A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

Science.gov (United States)

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

A Novel Artificial Immune Algorithm for Spatial Clustering with Obstacle Constraint and Its Applications

Directory of Open Access Journals (Sweden)

Liping Sun

2014-01-01

Full Text Available An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

The geometry of trifocal curves with applications in architecture, urban and spatial planning

Directory of Open Access Journals (Sweden)

Petrović Maja

2014-01-01

Full Text Available In this paper we consider historical genesis of trifocal curve as an optimal curve for solving the Fermat’s problem (minimizing the sum of distance of one point to three given points in the plane. Trifocal curves are basic plane geometric forms which appear in location problems. We also analyze algebraic equation of these curves and some of their applications in architecture, urbanism and spatial planning. The area and perimeter of trifocal curves are calculated using a Java application. The Java applet is developed for determining numerical value for the Fermat-Torricelli-Weber point and optimal curve with three foci, when starting points are given on an urban map. We also present an application of trifocal curves through the analysis of one specific solution in South Stream gas pipeline project.

Application of protective distances in vicinity of dangerous facilities in urban and spatial plans

Directory of Open Access Journals (Sweden)

Stojanović Božidar

2006-01-01

Full Text Available Environmental risk management in production, use and transportation of dangerous materials having been actual theme in the world and in Serbia. Although environmental risk is mostly connected with technical issues, since chemical catastrophe in Bophal-lndia (1986 in the world was recognized that this is complex issue that besides of technical-technological, includes also social-economic, organizational and spatial factors. Spatial component of risk management which is regulated by Seveso II Directive in EU is important for planners. This paper considers basic elements of environmental risk assessment, procedures and methods used in Europe, particularly in the process of land use planning, and characteristics of method for application of separation distances used in General plan of Belgrade.

Spatial variability of soil potassium in sugarcane areas subjected to the application of vinasse

Directory of Open Access Journals (Sweden)

LAÉRCIO A. DE CARVALHO

2014-12-01

Full Text Available When deposited on land the vinasse can promote improvement in fertility, however, often fertilizer application occurs in areas considered homogeneous, without taking into account the variability of the soil. The objective of this study was to evaluate the effect of vinasse application on potassium content in two classes of soils cultivated with sugarcane, and characterize the spatial variability of soil using geostatistical techniques. In the 2010 and 2011 crop year, soil samples were collected from an experimental grid at 0-0.2 and 0.2-0.4 m depth in three soils cultivated with sugarcane, totaling 90 samplings in each grid, for the determination of pH, calcium (Ca, magnesium (Mg, potassium (K, phosphorus (P, aluminum (Al and potential acidity (H + Al. The data have been submitted to analysis of descriptive statistics and the K attribute was subjected to geostatistical analysis. The coefficient of variation indicated medium and high variability of K for the three soils. The results showed that the spatial dependence of K increased in depth to FRce and decreased to PHlv, indicating that the attribute could have followed the pattern of distribution of clay in depth. The investigation of the spatial variability of K on the surface and subsurface soils provided the definition of management zones with different levels of fertility, which can be organized into sub-areas for a more efficient management of the resources and the environment.

[Effects of wheat-oilseed rape intercropping and methyl salicylate application on the spatial distributions of Sitobion avenae and its main natural enemies].

Science.gov (United States)

Dong, Jie; Liu, Ying-Jie; Wang, Guang; Liu, Yong

2012-07-01

A field investigation was conducted on the spatial distributions of Sitobion avenae and its main natural enemies under wheat-oilseed rape intercropping and methyl salicylate application. With the development of wheat plant, an alternation from aggregation to uniform was observed in the spatial distribution of S. avenae under the intercropping and methyl salicylate application, being more obvious under the interaction of the two practices. The spatial distribution of S. avenae natural enemies was in accordance with that of the aphid. These results could be used for the reference of sampling investigation and forecast of wheat aphid and its natural enemies in field.

Data Mining Relationships Among Urban Socioeconomic, Land Cover, and Remotely Sensed Ecological Data

Science.gov (United States)

Mennis, J.; Wessman, C.; Golubiewski, N.

2003-12-01

This research investigates the relationships among socioeconomic character, land cover, and ecological function in a rapidly urbanizing region, the Front Range of Colorado. We use novel spatial geographic information systems- (GIS-) based data integration and data mining techniques to integrate and analyze diverse spatial data sets. These data include elevation data, transportation data, land cover data derived from aerial photography, block group-level U.S. Census data, and vegetation greenness (NDVI) data derived from Landsat imagery. These data are used to derive a variety of U.S. block group-level variables indicating demographic, geographic, ecological, and land cover characteristics. We employ spatial association rule mining, decision tree induction, and spatial on-line analytical processing (OLAP), in addition to more conventional multivariate statistical techniques, to investigate relationships among these variables.

Likelihood devices in spatial statistics

NARCIS (Netherlands)

Zwet, E.W. van

1999-01-01

One of the main themes of this thesis is the application to spatial data of modern semi- and nonparametric methods. Another, closely related theme is maximum likelihood estimation from spatial data. Maximum likelihood estimation is not common practice in spatial statistics. The method of moments

Gelation of covalently edge-modified laponites in aqueous media. 1. rheology and nuclear magnetic resonance.

Science.gov (United States)

Patil, Suhas P; Mathew, Renny; Ajithkumar, T G; Rajamohanan, P R; Mahesh, T S; Kumaraswamy, Guruswamy

2008-04-17

We describe the covalent modification of the edges of laponite with organic groups and the influence of this modification on gelation behavior. We compare three materials: an unmodified laponite, a laponite edge modified with a trimethyl moiety (MLap), and an octyldimethyl moiety (OLap). Gelation is investigated using rheology and NMR T1 relaxation measurements and nuclear Overhauser enhancement spectroscopy (NOESY). MLap and OLap show qualitatively different gelation. Gelation of MLap is very similar to laponite: MLap gels over the same time scale as laponite and has about the same solid modulus, and the MLap gel is almost as transparent as laponite. In contrast, OLap gels rapidly relative to laponite and forms a weak, turbid gel. We believe that gelation in laponite and MLap results from the formation of a network of well-dispersed platelets (or a few platelets), while in OLap, gelation results from a network of stacks of several platelets. NMR relaxation measurements indicate that gelation does not affect the average relaxation of water protons. However, T1 increases marginally for the protons in the organic moieties in MLap and decreases for protons in the organic moieties in OLap. Relaxation measurements, analyses of line width, and NOESY taken together suggest that, in OLap, gelation is a consequence of association of the organic moieties on the laponite edges, and that this association strengthens with time. Thus, the time-dependent changes in NMR suggest a structural origin for the time-dependent changes in the rheological behavior.

The Decoration Operator: A Foundation for On-Line Dimensional Data Integration

DEFF Research Database (Denmark)

Pedersen, Dennis; Pedersen, Torben Bach; Riis, Karsten

2004-01-01

The changing data requirements of today's dynamic business environments are not handled well by current On-Line Analytical Processing (OLAP) systems. Physically integrating unexpected, external data into OLAP cubes, i.e., the data warehousing approach, is a long and time-consuming process, making...... logical, on-the-fly, integration the better choice in many situations. However, OLAP systems have no operations for integrating existing multidimensional cube data with external data. In this paper we present a novel multidimensional algebra operator, the decoration operator, which allows external data...... to be integrated in OLAP cubes as new dimensions, i.e., the cube is ``decorated'' with new dimensions which can subsequently be used just as the regular dimensions. We formally specify the semantics of the decoration operator, ensuring that semantic problems do not occur in the data integration process. We also...

A hierarchical spatial model of avian abundance with application to Cerulean Warblers

Science.gov (United States)

Thogmartin, Wayne E.; Sauer, John R.; Knutson, Melinda G.

2004-01-01

is counts, such as animal counts, activity (e.g.,nest) counts, or species richness. The most noteworthy practical application of this spatial modeling approach is the ability to map relative species abundance. The functional relationships that we elucidated for the Cerulean Warbler provide a basis for the development of management programs and may serve to focus management and monitoring on areas and habitat variables important to Cerulean Warblers.

Thermodynamic Model of Spatial Memory

Science.gov (United States)

Kaufman, Miron; Allen, P.

1998-03-01

We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.

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.

The application of spatial shifting for peak-to-average power ratio reduction in MIMO OFDM systems

NARCIS (Netherlands)

Schenk, T.C.W.; Smulders, P.F.M.; Fledderus, E.

2006-01-01

This paper investigates the application of spatial shifting (SS) of partial transmit sequences (PTSs) in multiple-input multiple-output OFDM. The technique rearranges the transmit (TX) vector in such a way that subparts are transmitted on those TX branches that result in the lowest overall

Applications of seismic spatial wavefield gradient and rotation data in exploration seismology

Science.gov (United States)

Schmelzbach, C.; Van Renterghem, C.; Sollberger, D.; Häusler, M.; Robertsson, J. O. A.

2017-12-01

Seismic spatial wavefield gradient and rotation data have the potential to open up new ways to address long-standing problems in land-seismic exploration such as identifying and separating P-, S-, and surface waves. Gradient-based acquisition and processing techniques could enable replacing large arrays of densely spaced receivers by sparse spatially-compact receiver layouts or even one single multicomponent station with dedicated instruments (e.g., rotational seismometers). Such approaches to maximize the information content of single-station recordings are also of significant interest for seismic measurements at sites with limited access such as boreholes, the sea bottom, and extraterrestrial seismology. Arrays of conventional three-component (3C) geophones enable measuring not only the particle velocity in three dimensions but also estimating their spatial gradients. Because the free-surface condition allows to express vertical derivatives in terms of horizontal derivatives, the full gradient tensor and, hence, curl and divergence of the wavefield can be computed. In total, three particle velocity components, three rotational components, and divergence, result seven-component (7C) seismic data. Combined particle velocity and gradient data can be used to isolate the incident P- or S-waves at the land surface or the sea bottom using filtering techniques based on the elastodynamic representation theorem. Alternatively, as only S-waves exhibit rotational motion, rotational measurements can directly be used to identify S-waves. We discuss the derivations of the gradient-based filters as well as their application to synthetic and field data, demonstrating that rotational data can be of particular interest to S-wave reflection and P-to-S-wave conversion imaging. The concept of array-derived gradient estimation can be extended to source arrays as well. Therefore, source arrays allow us to emulate rotational (curl) and dilatational (divergence) sources. Combined with 7C

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

Science.gov (United States)

Efron, Uzi (Editor)

1990-01-01

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Application of THz probe radiation in low-coherent tomographs based on spatially separated counterpropagating beams

Energy Technology Data Exchange (ETDEWEB)

Kuritsyn, I I; Shkurinov, A P; Nazarov, M M [Department of Physics, M.V. Lomonosov Moscow State University (Russian Federation); Mandrosov, V I [Moscow Institute of Physics and Technology (State University), Dolgoprudnyi, Moscow Region (Russian Federation); Cherkasova, O P [Institute of Laser Physics, Siberian Branch, Russian Academy of Sciences, Novosibirsk (Russian Federation)

2013-10-31

A principle of designing a high-resolution low-coherent THz tomograph, which makes it possible to investigate media with a high spatial resolution (in the range λ{sub 0} – 2λ{sub 0}, where λ{sub 0} is the average probe wavelength) is considered. The operation principle of this tomograph implies probing a medium by radiation with a coherence length of 8λ{sub 0} and recording a hologram of a focused image of a fixed layer of this medium using spatially separated counterpropagating object and reference beams. Tomograms of the medium studied are calculated using a temporal approach based on application of the time correlation function of probe radiation. (terahertz radiation)

Classical and spatial stochastic processes with applications to biology

CERN Document Server

Schinazi, Rinaldo B

2014-01-01

The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a f...

Pediatric and adolescent applications of the Taylor Spatial Frame.

