework of the GPS was formed from the perspective of spatial resilience, integrating both inner and external disturbance factors of the GPS. Both spatial heterogeneity and connectivity of internal and external disturbance factors are important contents of system space resilience. Finally, the hierarchy of spatial resilience of GPS became clear. The transformation of labor force and the land use transition form key thresholds of the GPS. In summary: based on protecting the basic functions of the GPS, the cross-scale effect of systematic disturbance factors and relevant countermeasures for spatial resilience are effectively influenced by the coordination of the interests of multiple stakeholders; spatial resilience is an effective analytical tool for GPS regulation, providing a reference for revealing the inherent mechanism and functional evolution of the GPS in the process of urban-rural transformation.

  9. Spatial analysis of charcoal kiln remains in the former royal forest district Tauer (Lower Lusatia, North German Lowlands)

    Science.gov (United States)

    Raab, Alexandra; Schneider, Anna; Bonhage, Alexander; Takla, Melanie; Hirsch, Florian; Müller, Frank; Rösler, Horst; Heußner, Karl-Uwe

    2016-04-01

    Archaeological excavations have revealed more than thousand charcoal kiln remains (CKRs) in the prefield of the active opencast lignite mine Jänschwalde, situated about 150 km SE of Berlin (SE Brandenburg, Germany). The charcoal was mainly produced for the ironwork Peitz nearby, which operated from the 16th to the mid-19th centuries. In a first approach, to estimate the dimension of the charcoal production, CKRs were mapped on shaded-relief maps (SRMs) derived from high-resolution LiDAR data (Raab et al. 2015). Subsequently, for a selected test area, identified CKRs on the SRMs were compared with archaeologically excavated CKRs in the field. This survey showed a considerably number of falsely detected sites. Therefore, the data was critically re-evaluated using additional relief visualisations. Further, we extended the CKR mapping to areas which are not archaeologically investigated. The study area, the former royal forest district Tauer, consists of two separate areas: the Tauersche Heide (c. 96 km2 area) N of Peitz and the area Jänschwalde (c. 32 km2 area) NE of Peitz. The study area is characterized by a flat topography. Different former and current anthropogenic uses (e.g., military training, solar power plant, forestry measures) have affected the study area, resulting in extensive disturbances of the terrain surface. The revised CKR abundance in the study area Jänschwalde was considerably smaller than the numbers produced by our first approach. Further, the CKR mapping revealed, that a total record of the CKRs is not possible for various reasons. Despite these limitations, a solid database can be provided for a much larger area than before. Basic statistic parameters of the CKR diameters and all comparative statistical tests were calculated using SPSS. To detect underlying spatial relationships in the CKR site distribution, we applied the Getis-Ord Gi* statistic, a method to test for local spatial autocorrelation between neighbouring sites. The test is

  10. 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)

  11. 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.

  12. Analysis of spatial relationships in three dimensions: tools for the study of nerve cell patterning

    Directory of Open Access Journals (Sweden)

    Raven Mary A

    2008-07-01

    Full Text Available Abstract Background Multiple technologies have been brought to bear on understanding the three-dimensional morphology of individual neurons and glia within the brain, but little progress has been made on understanding the rules controlling cellular patterning. We describe new matlab-based software tools, now available to the scientific community, permitting the calculation of spatial statistics associated with 3D point patterns. The analyses are largely derived from the Delaunay tessellation of the field, including the nearest neighbor and Voronoi domain analyses, and from the spatial autocorrelogram. Results Our tools enable the analysis of the spatial relationship between neurons within the central nervous system in 3D, and permit the modeling of these fields based on lattice-like simulations, and on simulations of minimal-distance spacing rules. Here we demonstrate the utility of our analysis methods to discriminate between two different simulated neuronal populations. Conclusion Together, these tools can be used to reveal the presence of nerve cell patterning and to model its foundation, in turn informing on the potential developmental mechanisms that govern its establishment. Furthermore, in conjunction with analyses of dendritic morphology, they can be used to determine the degree of dendritic coverage within a volume of tissue exhibited by mature nerve cells.

  13. Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

    Science.gov (United States)

    Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

    2017-12-01

    We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

  14. 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.

  15. 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.

  16. 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.