Science.gov (United States)

Paloski, Michael; Taylor, Benjamin C; Iobst, Christopher; Pugh, Kevin J

2012-06-01

Limb deformity can occur in the pediatric and adolescent populations from multiple etiologies: congenital, traumatic, posttraumatic sequelae, oncologic, and infection. Correcting these deformities is important for many reasons. Ilizarov popularized external fixation to accomplish this task. Taylor expanded on this by designing an external fixator in 1994 with 6 telescoping struts that can be sequentially manipulated to achieve multiaxial correction of deformity without the need for hinges or operative frame alterations. This frame can be used to correct deformities in children and has shown good anatomic correction with minimal morbidity. The nature of the construct and length of treatment affects psychosocial factors that the surgeon and family must be aware of prior to treatment. An understanding of applications of the Taylor Spatial Frame gives orthopedic surgeons an extra tool to correct simple and complex deformities in pediatric and adolescent patients. Copyright 2012, SLACK Incorporated.

Mutual information spectrum for selection of event-related spatial components. Application to eloquent motor cortex mapping.

Directory of Open Access Journals (Sweden)

Alexei eOssadtchi

2014-01-01

Full Text Available Spatial component analysis is often used to explore multidimensional time series data whose sources cannot be measured directly. Several methods may be used to decompose the data into a set of spatial components with temporal loadings. Component selection is of crucial importance, and should be supported by objective criteria. In some applications, the use of a well defined component selection criterion may provide for automation of the analysis.In this paper we describe a novel approach for ranking of spatial components calculated from the EEG or MEG data recorded within evoked response paradigm. Our method is called Mutual Information Spectrum and is based on gauging the amount of mutual information of spatial component temporal loadings with a synthetically created reference signal. We also describe the appropriate randomization based statistical assessment scheme that can be used for selection of components with statistically significant amount of mutual information. Using simulated data with realistic trial to trial variations and SNR corresponding to the real recordings we demonstrate the superior performance characteristics of the described mutual information based measure as compared to a more conventionally used power driven gauge. We also demonstrate the application of the Mutual Information Spectrum for the selection of task-related independent components from real MEG data. We show that the Mutual Information spectrum allows to identify task-related components reliably in a consistent fashion, yielding stable results even from a small number of trials. We conclude that the proposed method fits naturally the information driven nature of ICA and can be used for routine and automatic ranking of independent components calculated from the functional neuroimaging data collected within event-related paradigms.

Asset management -- Integrated software optimizes production performance

International Nuclear Information System (INIS)

Polczer, S.

1998-01-01

Developments in data collection and retrieval systems to allow timely cost analysis, financial reporting and production management are discussed. One of the most important new OLAP (on-line analytical processing) products is Energy Warehouse which gathers field information from various sources, allows advanced searches, and generates reports previously unavailable in other conventional financial accounting systems. Another OLAP-based system, the Canadian Upstream Energy System (CUES), was developed by the Oracle Corporation and the Calgary-based Applied Terravision Systems (ATS) Inc. CUES combines Oracle's universal data server software development tools with ATS's upstream financial, land, geotechnical and production applications. ATS also developed a product called IDPMARS (Integrated Daily Production Management Accounting Reporting System). It interfaces with CUES to link working interests, government royalties, administration, facility charges, lifting costs, transportation tooling, and customers by integrating field data collection systems with financial accounting

Asset management -- Integrated software optimizes production performance

Energy Technology Data Exchange (ETDEWEB)

Polczer, S.

1998-10-01

Developments in data collection and retrieval systems to allow timely cost analysis, financial reporting and production management are discussed. One of the most important new OLAP (on-line analytical processing) products is Energy Warehouse which gathers field information from various sources, allows advanced searches, and generates reports previously unavailable in other conventional financial accounting systems. Another OLAP-based system, the Canadian Upstream Energy System (CUES), was developed by the Oracle Corporation and the Calgary-based Applied Terravision Systems (ATS) Inc. CUES combines Oracle`s universal data server software development tools with ATS`s upstream financial, land, geotechnical and production applications. ATS also developed a product called IDPMARS (Integrated Daily Production Management Accounting Reporting System). It interfaces with CUES to link working interests, government royalties, administration, facility charges, lifting costs, transportation tooling, and customers by integrating field data collection systems with financial accounting.

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

Science.gov (United States)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

Application of spatially resolved high resolution crystal spectrometry to inertial confinement fusion plasmas.

Science.gov (United States)

Hill, K W; Bitter, M; Delgado-Aparacio, L; Pablant, N A; Beiersdorfer, P; Schneider, M; Widmann, K; Sanchez del Rio, M; Zhang, L

2012-10-01

High resolution (λ∕Δλ ∼ 10 000) 1D imaging x-ray spectroscopy using a spherically bent crystal and a 2D hybrid pixel array detector is used world wide for Doppler measurements of ion-temperature and plasma flow-velocity profiles in magnetic confinement fusion plasmas. Meter sized plasmas are diagnosed with cm spatial resolution and 10 ms time resolution. This concept can also be used as a diagnostic of small sources, such as inertial confinement fusion plasmas and targets on x-ray light source beam lines, with spatial resolution of micrometers, as demonstrated by laboratory experiments using a 250-μm (55)Fe source, and by ray-tracing calculations. Throughput calculations agree with measurements, and predict detector counts in the range 10(-8)-10(-6) times source x-rays, depending on crystal reflectivity and spectrometer geometry. Results of the lab demonstrations, application of the technique to the National Ignition Facility (NIF), and predictions of performance on NIF will be presented.

A spatial haplotype copying model with applications to genotype imputation.

Science.gov (United States)

Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan

2015-05-01

Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

Comparison of Spatial Interpolation Schemes for Rainfall Data and Application in Hydrological Modeling

Directory of Open Access Journals (Sweden)

Tao Chen

2017-05-01

Full Text Available The spatial distribution of precipitation is an important aspect of water-related research. The use of different interpolation schemes in the same catchment may cause large differences and deviations from the actual spatial distribution of rainfall. Our study analyzes different methods of spatial rainfall interpolation at annual, daily, and hourly time scales to provide a comprehensive evaluation. An improved regression-based scheme is proposed using principal component regression with residual correction (PCRR and is compared with inverse distance weighting (IDW and multiple linear regression (MLR interpolation methods. In this study, the meso-scale catchment of the Fuhe River in southeastern China was selected as a typical region. Furthermore, a hydrological model HEC-HMS was used to calculate streamflow and to evaluate the impact of rainfall interpolation methods on the results of the hydrological model. Results show that the PCRR method performed better than the other methods tested in the study and can effectively eliminate the interpolation anomalies caused by terrain differences between observation points and surrounding areas. Simulated streamflow showed different characteristics based on the mean, maximum, minimum, and peak flows. The results simulated by PCRR exhibited the lowest streamflow error and highest correlation with measured values at the daily time scale. The application of the PCRR method is found to be promising because it considers multicollinearity among variables.

Geomorphology and spatial planning

Directory of Open Access Journals (Sweden)

Matija Zorn

2006-01-01

Full Text Available Applicability of geomorphological knowledge for prevention against some natural disasters, also known as geomorphological disasters, is presented. Some home and foreign experience of applicability of this knowledge are introduced. It is known that the ratio between means put into sanitation of, for example, landslides and savings with prevention measures, are from 1:10 to 1:2.000. The use of geomorpholgical knowledge and corresponding cartographic works in Slovene spatial planning legislation is defined, but it is not carried out consistently. We recommend municipalities and spatial planners that they should also take in account geomorphic processes and characteristic of the relief.

Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems

Science.gov (United States)

Downie, John D.; Goodman, Joseph W.

1989-10-01

The accuracy requirements of optical processors in adaptive optics systems are determined by estimating the required accuracy in a general optical linear algebra processor (OLAP) that results in a smaller average residual aberration than that achieved with a conventional electronic digital processor with some specific computation speed. Special attention is given to an error analysis of a general OLAP with regard to the residual aberration that is created in an adaptive mirror system by the inaccuracies of the processor, and to the effect of computational speed of an electronic processor on the correction. Results are presented on the ability of an OLAP to compete with a digital processor in various situations.

Optical linear algebra processors - Noise and error-source modeling

Science.gov (United States)

Casasent, D.; Ghosh, A.

1985-01-01

The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.

Optical linear algebra processors: noise and error-source modeling.

Science.gov (United States)

Casasent, D; Ghosh, A

1985-06-01

The modeling of system and component noise and error sources in optical linear algebra processors (OLAP's) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.

DESIGN AND CONSTRUCTION OF A FOREST SPATIAL DATABASE: AN APPLICATION

Directory of Open Access Journals (Sweden)

Turan Sönmez

2006-11-01

Full Text Available General Directorate of Forests (GDF has not yet created the spatial forest database to manage forest and catch the developed countries in forestry. The lack of spatial forest database results in collection of the spatial data redundancy, communication problems among the forestry organizations. Also it causes Turkish forestry to be backward of informatics’ era. To solve these problems; GDF should establish spatial forest database supported Geographic Information System (GIS. To design the spatial database, supported GIS, which provides accurate, on time and current data/info for decision makers and operators in forestry, and to develop sample interface program to apply and monitor classical forest management plans is paramount in contemporary forest management planning process. This research is composed of three major stages: (i spatial rototype database design considering required by the three hierarchical organizations of GDF (regional directorate of forests, forest enterprise, and territorial division, (ii user interface program developed to apply and monitor classical management plans based on the designed database, (iii the implementation of the designed database and its user interface in Artvin Central Planning Unit.

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

Science.gov (United States)

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

2017-12-01

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

Lectures on Topics in Spatial Stochastic Processes

CERN Document Server

Capasso, Vincenzo; Ivanoff, B Gail; Dozzi, Marco; Dalang, Robert C; Mountford, Thomas S

2003-01-01

The theory of stochastic processes indexed by a partially ordered set has been the subject of much research over the past twenty years. The objective of this CIME International Summer School was to bring to a large audience of young probabilists the general theory of spatial processes, including the theory of set-indexed martingales and to present the different branches of applications of this theory, including stochastic geometry, spatial statistics, empirical processes, spatial estimators and survival analysis. This theory has a broad variety of applications in environmental sciences, social sciences, structure of material and image analysis. In this volume, the reader will find different approaches which foster the development of tools to modelling the spatial aspects of stochastic problems.

Handling Imprecision in Qualitative Data Warehouse: Urban Building Sites Annoyance Analysis Use Case

Science.gov (United States)

Amanzougarene, F.; Chachoua, M.; Zeitouni, K.

2013-05-01

Data warehouse means a decision support database allowing integration, organization, historisation, and management of data from heterogeneous sources, with the aim of exploiting them for decision-making. Data warehouses are essentially based on multidimensional model. This model organizes data into facts (subjects of analysis) and dimensions (axes of analysis). In classical data warehouses, facts are composed of numerical measures and dimensions which characterize it. Dimensions are organized into hierarchical levels of detail. Based on the navigation and aggregation mechanisms offered by OLAP (On-Line Analytical Processing) tools, facts can be analyzed according to the desired level of detail. In real world applications, facts are not always numerical, and can be of qualitative nature. In addition, sometimes a human expert or learned model such as a decision tree provides a qualitative evaluation of phenomenon based on its different parameters i.e. dimensions. Conventional data warehouses are thus not adapted to qualitative reasoning and have not the ability to deal with qualitative data. In previous work, we have proposed an original approach of qualitative data warehouse modeling, which permits integrating qualitative measures. Based on computing with words methodology, we have extended classical multidimensional data model to allow the aggregation and analysis of qualitative data in OLAP environment. We have implemented this model in a Spatial Decision Support System to help managers of public spaces to reduce annoyances and improve the quality of life of the citizens. In this paper, we will focus our study on the representation and management of imprecision in annoyance analysis process. The main objective of this process consists in determining the least harmful scenario of urban building sites, particularly in dense urban environments.

Correlation of Spatially Filtered Dynamic Speckles in Distance Measurement Application

International Nuclear Information System (INIS)

Semenov, Dmitry V.; Nippolainen, Ervin; Kamshilin, Alexei A.; Miridonov, Serguei V.

2008-01-01

In this paper statistical properties of spatially filtered dynamic speckles are considered. This phenomenon was not sufficiently studied yet while spatial filtering is an important instrument for speckles velocity measurements. In case of spatial filtering speckle velocity information is derived from the modulation frequency of filtered light power which is measured by photodetector. Typical photodetector output is represented by a narrow-band random noise signal which includes non-informative intervals. Therefore more or less precious frequency measurement requires averaging. In its turn averaging implies uncorrelated samples. However, conducting research we found that correlation is typical property not only of dynamic speckle patterns but also of spatially filtered speckles. Using spatial filtering the correlation is observed as a response of measurements provided to the same part of the object surface or in case of simultaneously using several adjacent photodetectors. Found correlations can not be explained using just properties of unfiltered dynamic speckles. As we demonstrate the subject of this paper is important not only from pure theoretical point but also from the point of applied speckle metrology. E.g. using single spatial filter and an array of photodetector can greatly improve accuracy of speckle velocity measurements

Automating the Analysis of Spatial Grids A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications

CERN Document Server

Lakshmanan, Valliappa

2012-01-01

The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.

SQL based cardiovascular ultrasound image classification.

Science.gov (United States)

Nandagopalan, S; Suryanarayana, Adiga B; Sudarshan, T S B; Chandrashekar, Dhanalakshmi; Manjunath, C N

2013-01-01

This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables (NBCD) with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables (NBCC) using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.

An API for Integrating Spatial Context Models with Spatial Reasoning Algorithms

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun

2006-01-01

The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible...... and can help reduce the complexity of algorithms making them easier to maintain and develop. This paper propose an object-oriented API for context models of the physical environment and extensions to a location modeling approach called geometric space trees for it to provide adequate support for location...... modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms....

GSHR-Tree: a spatial index tree based on dynamic spatial slot and hash table in grid environments

Science.gov (United States)

Chen, Zhanlong; Wu, Xin-cai; Wu, Liang

2008-12-01

Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are made possible by high-speed networks and a new generation of Grid middleware that resides between networks and traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the

A spatial application of a vegetation productivity equation for neo-soil reconstruction

International Nuclear Information System (INIS)

Burley, J.B.

1999-01-01

Reclamation specialists are interested in the application of recently developed soil productivity equations for post-mining reclamation planning and design. This paper presents the application of one recently developed soil productivity equation to a surface coal mine site in Mercer County, North Dakota. Geographic information systems (GIS) technology (Map*Factory 1.1) was combined with a soil productivity equation developed by the author to generate a GIS script to calculate a site's pre-mining productivity per 10 meter grid cell and then summed to calculate the grand and the expected average soil productivity for the site, resulting in a pre-mining baseline numerical spatial scores. Several post-mining alternatives were evaluated to study various soil management strategies to restore post-mining soil productivity, including: an abandoned mine landscape treatment, a reconstructed topsoil treatment with graded gentile slopes, and a reconstructed topsoil treatment with soil improvements. The results indicated that the abandoned mine scenario was significantly different than the other three treatments (ple0.05), with the reconstructed topsoil treatment with soil amendments generating the greatest estimated productivity

Application of XML in real-time data warehouse

Science.gov (United States)

Zhao, Yanhong; Wang, Beizhan; Liu, Lizhao; Ye, Su

2009-07-01

At present, XML is one of the most widely-used technologies of data-describing and data-exchanging, and the needs for real-time data make real-time data warehouse a popular area in the research of data warehouse. What effects can we have if we apply XML technology to the research of real-time data warehouse? XML technology solves many technologic problems which are impossible to be addressed in traditional real-time data warehouse, and realize the integration of OLAP (On-line Analytical Processing) and OLTP (Online transaction processing) environment. Then real-time data warehouse can truly be called "real time".

Towards Hydrological Applications of Stationary and Roving Cosmic-Ray Neutron Sensors in the Light of Spatial Sensitivity

Science.gov (United States)

Schrön, M.; Köhli, M.; Rosolem, R.; Baroni, G.; Bogena, H. R.; Brenner, J.; Zink, M.; Rebmann, C.; Oswald, S. E.; Dietrich, P.; Samaniego, L. E.; Zacharias, S.

2017-12-01

Cosmic-Ray Neutron Sensing (CRNS) has become a promising and unique method to monitor water content at an effective scale of tens of hectares in area and tens of centimeters in depth. The large footprint is particularly beneficial for hydrological models that operate at these scales.However, reliable estimates of average soil moisture require a detailed knowledge about the sensitivity of the signal to spatial inhomogeneity within the footprint. From this perspective, the large integrating volume challenges data interpretation, validation, and calibration of the sensor. Can we still generate reliable data for hydrological applications? One of the top challenges in the last years was to find out where the signal comes from, and how sensitive it is to spatial variabilities of moisture. Neutron physics simulations have shown that the neutron signal represents a non-linearly weighted average of soil water in the footprint. With the help of the so-called spatial sensitivity functions it is now possible to quantify the contribution of certain regions to the neutron signal. We present examples of how this knowledge can help (1) to understand the contribution of irrigated and sealed areas in the footprint, (2) to improve calibration and validation of the method, and (3) to even reveal excess water storages, e.g. from ponding or rain interception.The spatial sensitivity concept can also explain the influence of dry roads on the neutron signal. Mobile surveys with the CRNS rover have been a common practice to measure soil moisture patterns at the kilometer scale. However, dedicated experiments across agricultural fields in Germany and England have revealed that field soil moisture is significantly underestimated when moving the sensor on roads. We show that knowledge about the spatial sensitivity helps to correct survey data for these effects, depending on road material, width, and distance from the road. The recent methodological advances allow for improved signal

A free software tool for the development of decision support systems

Directory of Open Access Journals (Sweden)

COLONESE, G

2008-06-01

Full Text Available This article describes PostGeoOlap, a free software open source tool for decision support that integrates OLAP (On-Line Analytical Processing and GIS (Geographical Information Systems. Besides describing the tool, we show how it can be used to achieve effective and low cost decision support that is adequate for small and medium companies and for small public offices.

Bayesian spatial transformation models with applications in neuroimaging data.

Science.gov (United States)

Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

2013-12-01

The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

Application and Analysis of Measurement Model for Calibrating Spatial Shear Surface in Triaxial Test

Science.gov (United States)

Zhang, Zhihua; Qiu, Hongsheng; Zhang, Xiedong; Zhang, Hang

2017-12-01

Discrete element method has great advantages in simulating the contacts, fractures, large displacement and deformation between particles. In order to analyze the spatial distribution of the shear surface in the three-dimensional triaxial test, a measurement model is inserted in the numerical triaxial model which is generated by weighted average assembling method. Due to the non-visibility of internal shear surface in laboratory, it is largely insufficient to judge the trend of internal shear surface only based on the superficial cracks of sheared sample, therefore, the measurement model is introduced. The trend of the internal shear zone is analyzed according to the variations of porosity, coordination number and volumetric strain in each layer. It shows that as a case study on confining stress of 0.8 MPa, the spatial shear surface is calibrated with the results of the rotated particle distribution and the theoretical value with the specific characteristics of the increase of porosity, the decrease of coordination number, and the increase of volumetric strain, which represents the measurement model used in three-dimensional model is applicable.

A Compact "Water Window" Microscope with 60 nm Spatial Resolution for Applications in Biology and Nanotechnology.

Science.gov (United States)

Wachulak, Przemyslaw; Torrisi, Alfio; Nawaz, Muhammad F; Bartnik, Andrzej; Adjei, Daniel; Vondrová, Šárka; Turňová, Jana; Jančarek, Alexandr; Limpouch, Jiří; Vrbová, Miroslava; Fiedorowicz, Henryk

2015-10-01

Short illumination wavelength allows an extension of the diffraction limit toward nanometer scale; thus, improving spatial resolution in optical systems. Soft X-ray (SXR) radiation, from "water window" spectral range, λ=2.3-4.4 nm wavelength, which is particularly suitable for biological imaging due to natural optical contrast provides better spatial resolution than one obtained with visible light microscopes. The high contrast in the "water window" is obtained because of selective radiation absorption by carbon and water, which are constituents of the biological samples. The development of SXR microscopes permits the visualization of features on the nanometer scale, but often with a tradeoff, which can be seen between the exposure time and the size and complexity of the microscopes. Thus, herein, we present a desk-top system, which overcomes the already mentioned limitations and is capable of resolving 60 nm features with very short exposure time. Even though the system is in its initial stage of development, we present different applications of the system for biology and nanotechnology. Construction of the microscope with recently acquired images of various samples will be presented and discussed. Such a high resolution imaging system represents an interesting solution for biomedical, material science, and nanotechnology applications.

Development and Application of a Planning Support System for Regional Spatial Functional Zoning Based on GIS

Directory of Open Access Journals (Sweden)

Xiaorui Zhang

2016-09-01

Full Text Available Regional spatial functional zoning in China is a large-scale strategic planning and requires very advanced planning decision support technology. With respect to spatial functional zoning, the planning support system (PSS is introduced as one of the most popular computer aided planning systems at the present time in this paper, and is further explained with the example of the latest regional main functional area (RMFA planning in China. On the Visual Studio.NET visualization development platform, the planning decision model, planning decision method, and GIS are organically integrated and customized by using the component-type secondary development technology of the ArcGIS Engine with the development language VB.NET. Hence, a highly efficient and flexible planning support system of regional main functional areas (RMFA-PSS is established. It was adopted in the research of the Beijing–Tianjin area in China and accordingly two types of main functional area planning are acquired. The RMFA-PSS offers an efficient and flexible decision support with regard to RMFA planning. The research can provide a reference for further PSS development and applications related to other types of spatial functional zoning.

Метод концептуального OLAP-моделирования на основе формального концептуального анализа

OpenAIRE

Коробко, А.; Пенькова, Т.

2010-01-01

Предложен метод концептуального OLAP-моделирования предметной области. Представлено описание процесса построения интегральной аналитической модели в виде формальной концептуальной решетки OLAP-кубов. Применение концептуальной OLAP-модели позволяет повысить эффективность оперативной аналитической обработки многомерных данных. Выполнено построение концептуальной аналитической модели научной деятельности организации на основе предложенного метода....

Multivariate Max-Stable Spatial Processes

KAUST Repository

Genton, Marc G.

2014-01-06

Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.

Multivariate Max-Stable Spatial Processes

KAUST Repository

Genton, Marc G.

2014-01-01

Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.

Metal Amorphous Nanocomposite (MANC) Alloy Cores with Spatially Tuned Permeability for Advanced Power Magnetics Applications

Science.gov (United States)

Byerly, K.; Ohodnicki, P. R.; Moon, S. R.; Leary, A. M.; Keylin, V.; McHenry, M. E.; Simizu, S.; Beddingfield, R.; Yu, Y.; Feichter, G.; Noebe, R.; Bowman, R.; Bhattacharya, S.

2018-06-01

Metal amorphous nanocomposite (MANC) alloys are an emerging class of soft magnetic materials showing promise for a range of inductive components targeted for higher power density and higher efficiency power conversion applications including inductors, transformers, and rotating electrical machinery. Magnetization reversal mechanisms within these alloys are typically determined by composition optimization as well as controlled annealing treatments to generate a nanocomposite structure composed of nanocrystals embedded in an amorphous precursor. Here we demonstrate the concept of spatially varying the permeability within a given component for optimization of performance by using the strain annealing process. The concept is realized experimentally through the smoothing of the flux profile from the inner to outer core radius achieved by a monotonic variation in tension during the strain annealing process. Great potential exists for an extension of this concept to a wide range of other power magnetic components and more complex spatially varying permeability profiles through advances in strain annealing techniques and controls.

Empirical Mode Decomposition on the sphere: application to the spatial scales of surface temperature variations

Directory of Open Access Journals (Sweden)

N. Fauchereau

2008-06-01

Full Text Available Empirical Mode Decomposition (EMD is applied here in two dimensions over the sphere to demonstrate its potential as a data-adaptive method of separating the different scales of spatial variability in a geophysical (climatological/meteorological field. After a brief description of the basics of the EMD in 1 then 2 dimensions, the principles of its application on the sphere are explained, in particular via the use of a zonal equal area partitioning. EMD is first applied to an artificial dataset, demonstrating its capability in extracting the different (known scales embedded in the field. The decomposition is then applied to a global mean surface temperature dataset, and we show qualitatively that it extracts successively larger scales of temperature variations related, for example, to topographic and large-scale, solar radiation forcing. We propose that EMD can be used as a global data-adaptive filter, which will be useful in analysing geophysical phenomena that arise as the result of forcings at multiple spatial scales.