  17. Fast Transient And Spatially Non-Homogenous Accident Analysis Of Two-Dimensional Cylindrical Nuclear Reactor

    International Nuclear Information System (INIS)

    Yulianti, Yanti; Su'ud, Zaki; Waris, Abdul; Khotimah, S. N.; Shafii, M. Ali

    2010-01-01

    The research about fast transient and spatially non-homogenous nuclear reactor accident analysis of two-dimensional nuclear reactor has been done. This research is about prediction of reactor behavior is during accident. In the present study, space-time diffusion equation is solved by using direct methods which consider spatial factor in detail during nuclear reactor accident simulation. Set of equations that obtained from full implicit finite-difference discretization method is solved by using iterative methods ADI (Alternating Direct Implicit). The indication of accident is decreasing macroscopic absorption cross-section that results large external reactivity. The power reactor has a peak value before reactor has new balance condition. Changing of temperature reactor produce a negative Doppler feedback reactivity. The reactivity will reduce excess positive reactivity. Temperature reactor during accident is still in below fuel melting point which is in secure condition.

  18. Spatial analysis for prevalence of type 2 diabetes mellitus - A state investigation

    Science.gov (United States)

    Zainal, Siti Salsabilah Nabilah; Masnan, Maz Jamilah; Amin, Nor Azrita Mohd; Mohamed, Nordin

    2017-11-01

    Type 2 Diabetes Mellitus (T2DM) is a chronic and non-communicable disease, which is characterized as the cause of premature deaths in the world. Unfortunately, Malaysia is one of the many countries facing this epidemic. Based on the increasing current trend of T2DM patients' cases from the National Diabetes Registry (NDR) Report from 2009 to 2012, there were approximately 2.6 million adults aged 18 years and above living with diabetes disease in Malaysia. Thus, this study aims to (i) perform preliminary spatial analysis for the prevalence of T2DM patients based on some factors, (ii) map the findings of the analyses according to some spatial properties, and (iii) analyze the pattern of diagnosed T2DM patients based on the studied factors. The studied population is one of the highest prevalence states of T2DM in Malaysia. This study is expected to reveal some demographic patterns that probably significant to this alarming epidemic.

  19. Geo-ecological spatial pattern analysis of the island of Fogo (Cape Verde)

    Science.gov (United States)

    Olehowski, C.; Naumann, S.; Fischer, D.; Siegmund, A.

    2008-12-01

    With its small-scale climatic, floristic and geo-ecological differentiation, the island of Fogo is an optimal research area for understanding semi-arid island ecosystems in the marginal tropics. Because of the high variability in precipitation, the archipelago of Cape Verde has a potentially high ecological vulnerability, which is caused mainly by population growth, intensification of agricultural land use and increasing tourism. In this context, a geo-ecological spatial pattern analysis has been conducted for Fogo, including several types of geo-ecological layers like vegetation, elevation, aspect, soil and geology. The different kinds of spatial patterns that are detected can be used as a first tool to display distinctive levels of ecological vulnerability. These levels could constitute a base for sustainable land use planning and the redevelopment of agricultural strategies.

  20. Relative risk of visceral leishmaniasis in Brazil: a spatial analysis in urban area.

    Directory of Open Access Journals (Sweden)

    Valdelaine Etelvina Miranda de Araújo

    2013-11-01

    Full Text Available BACKGROUND: Visceral leishmaniasis (VL is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission. METHODOLOGY: This is an ecological study on the relative risk of human VL. Spatial units of analysis were the coverage areas of the Basic Health Units (146 small-areas of Belo Horizonte, Minas Gerais State, Brazil. Human VL cases, from 2007 to 2009 (n = 412, were obtained in the Brazilian Reportable Disease Information System. Bayesian approach was used to model the relative risk of VL including potential risk factors involved in transmission (canine infection, socioeconomic and environmental features and to identify the small-areas of greater risk to human VL. PRINCIPAL FINDINGS: The relative risk of VL was shown to be correlated with income, education, and the number of infected dogs per inhabitants. The estimates of relative risk of VL were higher than 1.0 in 54% of the areas (79/146. The spatial modeling highlighted 14 areas with the highest relative risk of VL and 12 of them are concentrated in the northern region of the city. CONCLUSIONS: The spatial analysis used in this study is useful for the identification of small-areas according to risk of human VL and presents operational applicability in control and surveillance program in an urban environment with an unequal spatial distribution of the disease. Thus the frequent monitoring of relative risk of human VL in small-areas is important to direct and prioritize the actions of the control program in urban environment, especially in big cities.