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

Science.gov (United States)

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the

Characteristics and Classification of Topological Spatial Relations in 3-D Cadasters

Directory of Open Access Journals (Sweden)

Lili Fu

2018-03-01

Full Text Available The application of a 3-D topology to cadasters is becoming increasingly important as 3-D cadasters continue to develop and cadastral data applications increase. This study discusses spatial topological relations related to 3-D cadasters, the geometric objects used in 3-D cadastral spatial modelling, and the characteristics of the spatial data. The characteristics of the topological relations for a 3-D cadaster are summarized, and a classification method is proposed. Research on the classification of topological spatial relations in 3-D cadasters provides guidance for the analysis and computation of the topological spatial relations, changing of cadastral parcels, and topological consistency in cadastral spatial data.

A similarity-based data warehousing environment for medical images.

Science.gov (United States)

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Early non-destructive biofouling detection and spatial distribution: Application of oxygen sensing optodes

KAUST Repository

Farhat, Nadia

2015-06-11

Biofouling is a serious problem in reverse osmosis/nanofiltration (RO/NF) applications, reducing membrane performance. Early detection of biofouling plays an essential role in an adequate anti-biofouling strategy. Presently, fouling of membrane filtration systems is mainly determined by measuring changes in pressure drop, which is not exclusively linked to biofouling. Non-destructive imaging of oxygen concentrations (i) is specific for biological activity of biofilms and (ii) may enable earlier detection of biofilm accumulation than pressure drop. The objective of this study was to test whether transparent luminescent planar O2 optodes, in combination with a simple imaging system, can be used for early non-destructive biofouling detection. This biofouling detection is done by mapping the two-dimensional distribution of O2 concentrations and O2 decrease rates inside a membrane fouling simulator (MFS). Results show that at an early stage, biofouling development was detected by the oxygen sensing optodes while no significant increase in pressure drop was yet observed. Additionally, optodes could detect spatial heterogeneities in biofouling distribution at a micro scale. Biofilm development started mainly at the feed spacer crossings. The spatial and quantitative information on biological activity will lead to better understanding of the biofouling processes, contributing to the development of more effective biofouling control strategies.

Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

Science.gov (United States)

Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

2014-01-01

To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

Rancang Bangun Sistem Business Intelligence Universitas Sebagai Pendukung Pengambilan Keputusan Akademik

Directory of Open Access Journals (Sweden)

Zainal Arifin

2016-01-01

Full Text Available Sistem business intelligence universitas dimulai dengan tahapan integrasi data, analisis data, membuat laporan dan membuatweb portal dan kemudian mengitegrasikan laporan tersebut dengan web portal. Analisis data diolah dengan OLAP, KPI dandata mining untuk mengekstrak informasi dari data yang tersimpan didalam data warehouse. Hasil proses analisis datatersebut di representasikan dalam bentuk laporan statistik dan dashboard, kemudian digunakan sebagai pendukungpengambilan keputusan akademik. Penelitian ini bertujuan merancang bangun sistem business intelligence universitassebagai pendukung pengambilan keputusan akademik pada Universitas Mulawarman berbasis web dengan OLAP. Penelitianini menghasilkan kerangka sistem dan web portal sistem business intelligence universitas yang diakses melalui browsersecara online. Business Intelligence dapat digunakan sebagai solusi untuk mempertimbangkan proses pengambilan keputusandalam pengelolaan universitas dan solusi dalam peningkatan kinerja pengelolaan akademik untuk mencapai keunggulanakademik.Kata kunci : Business Intelligence; Data warehouse; OLAP; KPI; Data mining

Extending Practical Pre-Aggregation in On-Line Analytical Processing

DEFF Research Database (Denmark)

Pedersen, Torben Bach; Jensen, Christian Søndergaard; Dyreson, Curtis E.

On-Line Analytical Processing (OLAP) based on a dimensional view of data is being used increasingly in traditional business applications as well as in applications such as health care for the purpose of analyzing very large amounts of data. Pre-aggregation, the prior materialization of aggregate...... select combinations of aggregates and then re-use these for efficiently computing other aggregates. However, this re-use of aggregates is contingent on the dimension hierarchies and the relationships between facts and dimensions satisfying stringent constraints. This severely limits the scope...

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

Science.gov (United States)

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

2015-01-01

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

Spatial Domain Adaptive Control of Nonlinear Rotary Systems Subject to Spatially Periodic Disturbances

Directory of Open Access Journals (Sweden)

Yen-Hsiu Yang

2012-01-01

Full Text Available We propose a generic spatial domain control scheme for a class of nonlinear rotary systems of variable speeds and subject to spatially periodic disturbances. The nonlinear model of the rotary system in time domain is transformed into one in spatial domain employing a coordinate transformation with respect to angular displacement. Under the circumstances that measurement of the system states is not available, a nonlinear state observer is established for providing the estimated states. A two-degree-of-freedom spatial domain control configuration is then proposed to stabilize the system and improve the tracking performance. The first control module applies adaptive backstepping with projected parametric update and concentrates on robust stabilization of the closed-loop system. The second control module introduces an internal model of the periodic disturbances cascaded with a loop-shaping filter, which not only further reduces the tracking error but also improves parametric adaptation. The overall spatial domain output feedback adaptive control system is robust to model uncertainties and state estimated error and capable of rejecting spatially periodic disturbances under varying system speeds. Stability proof of the overall system is given. A design example with simulation demonstrates the applicability of the proposed design.

Toward seamless hydrologic predictions across spatial scales

NARCIS (Netherlands)

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

2017-01-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the

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...

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.

Data Warehousing at the Marine Corps Institute

Science.gov (United States)

2003-09-01

applications exists for several reasons. It allows for data to be extracted from many sources, by “cleaned”, and stored into one large data facility ...exists. Key individuals at MCI, or the so called “knowledge workers” will be educated , and try to brainstorm possible data relationships that can...They include querying and reporting, On-Line Analytical Processing (OLAP) and statistical analysis, and data mining. 1. Queries and Reports The

Spatial extreme learning machines: An application on prediction of disease counts.

Science.gov (United States)

Prates, Marcos O

2018-01-01

Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing information making statistical analysis harder or unfeasible. In this paper, we present a new model, coined spatial extreme learning machine, that combine spatial modeling with extreme learning machines keeping the nice properties of both methodologies and making it very flexible and robust. As explained throughout the text, the spatial extreme learning machines have many advantages in comparison with the traditional extreme learning machines. By a simulation study and a real data analysis we present how the spatial extreme learning machine can be used to improve imputation of missing data and uncertainty prediction estimation.

Application of validation data for assessing spatial interpolation methods for 8-h ozone or other sparsely monitored constituents

International Nuclear Information System (INIS)

Joseph, John; Sharif, Hatim O.; Sunil, Thankam; Alamgir, Hasanat

2013-01-01

The adverse health effects of high concentrations of ground-level ozone are well-known, but estimating exposure is difficult due to the sparseness of urban monitoring networks. This sparseness discourages the reservation of a portion of the monitoring stations for validation of interpolation techniques precisely when the risk of overfitting is greatest. In this study, we test a variety of simple spatial interpolation techniques for 8-h ozone with thousands of randomly selected subsets of data from two urban areas with monitoring stations sufficiently numerous to allow for true validation. Results indicate that ordinary kriging with only the range parameter calibrated in an exponential variogram is the generally superior method, and yields reliable confidence intervals. Sparse data sets may contain sufficient information for calibration of the range parameter even if the Moran I p-value is close to unity. R script is made available to apply the methodology to other sparsely monitored constituents. -- Highlights: •Spatial interpolation methods were tested for thousands of sparse ozone data sets. •A particular single-parameter ordinary kriging was found to be generally superior. •A Moran I p-value in the training set is not helpful in selecting the method. •The sum of the squares of the residuals is helpful in selecting the method. •R script is available for application to other sites and constituents. -- Spatial interpolation methods were compared for thousands of subsets of data for 8-h ozone using R script applicable to other constituents as well, and available from the authors

Spatial Game Analytics and Visualization

DEFF Research Database (Denmark)

Drachen, Anders; Schubert, Matthias

2013-01-01

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

Use of Radcube for extraction of finding trends in a large radiology practice.

Science.gov (United States)

Dang, Pragya A; Kalra, Mannudeep K; Blake, Michael A; Schultz, Thomas J; Stout, Markus; Halpern, Elkan F; Dreyer, Keith J

2009-12-01

The purpose of our study was to demonstrate the use of Natural Language Processing (Leximer), along with Online Analytic Processing, (NLP-OLAP), for extraction of finding trends in a large radiology practice. Prior studies have validated the Natural Language Processing (NLP) program, Leximer for classifying unstructured radiology reports based on the presence of positive radiology findings (F (POS)) and negative radiology findings (F (NEG)). The F (POS) included new relevant radiology findings and any change in status from prior imaging. Electronic radiology reports from 1995-2002 and data from analysis of these reports with NLP-Leximer were saved in a data warehouse and exported to a multidimensional structure called the Radcube. Various relational queries on the data in the Radcube were performed using OLAP technique. Thus, NLP-OLAP was applied to determine trends of F (POS) in different radiology exams for different patient and examination attributes. Pivot tables were exported from NLP-OLAP interface to Microsoft Excel for statistical analysis. Radcube allowed rapid and comprehensive analysis of F (POS) and F (NEG) trends in a large radiology report database. Trends of F (POS) were extracted for different patient attributes such as age groups, gender, clinical indications, diseases with ICD codes, patient types (inpatient, ambulatory), imaging characteristics such as imaging modalities, referring physicians, radiology subspecialties, and body regions. Data analysis showed substantial differences between F (POS) rates for different imaging modalities ranging from 23.1% (mammography, 49,163/212,906) to 85.8% (nuclear medicine, 93,852/109,374; p OLAP can help in analysis of yield of different radiology exams from a large radiology report database.

Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium

Directory of Open Access Journals (Sweden)

G. Heuvelmans

2004-01-01

Full Text Available Operational applications of a hydrological model often require the prediction of stream flow in (future time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders, with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the

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

Science.gov (United States)

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

2009-07-01

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

Semantic Metadata for Heterogeneous Spatial Planning Documents

Science.gov (United States)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Database modeling and design logical design

CERN Document Server

Teorey, Toby J; Nadeau, Tom; Jagadish, HV

2011-01-01

Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fifth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rules

Database modeling and design logical design

CERN Document Server

Teorey, Toby J; Nadeau, Tom; Jagadish, HV

2005-01-01

Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fourth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rul

The spatial and temporal behavior of brightness temperature in Tel-Aviv and its application to air temperature monitoring

Science.gov (United States)

Pelta, Ran; Chudnovsky, A. Alexandra; Schwarts, Joel

2016-01-01

This study applies remote sensing technology to assess and examine the spatial and temporal Brightness Temperature (BT) profile in the city of Tel-Aviv, Israel over the last 30 years using Landsat imagery. The location of warmest and coldest zones are constant over the studied period. Distinct diurnal and temporal BT behavior divide the city into four different segments. As an example of future application, we applied mixed regression models with daily random slopes to correlate Landsat BT data with monitored air temperature (Tair) measurements using 14 images for 1989–2014. Our preliminary results show a good model performance with R2 = 0.81. Furthermore, based on the model’s results, we analyzed the spatial profile of Tair within the study domain for representative days. PMID:26499933

Towards models of strategic spatial choice behaviour: theory and application issues

NARCIS (Netherlands)

Han, Q.; Timmermans, H.J.P.

2005-01-01

Models of spatial choice behaviour have been around in urban planning for decades to assess the feasibility of planning actions or to predict external (competition) effects on existing destinations. The well known spatial interaction models of the 1970s have gradually been replaced by discrete

Spatial pattern of 2009 dengue distribution in Kuala Lumpur using GIS application.

Science.gov (United States)

Aziz, S; Ngui, R; Lim, Y A L; Sholehah, I; Nur Farhana, J; Azizan, A S; Wan Yusoff, W S

2012-03-01

In the last few years in Malaysia, dengue fever has increased dramatically and has caused huge public health concerns. The present study aimed to establish a spatial distribution of dengue cases in the city of Kuala Lumpur using a combination of Geographic Information System (GIS) and spatial statistical tools. Collation of data from 1,618 dengue cases in 2009 was obtained from Kuala Lumpur City Hall (DBKL). These data were processed and then converted into GIS format. Information on the average monthly rainfall was also used to correlate with the distribution pattern of dengue cases. To asses the spatial distribution of dengue cases, Average Nearest Neighbor (ANN) Analysis was applied together with spatial analysis with the ESRI ArcGIS V9.3 programme. Results indicated that the distribution of dengue cases in Kuala Lumpur for the year 2009 was spatially clustered with R value less than 1 (R = 0.42; z-scores = - 4.47; p 1) between August and November. In addition, the mean monthly rainfall has not influenced the distribution pattern of the dengue cases. Implementation of control measures is more difficult for dispersed pattern compared to clustered pattern. From this study, it was found that distribution pattern of dengue cases in Kuala Lumpur in 2009 was spatially distributed (dispersed or clustered) rather than cases occurring randomly. It was proven that by using GIS and spatial statistic tools, we can determine the spatial distribution between dengue and population. Utilization of GIS tools is vital in assisting health agencies, epidemiologist, public health officer, town planner and relevant authorities in developing efficient control measures and contingency programmes to effectively combat dengue fever.

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

Directory of Open Access Journals (Sweden)

Yi Weng

2016-08-01

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

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

Science.gov (United States)

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

2016-01-01

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

Spatial cluster detection using dynamic programming

Directory of Open Access Journals (Sweden)

Sverchkov Yuriy

2012-03-01

Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic

Bayesian Spatial Modelling with R-INLA

Directory of Open Access Journals (Sweden)

Finn Lindgren

2015-02-01

Full Text Available The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA approach proposed by Rue, Martino, and Chopin (2009 is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized linear mixed to spatial and spatio-temporal models. Combined with the stochastic partial differential equation approach (SPDE, Lindgren, Rue, and Lindstrm 2011, one can accommodate all kinds of geographically referenced data, including areal and geostatistical ones, as well as spatial point process data. The implementation interface covers stationary spatial mod- els, non-stationary spatial models, and also spatio-temporal models, and is applicable in epidemiology, ecology, environmental risk assessment, as well as general geostatistics.

Preliminary Development of the MARS/FREK Spatial Kinetics Coupled System Code for Square Fueled Fast Reactor Applications

International Nuclear Information System (INIS)

Bae, Moo Hoon; Joo, Han Gyu

2009-01-01

Incorporation of a three-dimensional (3-D) reactor kinetics model into a system thermal-hydraulic (T/H) code enhances the capability to perform realistic analyses of the core neutronic behavior and the plant system dynamics which are coupled each other. For this advantage, several coupled system T/H and spatial kinetics codes, such as RELAP/PARCS, RELAP5/ PANBOX, and MARS/MASTER have been developed. These codes, however, so far limited to LWR applications. The objective of this work is to develop such a coupled code for fast reactor applications. Particularly, applications to lead-bismuth eutectic (LBE) cooled fast reactor are of interest which employ open square lattices. A fast reactor kinetics code applicable to square fueled cores called FREK is coupled the LBE version of the MARS code. The MARS/MASTER coupled code is used as the reference for the integration. The coupled code MARS/FREK is examined for a conceptual reactor called P-DEMO which is being developed by NUTRECK. In order to check the validity of the coupled code, however, the OECD MSLB benchmark exercise III calculation is solved first

Pengembangan Data Warehouse Menggunakan Pendekatan Data-Driven untuk Membantu Pengelolaan SDM

Directory of Open Access Journals (Sweden)

Mujiono Mujiono

2016-01-01

Full Text Available The basis of bureaucratic reform is the reform of human resources management. One supporting factor is the development of an employee database. To support the management of human resources required including data warehouse and business intelligent tools. The data warehouse is an integrated concept of reliable data storage to provide support to all the needs of the data analysis. In this study developed a data warehouse using the data-driven approach to the source data comes from SIMPEG, SAPK and electronic presence. Data warehouses are designed using the nine steps methodology and unified modeling language (UML notation. Extract transform load (ETL is done by using Pentaho Data Integration by applying transformation maps. Furthermore, to help human resource management, the system is built to perform online analytical processing (OLAP to facilitate web-based information. In this study generated BI application development framework with Model-View-Controller (MVC architecture and OLAP operations are built using the dynamic query generation, PivotTable, and HighChart to present information about PNS, CPNS, Retirement, Kenpa and Presence

Spatial reconstruction of single-cell gene expression

Science.gov (United States)

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Measuring the value of air quality: application of the spatial hedonic model.

Science.gov (United States)

Kim, Seung Gyu; Cho, Seong-Hoon; Lambert, Dayton M; Roberts, Roland K

2010-03-01

This study applies a hedonic model to assess the economic benefits of air quality improvement following the 1990 Clean Air Act Amendment at the county level in the lower 48 United States. An instrumental variable approach that combines geographically weighted regression and spatial autoregression methods (GWR-SEM) is adopted to simultaneously account for spatial heterogeneity and spatial autocorrelation. SEM mitigates spatial dependency while GWR addresses spatial heterogeneity by allowing response coefficients to vary across observations. Positive amenity values of improved air quality are found in four major clusters: (1) in East Kentucky and most of Georgia around the Southern Appalachian area; (2) in a few counties in Illinois; (3) on the border of Oklahoma and Kansas, on the border of Kansas and Nebraska, and in east Texas; and (4) in a few counties in Montana. Clusters of significant positive amenity values may exist because of a combination of intense air pollution and consumer awareness of diminishing air quality.

Simple and Realistic Data Generation

DEFF Research Database (Denmark)

Pedersen, Kenneth Houkjær; Torp, Kristian; Wind, Rico

2006-01-01

This paper presents a generic, DBMS independent, and highly extensible relational data generation tool. The tool can efficiently generate realistic test data for OLTP, OLAP, and data streaming applications. The tool uses a graph model to direct the data generation. This model makes it very simple...... to generate data even for large database schemas with complex inter- and intra table relationships. The model also makes it possible to generate data with very accurate characteristics....

SEMANTIC METADATA FOR HETEROGENEOUS SPATIAL PLANNING DOCUMENTS

Directory of Open Access Journals (Sweden)

A. Iwaniak

2016-09-01

Full Text Available Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa. The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Spatial evolution of quantum mechanical states

Science.gov (United States)

Christensen, N. D.; Unger, J. E.; Pinto, S.; Su, Q.; Grobe, R.

2018-02-01

The time-dependent Schrödinger equation is solved traditionally as an initial-time value problem, where its solution is obtained by the action of the unitary time-evolution propagator on the quantum state that is known at all spatial locations but only at t = 0. We generalize this approach by examining the spatial evolution from a state that is, by contrast, known at all times t, but only at one specific location. The corresponding spatial-evolution propagator turns out to be pseudo-unitary. In contrast to the real energies that govern the usual (unitary) time evolution, the spatial evolution can therefore require complex phases associated with dynamically relevant solutions that grow exponentially. By introducing a generalized scalar product, for which the spatial generator is Hermitian, one can show that the temporal integral over the probability current density is spatially conserved, in full analogy to the usual norm of the state, which is temporally conserved. As an application of the spatial propagation formalism, we introduce a spatial backtracking technique that permits us to reconstruct any quantum information about an atom from the ionization data measured at a detector outside the interaction region.

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.

A Novel Fixed Low-Rank Constrained EEG Spatial Filter Estimation with Application to Movie-Induced Emotion Recognition

Directory of Open Access Journals (Sweden)

Ken Yano

2016-01-01

Full Text Available This paper proposes a novel fixed low-rank spatial filter estimation for brain computer interface (BCI systems with an application that recognizes emotions elicited by movies. The proposed approach unifies such tasks as feature extraction, feature selection, and classification, which are often independently tackled in a “bottom-up” manner, under a regularized loss minimization problem. The loss function is explicitly derived from the conventional BCI approach and solves its minimization by optimization with a nonconvex fixed low-rank constraint. For evaluation, an experiment was conducted to induce emotions by movies for dozens of young adult subjects and estimated the emotional states using the proposed method. The advantage of the proposed method is that it combines feature selection, feature extraction, and classification into a monolithic optimization problem with a fixed low-rank regularization, which implicitly estimates optimal spatial filters. The proposed method shows competitive performance against the best CSP-based alternatives.

Spatial Power Combining Amplifier for Ground and Flight Applications

Science.gov (United States)

Velazco, J. E.; Taylor, M.

2016-11-01

Vacuum-tube amplifiers such as klystrons and traveling-wave tubes are the workhorses of high-power microwave radiation generation. At JPL, vacuum tubes are extensively used in ground and flight missions for radar and communications. Vacuum tubes use electron beams as the source of energy to achieve microwave power amplification. Such electron beams operate at high kinetic energies and thus require high voltages to function. In addition, vacuum tubes use compact cavity and waveguide structures that hold very intense radio frequency (RF) fields inside. As the operational frequency is increased, the dimensions of these RF structures become increasingly smaller. As power levels and operational frequencies are increased, the highly intense RF fields inside of the tubes' structures tend to arc and create RF breakdown. In the case of very high-power klystrons, electron interception - also known as body current - can produce thermal runaway of the cavities that could lead to the destruction of the tube. The high voltages needed to power vacuum tubes tend to require complicated and cumbersome power supplies. Consequently, although vacuum tubes provide unmatched high-power microwaves, they tend to arc, suffer from thermal issues, and require failure-prone high-voltage power supplies. In this article, we present a new concept for generating high-power microwaves that we refer to as the Spatial Power Combining Amplifier (SPCA). The SPCA is very compact, requires simpler, lower-voltage power supplies, and uses a unique power-combining scheme wherein power from solid-state amplifiers is coherently combined. It is a two-port amplifier and can be used inline as any conventional two-port amplifier. It can deliver its output power to a coaxial line, a waveguide, a feed, or to any microwave load. A key feature of this new scheme is the use of higher-order-mode microwave structures to spatially divide and combine power. Such higher-order-mode structures have considerably larger cross

a Novel Approach of Indexing and Retrieving Spatial Polygons for Efficient Spatial Region Queries

Science.gov (United States)

Zhao, J. H.; Wang, X. Z.; Wang, F. Y.; Shen, Z. H.; Zhou, Y. C.; Wang, Y. L.

2017-10-01

Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree) suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

A NOVEL APPROACH OF INDEXING AND RETRIEVING SPATIAL POLYGONS FOR EFFICIENT SPATIAL REGION QUERIES

Directory of Open Access Journals (Sweden)

J. H. Zhao

2017-10-01

Full Text Available Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

Science.gov (United States)

Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

2010-01-01

Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

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.

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

Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories

OpenAIRE

Wałęga, Przemysław Andrzej; Schultz, Carl; Bhatt, Mehul

2016-01-01

The systematic modelling of dynamic spatial systems is a key requirement in a wide range of application areas such as commonsense cognitive robotics, computer-aided architecture design, and dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning -a crucial requirement within dynamic spatial systems- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) spatial re...

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.

Spatial MEG laterality maps for language: clinical applications in epilepsy.

Science.gov (United States)

D'Arcy, Ryan C N; Bardouille, Timothy; Newman, Aaron J; McWhinney, Sean R; Debay, Drew; Sadler, R Mark; Clarke, David B; Esser, Michael J

2013-08-01

Functional imaging is increasingly being used to provide a noninvasive alternative to intracarotid sodium amobarbitol testing (i.e., the Wada test). Although magnetoencephalography (MEG) has shown significant potential in this regard, the resultant output is often reduced to a simplified estimate of laterality. Such estimates belie the richness of functional imaging data and consequently limit the potential value. We present a novel approach that utilizes MEG data to compute "complex laterality vectors" and consequently "laterality maps" for a given function. Language function was examined in healthy controls and in people with epilepsy. When compared with traditional laterality index (LI) approaches, the resultant maps provided critical information about the magnitude and spatial characteristics of lateralized function. Specifically, it was possible to more clearly define low LI scores resulting from strong bilateral activation, high LI scores resulting from weak unilateral activation, and most importantly, the spatial distribution of lateralized activation. We argue that the laterality concept is better presented with the inherent spatial sensitivity of activation maps, rather than being collapsed into a one-dimensional index. Copyright © 2012 Wiley Periodicals, Inc.

MALDI Imaging Mass Spectrometry (MALDI-IMS―Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis

Directory of Open Access Journals (Sweden)

Johan O. R. Gustafsson

2011-01-01

Full Text Available MALDI imaging mass spectrometry (MALDI-IMS allows acquisition of mass data for metabolites, lipids, peptides and proteins directly from tissue sections. IMS is typically performed either as a multiple spot profiling experiment to generate tissue specific mass profiles, or a high resolution imaging experiment where relative spatial abundance for potentially hundreds of analytes across virtually any tissue section can be measured. Crucially, imaging can be achieved without prior knowledge of tissue composition and without the use of antibodies. In effect MALDI-IMS allows generation of molecular data which complement and expand upon the information provided by histology including immuno-histochemistry, making its application valuable to both cancer biomarker research and diagnostics. The current state of MALDI-IMS, key biological applications to ovarian cancer research and practical considerations for analysis of peptides and proteins on ovarian tissue are presented in this review.

Chemistry with spatial control using particles and streams†

Science.gov (United States)

Kalinin, Yevgeniy V.; Murali, Adithya

2012-01-01

Spatial control of chemical reactions, with micro- and nanometer scale resolution, has important consequences for one pot synthesis, engineering complex reactions, developmental biology, cellular biochemistry and emergent behavior. We review synthetic methods to engineer this spatial control using chemical diffusion from spherical particles, shells and polyhedra. We discuss systems that enable both isotropic and anisotropic chemical release from isolated and arrayed particles to create inhomogeneous and spatially patterned chemical fields. In addition to such finite chemical sources, we also discuss spatial control enabled with laminar flow in 2D and 3D microfluidic networks. Throughout the paper, we highlight applications of spatially controlled chemistry in chemical kinetics, reaction-diffusion systems, chemotaxis and morphogenesis. PMID:23145348

Spatial Skill Profile of Mathematics Pre-Service Teachers

Science.gov (United States)

Putri, R. O. E.

2018-01-01

This study is aimed to investigate the spatial intelligence of mathematics pre-service teachers and find the best instructional strategy that facilitates this aspect. Data were collected from 35 mathematics pre-service teachers. The Purdue Spatial Visualization Test (PSVT) was used to identify the spatial skill of mathematics pre-service teachers. Statistical analysis indicate that more than 50% of the participants possessed spatial skill in intermediate level, whereas the other were in high and low level of spatial skill. The result also shows that there is a positive correlation between spatial skill and mathematics ability, especially in geometrical problem solving. High spatial skill students tend to have better mathematical performance compare to those in two other levels. Furthermore, qualitative analysis reveals that most students have difficulty in manipulating geometrical objects mentally. This problem mostly appears in intermediate and low-level spatial skill students. The observation revealed that 3-D geometrical figures is the best method that can overcome the mentally manipulation problem and develop the spatial visualization. Computer application can also be used to improve students’ spatial skill.

Developments in plasma enhanced spatial ALD for high throughput applications [3.04

NARCIS (Netherlands)

Creyghton, Y.; Illiberi, A.; Mione, M.; Boekel, W. van; Debernardi, N.; Seitz, M.; Bruele, F. van den; Poodt, P.; Roozeboom,F.

2016-01-01

Atomic layer deposition by means of spatial separation of reactive gases is emerging as an industrial manufacturing technology. Integration of non-thermal plasma in spatial ALD machines will further expand the process window towards lower operation temperatures and specific materials requiring

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

Science.gov (United States)

Strauß, Magdalena E; Mezzetti, Maura; Leorato, Samantha

2017-05-01

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms.

Tukey max-stable processes for spatial extremes

KAUST Repository

Xu, Ganggang

2016-09-21

We propose a new type of max-stable process that we call the Tukey max-stable process for spatial extremes. It brings additional flexibility to modeling dependence structures among spatial extremes. The statistical properties of the Tukey max-stable process are demonstrated theoretically and numerically. Simulation studies and an application to Swiss rainfall data indicate the effectiveness of the proposed process. © 2016 Elsevier B.V.

Seed Dispersal, Microsites or Competition—What Drives Gap Regeneration in an Old-Growth Forest? An Application of Spatial Point Process Modelling

Directory of Open Access Journals (Sweden)

Georg Gratzer

2018-04-01

Full Text Available The spatial structure of trees is a template for forest dynamics and the outcome of a variety of processes in ecosystems. Identifying the contribution and magnitude of the different drivers is an age-old task in plant ecology. Recently, the modelling of a spatial point process was used to identify factors driving the spatial distribution of trees at stand scales. Processes driving the coexistence of trees, however, frequently unfold within gaps and questions on the role of resource heterogeneity within-gaps have become central issues in community ecology. We tested the applicability of a spatial point process modelling approach for quantifying the effects of seed dispersal, within gap light environment, microsite heterogeneity, and competition on the generation of within gap spatial structure of small tree seedlings in a temperate, old growth, mixed-species forest. By fitting a non-homogeneous Neyman–Scott point process model, we could disentangle the role of seed dispersal from niche partitioning for within gap tree establishment and did not detect seed densities as a factor explaining the clustering of small trees. We found only a very weak indication for partitioning of within gap light among the three species and detected a clear niche segregation of Picea abies (L. Karst. on nurse logs. The other two dominating species, Abies alba Mill. and Fagus sylvatica L., did not show signs of within gap segregation.

The Spatial Politics of Spatial Representation

DEFF Research Database (Denmark)

Olesen, Kristian; Richardson, Tim

2011-01-01

spatial planning in Denmark reveals how fuzzy spatial representations and relational spatial concepts are being used to depoliticise strategic spatial planning processes and to camouflage spatial politics. The paper concludes that, while relational geography might play an important role in building......This paper explores the interplay between the spatial politics of new governance landscapes and innovations in the use of spatial representations in planning. The central premise is that planning experiments with new relational approaches become enmeshed in spatial politics. The case of strategic...

Spatial reconstruction of single-cell gene expression data.

Science.gov (United States)

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

PERANCANGAN DATA WAREHOUSE UNTUK MENDUKUNG PERENCANAAN PEMASARAN PERGURUAN TINGGI

Directory of Open Access Journals (Sweden)

agung prasetyo

2017-02-01

Full Text Available Salah satu indikasi perguruan tinggi yang besar adalah dilihat dari jumlah mahasiswa di perguruan tinggi tersebut. Karenanya, mahasiswa baru merupakan salah satu sumber daya yang menentukan berjalannya sebuah perguruan tinggi. Setiap tahunnya STMIK AMIKOM Purwokerto selalu melakukan penerimaan calon mahasiswa. Data mahasiswa baru tersebut sangat berguna bagi bagian pemasaran sebagai informasi untuk evaluasi kegiatan pemasaran berikutnya. Dengan dibangunnya data warehouse dan aplikasi OLAP dengan menggunakan aplikasi Pentaho Data Integration/Kettle sebagai perangkat ETL dan Pentaho Workbench yang merupakan Online Analytical Processing (OLAP sebagai pengolah database, manajemen di STMIK AMIKOM Purwokerto bisa mengambil beberapa informasi misalnya; banyak jumlah pendaftar per-periode/gelombang, per/asal sekolahnya, per/asal sumber informasi yang diperoleh calon mahasiswa baru, serta tren minat terhadap jurusan yang dipilih oleh calon mahasiswa baru. Data warehouse mampu menganalisis data transaksi, mampu memberikan laporan yang dinamis dan mampu memberikan informasi dalam berbagai dimensi tentang penerimaan mahasiswa baru di STMIK AMIKOM Purwokerto.Kata Kunci: Data Warehouse, OLAP, Pentaho, Penerimaan Calon Mahasiswa.

Detecting spatial regimes in ecosystems

Science.gov (United States)

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

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

Science.gov (United States)

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

2005-10-01

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

Review of Spatial-Database System Usability: Recommendations for the ADDNS Project

National Research Council Canada - National Science Library

Abdalla, R. M; Niall, K. K

2007-01-01

...) and three-dimensional (3D) visualizations. This report presents an overview of the basic concepts of GIS and spatial databases, provides an analytical usability evaluation and critically analyses different spatial- database applications...

Expression and Organization of Geographic Spatial Relations Based on Topic Maps

Science.gov (United States)

Liang, H. J.; Wang, H.; Cui, T. J.; Guo, J. F.

2017-09-01

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

Multidimensional extended spatial evolutionary games.

Science.gov (United States)

Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

Science.gov (United States)

Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

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.

Spatial strategies for managing visitor impacts in National Parks

Science.gov (United States)

Leung, Y.-F.; Marion, J.L.

1999-01-01

effective in minimizing resource impacts. Spatial configuration was only minimally evaluated, as it was not included in the survey. The proposed typology of spatial strategies offers a useful means of organizing and understanding the wide variety of management strategies and actions applied in managing visitor impacts in parks and protected areas. Examples from U.S. national parks demonstrate the diversity of these basic strategies and their flexibility in implementation at various spatial scales. Documentation of these examples helps illustrate their application and inform managers of the multitude of options. Further analysis from the spatial perspective is needed Io extend the applicability of this typology to other recreational activities and management issues.

Modeling structural change in spatial system dynamics: A Daisyworld example.

Science.gov (United States)

Neuwirth, C; Peck, A; Simonović, S P

2015-03-01

System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed.

Cooperative Spatial Retreat for Resilient Drone Networks.

Science.gov (United States)

Kang, Jin-Hyeok; Kwon, Young-Min; Park, Kyung-Joon

2017-05-03

Drones are broadening their scope to various applications such as networking, package delivery, agriculture, rescue, and many more. For proper operation of drones, reliable communication should be guaranteed because drones are remotely controlled. When drones experience communication failure due to bad channel condition, interference, or jamming in a certain area, one existing solution is to exploit mobility or so-called spatial retreat to evacuate them from the communication failure area. However, the conventional spatial retreat scheme moves drones in random directions, which results in inefficient movement with significant evacuation time and waste of battery lifetime. In this paper, we propose a novel spatial retreat technique that takes advantage of cooperation between drones for resilient networking, which is called cooperative spatial retreat (CSR). Our performance evaluation shows that the proposed CSR significantly outperforms existing schemes.

A spatially based field specific crop recordkeeping system prototype ...

African Journals Online (AJOL)

These spatial data were prepared using ArcGIS 9.3. A database was created in Microsoft Access 2007. The database contained information on crops, fertilizers and past management. The information was linked to the spatial data table and maintained in the database. An application was developed using Visual Basic 6 in ...

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-08-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS - a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive.

implementation of spatial domain homomorphic filtering

African Journals Online (AJOL)

eobe

on a Java-enabled mobile phone and form a low cost embedded image processing enhancement system. Keywords: Spatial ... important because of the wide range of applications that can ..... Co our Image Processi g” Ph D thesis U iversity of.

Spatial data efficient transmission in WebGIS based on IPv6

Science.gov (United States)

Wang, Zhen-feng; Liu, Ji-ping; Wang, Liang; Tao, Kun-wang

2008-12-01

Large-size of spatial data and limited bandwidth of network make it restricted to transmit spatial data in WebGIS. This paper employs IPv6 (Internet Protocol version 6), the successor of IPv4 running now, to transmit spatial data efficiently. As the core of NGN (Next Generation Network), IPv6 brings us many advantages to resolve performance problems in current IPv4 network applications. Multicast, which is mandatory in IPv6 routers, can make one server serve many clients simultaneously efficiently, thus to improve capacity of network applications. The new type of anycast address in IPv6 will make network client applications possible to find the nearest server. This makes data transmission between client and server fastest. The paper introduces how to apply IPv6 multicast and anycast in WebGIS to transmit data efficiently.

The research and application of the power big data

Science.gov (United States)

Zhang, Suxiang; Zhang, Dong; Zhang, Yaping; Cao, Jinping; Xu, Huiming

2017-01-01

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application; meanwhile, the continuous development of the Internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. These data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions; and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model; we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. Therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

"Real-Time Optical Laboratory Linear Algebra Solution Of Partial Differential Equations"

Science.gov (United States)

Casasent, David; Jackson, James

1986-03-01

A Space Integrating (SI) Optical Linear Algebra Processor (OLAP) employing space and frequency-multiplexing, new partitioning and data flow, and achieving high accuracy performance with a non base-2 number system is described. Laboratory data on the performance of this system and the solution of parabolic Partial Differential Equations (PDEs) is provided. A multi-processor OLAP system is also described for the first time. It use in the solution of multiple banded matrices that frequently arise is then discussed. The utility and flexibility of this processor compared to digital systolic architectures should be apparent.

A Conceptual Model for Multidimensional Analysis of Documents

Science.gov (United States)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

A spatial error model with continuous random effects and an application to growth convergence

Science.gov (United States)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

Compatible Spatial Discretizations for Partial Differential Equations

Energy Technology Data Exchange (ETDEWEB)

Arnold, Douglas, N, ed.

2004-11-25

From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide variety of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical

APPLICATION OF OLAP SYSTEM IN INFORMATION SUB-SYSTEM OF QMS INCOSISTENCY ANALYSIS

Directory of Open Access Journals (Sweden)

Alempije Veljovic

2008-03-01

Full Text Available Records of inconsistencies arise as a result of incompliance of certain requirements during the execution of the process for the quality management system (QMS functioning. In this study, the established connection between QMS and projected information sub-system for inconsistencies management is presented. The information model of inconsistencies management provides a possibility to analyse inconsistencies from the aspect of interactive analytical data processing (OLAPsystems on the basis of multi-dimensional tables (OLAPcubes created in MSSQL Server-Analysis Services programme.

Site characterization: a spatial estimation approach

International Nuclear Information System (INIS)

Candy, J.V.; Mao, N.

1980-10-01

In this report the application of spatial estimation techniques or kriging to groundwater aquifers and geological borehole data is considered. The adequacy of these techniques to reliably develop contour maps from various data sets is investigated. The estimator is developed theoretically in a simplified fashion using vector-matrix calculus. The practice of spatial estimation is discussed and the estimator is then applied to two groundwater aquifer systems and used also to investigate geological formations from borehole data. It is shown that the estimator can provide reasonable results when designed properly

Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

Science.gov (United States)

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

Spatial coherence resonance and spatial pattern transition induced by the decrease of inhibitory effect in a neuronal network

Science.gov (United States)

Tao, Ye; Gu, Huaguang; Ding, Xueli

2017-10-01

Spiral waves were observed in the biological experiment on rat brain cortex with the application of carbachol and bicuculline which can block inhibitory coupling from interneurons to pyramidal neurons. To simulate the experimental spiral waves, a two-dimensional neuronal network composed of pyramidal neurons and inhibitory interneurons was built. By decreasing the percentage of active inhibitory interneurons, the random-like spatial patterns change to spiral waves and to random-like spatial patterns or nearly synchronous behaviors. The spiral waves appear at a low percentage of inhibitory interneurons, which matches the experimental condition that inhibitory couplings of the interneurons were blocked. The spiral waves exhibit a higher order or signal-to-noise ratio (SNR) characterized by spatial structure function than both random-like spatial patterns and nearly synchronous behaviors, which shows that changes of the percentage of active inhibitory interneurons can induce spatial coherence resonance-like behaviors. In addition, the relationship between the coherence degree and the spatial structures of the spiral waves is identified. The results not only present a possible and reasonable interpretation to the spiral waves observed in the biological experiment on the brain cortex with disinhibition, but also reveal that the spiral waves exhibit more ordered degree in spatial patterns.

Spatially independent martingales, intersections, and applications

CERN Document Server

Shmerkin, Pablo

2018-01-01

The authors define a class of random measures, spatially independent martingales, which we view as a natural generalization of the canonical random discrete set, and which includes as special cases many variants of fractal percolation and Poissonian cut-outs. The authors pair the random measures with deterministic families of parametrized measures \\{\\eta_t\\}_t, and show that under some natural checkable conditions, a.s. the mass of the intersections is H�lder continuous as a function of t. This continuity phenomenon turns out to underpin a large amount of geometric information about these measures, allowing us to unify and substantially generalize a large number of existing results on the geometry of random Cantor sets and measures, as well as obtaining many new ones. Among other things, for large classes of random fractals they establish (a) very strong versions of the Marstrand-Mattila projection and slicing results, as well as dimension conservation, (b) slicing results with respect to algebraic curves a...

Spherical Process Models for Global Spatial Statistics

KAUST Repository

Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

2017-01-01

Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture

Modern Statistics for Spatial Point Processes

DEFF Research Database (Denmark)

Møller, Jesper; Waagepetersen, Rasmus

2007-01-01

We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs...

Modern statistics for spatial point processes

DEFF Research Database (Denmark)

Møller, Jesper; Waagepetersen, Rasmus

We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs...

MGlu5 antagonism impairs exploration and memory of spatial and non-spatial stimuli in rats

DEFF Research Database (Denmark)

Christoffersen, Gert Rene Juul; Simonyi, Agnes; Schachtman, Todd R.

2008-01-01

and it was found that: 1) Locomotion during exploration of spatial environments and exploration time at novel objects were reduced by i.p. but not by prelimbic administration of MPEP, 2) spatial short-term memory was impaired in cross-maze and object discrimination was reduced after both types of administration, 3......) long-term retention of spatial conditioning in the cross-maze was inhibited after i.p. applications which 4) also inhibited spontaneous alternation performance during maze-exploration. Reduced exploratory locomotion and exploration time after i.p. injections may have contributed to the observed......Metabotropic glutamate receptor subtype 5 (mGlu5) has been implicated in memory processing in some but not all learning tasks.  The reason why this receptor is involved in some tasks but not in others remains to be determined.  The present experiments using rats examined effects of the mGlu5...

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.

Some topics in the spatial bispectra

Energy Technology Data Exchange (ETDEWEB)

Sullivan, E. [NUWC, Newport, RI (United States)

1994-11-15

The bispectrum can be defined as the triple fourier transform of the third order cumulant of a data series. Up to the present, except in image analysis, most work on the bispectrum has treated time series. Recently, however, there has been interest in using the bispectrum in acoustic array processing. After a look at some issues involving sampling frequencies and symmetries of the bispectrum in general, two applications of the spatial bispectrum to underwater acoustic array processing will be discussed. One is a method of processing against loss of spatial coherence in towed arrays, which takes the form of a one-dimensional image, and the other is a look at the role of spatial bispectra in matched-field processing, which is a form of model-based processing used for the localization of acoustic sound sources.

Accuracy and impact of spatial aids based upon satellite enumeration to improve indoor residual spraying spatial coverage.

Science.gov (United States)

Bridges, Daniel J; Pollard, Derek; Winters, Anna M; Winters, Benjamin; Sikaala, Chadwick; Renn, Silvia; Larsen, David A

2018-02-23

Indoor residual spraying (IRS) is a key tool in the fight to control, eliminate and ultimately eradicate malaria. IRS protection is based on a communal effect such that an individual's protection primarily relies on the community-level coverage of IRS with limited protection being provided by household-level coverage. To ensure a communal effect is achieved through IRS, achieving high and uniform community-level coverage should be the ultimate priority of an IRS campaign. Ensuring high community-level coverage of IRS in malaria-endemic areas is challenging given the lack of information available about both the location and number of households needing IRS in any given area. A process termed 'mSpray' has been developed and implemented and involves use of satellite imagery for enumeration for planning IRS and a mobile application to guide IRS implementation. This study assessed (1) the accuracy of the satellite enumeration and (2) how various degrees of spatial aid provided through the mSpray process affected community-level IRS coverage during the 2015 spray campaign in Zambia. A 2-stage sampling process was applied to assess accuracy of satellite enumeration to determine number and location of sprayable structures. Results indicated an overall sensitivity of 94% for satellite enumeration compared to finding structures on the ground. After adjusting for structure size, roof, and wall type, households in Nchelenge District where all types of satellite-based spatial aids (paper-based maps plus use of the mobile mSpray application) were used were more likely to have received IRS than Kasama district where maps used were not based on satellite enumeration. The probability of a household being sprayed in Nchelenge district where tablet-based maps were used, did not differ statistically from that of a household in Samfya District, where detailed paper-based spatial aids based on satellite enumeration were provided. IRS coverage from the 2015 spray season benefited from

Spatial modeling on the upperstream of the Citarum watershed: An application of geoinformatics

Science.gov (United States)

Ningrum, Windy Setia; Widyaningsih, Yekti; Indra, Tito Latif

2017-03-01

The Citarum watershed is the longest and the largest watershed in West Java, Indonesia, located at 106°51'36''-107°51' E and 7°19'-6°24'S across 10 districts, and serves as the water supply for over 15 million people. In this area, the water criticality index is concerned to reach the balance between water supply and water demand, so that in the dry season, the watershed is still able to meet the water needs of the society along the Citarum river. The objective of this research is to evaluate the water criticality index of Citarum watershed area using spatial model to overcome the spatial dependencies in the data. The result of Lagrange multiplier diagnostics for spatial dependence results are LM-err = 34.6 (p-value = 4.1e-09) and LM-lag = 8.05 (p-value = 0.005), then modeling using Spatial Lag Model (SLM) and Spatial Error Model (SEM) were conducted. The likelihood ratio test show that both of SLM dan SEM model is better than OLS model in modeling water criticality index in Citarum watershed. The AIC value of SLM and SEM model are 78.9 and 51.4, then the SEM model is better than SLM model in predicting water criticality index in Citarum watershed.

Multiscale spatial and temporal estimation of the b-value

Science.gov (United States)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Bounds on achievable accuracy in analog optical linear-algebra processors

Science.gov (United States)

Batsell, Stephen G.; Walkup, John F.; Krile, Thomas F.

1990-07-01

Upper arid lower bounds on the number of bits of accuracy achievable are determined by applying a seconth-ortler statistical model to the linear algebra processor. The use of bounds was found necessary due to the strong signal-dependence of the noise at the output of the optical linear algebra processor (OLAP). 1 1. ACCURACY BOUNDS One of the limiting factors in applying OLAPs to real world problems has been the poor achievable accuracy of these processors. Little previous research has been done on determining noise sources from a systems perspective which would include noise generated in the multiplication ard addition operations spatial variations across arrays and crosstalk. We have previously examined these noise sources and determined a general model for the output noise mean and variance. The model demonstrates a strony signaldependency in the noise at the output of the processor which has been confirmed by our experiments. 1 We define accuracy similar to its definition for an analog signal input to an analog-to-digital (ND) converter. The number of bits of accuracy achievable is related to the log (base 2) of the number of separable levels at the P/D converter output. The number of separable levels is fouri by dividing the dynamic range by m times the standard deviation of the signal a. 2 Here m determines the error rate in the P/D conversion. The dynamic range can be expressed as the

Accuracy Limitations in Optical Linear Algebra Processors

Science.gov (United States)

Batsell, Stephen Gordon

1990-01-01

One of the limiting factors in applying optical linear algebra processors (OLAPs) to real-world problems has been the poor achievable accuracy of these processors. Little previous research has been done on determining noise sources from a systems perspective which would include noise generated in the multiplication and addition operations, noise from spatial variations across arrays, and from crosstalk. In this dissertation, we propose a second-order statistical model for an OLAP which incorporates all these system noise sources. We now apply this knowledge to determining upper and lower bounds on the achievable accuracy. This is accomplished by first translating the standard definition of accuracy used in electronic digital processors to analog optical processors. We then employ our second-order statistical model. Having determined a general accuracy equation, we consider limiting cases such as for ideal and noisy components. From the ideal case, we find the fundamental limitations on improving analog processor accuracy. From the noisy case, we determine the practical limitations based on both device and system noise sources. These bounds allow system trade-offs to be made both in the choice of architecture and in individual components in such a way as to maximize the accuracy of the processor. Finally, by determining the fundamental limitations, we show the system engineer when the accuracy desired can be achieved from hardware or architecture improvements and when it must come from signal pre-processing and/or post-processing techniques.

Review of Spatial Indexing Techniques for Large Urban Data Management

DEFF Research Database (Denmark)

Azri, Suhaibah; Ujang, Uznir; Anton, François

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

Research on Heterogeneous Data Exchange based on XML

Science.gov (United States)

Li, Huanqin; Liu, Jinfeng

Integration of multiple data sources is becoming increasingly important for enterprises that cooperate closely with their partners for e-commerce. OLAP enables analysts and decision makers fast access to various materialized views from data warehouses. However, many corporations have internal business applications deployed on different platforms. This paper introduces a model for heterogeneous data exchange based on XML. The system can exchange and share the data among the different sources. The method used to realize the heterogeneous data exchange is given in this paper.

Development of a medical informatics data warehouse.

Science.gov (United States)

Wu, Cai

2006-01-01

This project built a medical informatics data warehouse (MedInfo DDW) in an Oracle database to analyze medical information which has been collected through Baylor Family Medicine Clinic (FCM) Logician application. The MedInfo DDW used Star Schema with dimensional model, FCM database as operational data store (ODS); the data from on-line transaction processing (OLTP) were extracted and transferred to a knowledge based data warehouse through SQLLoad, and the patient information was analyzed by using on-line analytic processing (OLAP) in Crystal Report.

Adaptive Architecture - a Spatial Objective

DEFF Research Database (Denmark)

Unterrainer, Walter

2011-01-01

New challenges of a fast changing society with new social phenomena as well as growing environmental problems ask for rethinking our habitats on all scales and reflecting our design methods to produce them. Many Megacities prepare with big projects against dramatic environmental threats (New York...... detail in itself, does not create humanity: We have today enough of superficial and rather bad architecture which is modern.´ There is nothing to add on....... the weakest point in the development towards a more sustainable architecture on all scales, the problems and solutions are discussed as spatial challenges, including all aspects of spatial creations and spatial retrofitting. To get to the point: The ´sustainable´ in ´sustainable architecture´ is reduced...... in too many buildings to implementations of new technologies, in its worst examples reduced to meaningless applications of new technologies to rather mediocre architecture. I am not arguing in general against new building technologies and I have been involved myself in developments of new building skins...

Spatial properties of odd and even low order harmonics generated in gas.

Science.gov (United States)

Lambert, G; Andreev, A; Gautier, J; Giannessi, L; Malka, V; Petralia, A; Sebban, S; Stremoukhov, S; Tissandier, F; Vodungbo, B; Zeitoun, Ph

2015-01-14

High harmonic generation in gases is developing rapidly as a soft X-ray femtosecond light-source for applications. This requires control over all the harmonics characteristics and in particular, spatial properties have to be kept very good. In previous literature, measurements have always included several harmonics contrary to applications, especially spectroscopic applications, which usually require a single harmonic. To fill this gap, we present here for the first time a detailed study of completely isolated harmonics. The contribution of the surrounding harmonics has been totally suppressed using interferential filtering which is available for low harmonic orders. In addition, this allows to clearly identify behaviors of standard odd orders from even orders obtained by frequency-mixing of a fundamental laser and of its second harmonic. Comparisons of the spatial intensity profiles, of the spatial coherence and of the wavefront aberration level of 5ω at 160 nm and 6ω at 135 nm have then been performed. We have established that the fundamental laser beam aberrations can cause the appearance of a non-homogenous donut-shape in the 6ω spatial intensity distribution. This undesirable effect can be easily controlled. We finally conclude that the spatial quality of an even harmonic can be as excellent as in standard generation.

Architectural Implications for Spatial Object Association Algorithms*

Science.gov (United States)

Kumar, Vijay S.; Kurc, Tahsin; Saltz, Joel; Abdulla, Ghaleb; Kohn, Scott R.; Matarazzo, Celeste

2013-01-01

Spatial object association, also referred to as crossmatch of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Server®, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation provides insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the Large Synoptic Survey Telescope (LSST). PMID:25692244

Generalized index for spatial data sets as a measure of complete spatial randomness

Science.gov (United States)

Hackett-Jones, Emily J.; Davies, Kale J.; Binder, Benjamin J.; Landman, Kerry A.

2012-06-01

Spatial data sets, generated from a wide range of physical systems can be analyzed by counting the number of objects in a set of bins. Previous work has been limited to equal-sized bins, which are inappropriate for some domains (e.g., circular). We consider a nonequal size bin configuration whereby overlapping or nonoverlapping bins cover the domain. A generalized index, defined in terms of a variance between bin counts, is developed to indicate whether or not a spatial data set, generated from exclusion or nonexclusion processes, is at the complete spatial randomness (CSR) state. Limiting values of the index are determined. Using examples, we investigate trends in the generalized index as a function of density and compare the results with those using equal size bins. The smallest bin size must be much larger than the mean size of the objects. We can determine whether a spatial data set is at the CSR state or not by comparing the values of a generalized index for different bin configurations—the values will be approximately the same if the data is at the CSR state, while the values will differ if the data set is not at the CSR state. In general, the generalized index is lower than the limiting value of the index, since objects do not have access to the entire region due to blocking by other objects. These methods are applied to two applications: (i) spatial data sets generated from a cellular automata model of cell aggregation in the enteric nervous system and (ii) a known plant data distribution.

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.

Spatial-Temporal Event Detection from Geo-Tagged Tweets

Directory of Open Access Journals (Sweden)

Yuqian Huang

2018-04-01

Full Text Available As one of the most popular social networking services in the world, Twitter allows users to post messages along with their current geographic locations. Such georeferenced or geo-tagged Twitter datasets can benefit location-based services, targeted advertising and geosocial studies. Our study focused on the detection of small-scale spatial-temporal events and their textual content. First, we used Spatial-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN to spatially-temporally cluster the tweets. Then, the word frequencies were summarized for each cluster and the potential topics were modeled by the Latent Dirichlet Allocation (LDA algorithm. Using two years of Twitter data from four college cities in the U.S., we were able to determine the spatial-temporal patterns of two known events, two unknown events and one recurring event, which then were further explored and modeled to identify the semantic content about the events. This paper presents our process and recommendations for both finding event-related tweets as well as understanding the spatial-temporal behaviors and semantic natures of the detected events.

Scanning SQUID susceptometers with sub-micron spatial resolution

Energy Technology Data Exchange (ETDEWEB)

Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.; Holland, Connor M.; Moler, Kathryn A. [Department of Applied Physics, Stanford University, Stanford, California 94305-4045 (United States); Paulius, Lisa [Department of Physics, Western Michigan University, Kalamazoo, Michigan 49008-5252 (United States); Spanton, Eric M. [Department of Physics, Stanford University, Stanford, California 94305-4045 (United States); Schiessl, Daniel [Attocube Systems AG, Königinstraße 11A, 80539 Munich (Germany); Jermain, Colin L.; Gibbons, Jonathan [Department of Physics, Cornell University, Cornell, Ithaca, New York 14853 (United States); Fung, Y.-K.K.; Gibson, Gerald W. [IBM Research Division, T. J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Huber, Martin E. [Department of Physics, University of Colorado Denver, Denver, Colorado 80217-3364 (United States); Ralph, Daniel C. [Department of Physics, Cornell University, Cornell, Ithaca, New York 14853 (United States); Kavli Institute at Cornell, Ithaca, New York 14853 (United States); Ketchen, Mark B. [OcteVue, Hadley, Massachusetts 01035 (United States)

2016-09-15

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes the spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.

Scanning SQUID susceptometers with sub-micron spatial resolution

International Nuclear Information System (INIS)

Kirtley, John R.; Rosenberg, Aaron J.; Palmstrom, Johanna C.; Holland, Connor M.; Moler, Kathryn A.; Paulius, Lisa; Spanton, Eric M.; Schiessl, Daniel; Jermain, Colin L.; Gibbons, Jonathan; Fung, Y.-K.K.; Gibson, Gerald W.; Huber, Martin E.; Ralph, Daniel C.; Ketchen, Mark B.

2016-01-01

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ_0/Hz"1"/"2. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes the spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.

Development of a web GIS application for emissions inventory spatial allocation based on open source software tools

Science.gov (United States)

Gkatzoflias, Dimitrios; Mellios, Giorgos; Samaras, Zissis

2013-03-01

Combining emission inventory methods and geographic information systems (GIS) remains a key issue for environmental modelling and management purposes. This paper examines the development of a web GIS application as part of an emission inventory system that produces maps and files with spatial allocated emissions in a grid format. The study is not confined in the maps produced but also presents the features and capabilities of a web application that can be used by every user even without any prior knowledge of the GIS field. The development of the application was based on open source software tools such as MapServer for the GIS functions, PostgreSQL and PostGIS for the data management and HTML, PHP and JavaScript as programming languages. In addition, background processes are used in an innovative manner to handle the time consuming and computational costly procedures of the application. Furthermore, a web map service was created to provide maps to other clients such as the Google Maps API v3 that is used as part of the user interface. The output of the application includes maps in vector and raster format, maps with temporal resolution on daily and hourly basis, grid files that can be used by air quality management systems and grid files consistent with the European Monitoring and Evaluation Programme Grid. Although the system was developed and validated for the Republic of Cyprus covering a remarkable wide range of pollutant and emissions sources, it can be easily customized for use in other countries or smaller areas, as long as geospatial and activity data are available.

A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

Directory of Open Access Journals (Sweden)

H.J. Foster

2001-01-01

Full Text Available Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests, has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry

Detecting summarizability in OLAP

CERN Document Server

Niemi, Tapio; Thanisch, Peter; Nummenmaa, Jyrki

2014-01-01

The industry trend towards self-service business intelligence is impeded by the absence, in commercially-available information systems, of automated identification of potential issues with summarization operations. Research on statistical databases and on data warehouses have both produced widely-accepted categorisations of measure attributes, the former based on general summarizability properties and the latter based on measures' additivity properties. We demonstrate that neither of these categorisations is an appropriate basis for precise identification of measure types since they are incomplete, ambiguous and insufficiently refined. Using a new categorisation of dimension types and multidimensional structures, we derive a measure categorisation which is a synthesis and a refinement of the two aforementioned categorisations. We give formal definitions for our summarizability types, based on the relational model of data, and then construct rules for correct summarization by using these definitions. We also g...

Spatial filtring and thermocouple spatial filter

International Nuclear Information System (INIS)

Han Bing; Tong Yunxian

1989-12-01

The design and study on thermocouple spatial filter have been conducted for the flow measurement of integrated reactor coolant. The fundamental principle of spatial filtring, mathematical descriptions and analyses of thermocouple spatial filter are given

A survey of open source tools for business intelligence

DEFF Research Database (Denmark)

Thomsen, Christian; Pedersen, Torben Bach

2005-01-01

The industrial use of open source Business Intelligence (BI) tools is not yet common. It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey paper, we consider the capabilities of a number of open source tools for BI....... In the paper, we consider three Extract-Transform-Load (ETL) tools, three On-Line Analytical Processing (OLAP) servers, two OLAP clients, and four database management systems (DBMSs). Further, we describe the licenses that the products are released under. It is argued that the ETL tools are still not very...

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)

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.

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

Energy Technology Data Exchange (ETDEWEB)

Siljander, M.

2010-07-01

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

Pulse shaping using a spatial light modulator

CSIR Research Space (South Africa)

Botha, N

2009-07-01

Full Text Available Femtosecond pulse shaping can be done by different kinds of pulse shapers, such as liquid crystal spatial light modulators (LC SLM), acousto optic modulators (AOM) and deformable and movable mirrors. A few applications where pulse shaping...

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

Optical spatial differentiator based on subwavelength high-contrast gratings

Science.gov (United States)

Dong, Zhewei; Si, Jiangnan; Yu, Xuanyi; Deng, Xiaoxu

2018-04-01

An optical spatial differentiator based on subwavelength high-contrast gratings (HCGs) is proposed experimentally. The spatial differentiation property of the subwavelength HCG is analyzed by calculating its spatial spectral transfer function based on the periodic waveguide theory. By employing the FDTD solutions, the performance of the subwavelength HCG spatial differentiator was investigated numerically. The subwavelength HCG differentiator with the thickness at the nanoscale was fabricated on the quartz substrate by electron beam lithography and Bosch deep silicon etching. Observed under an optical microscope with a CCD camera, the spatial differentiation of the incident field profile was obtained by the subwavelength HCG differentiator in transmission without Fourier lens. By projecting the images of slits, letter "X," and a cross on the subwavelength HCG differentiator, edge detections of images were obtained in transmission. With the nanoscale HCG structure and simple optical implementation, the proposed optical spatial differentiator provides the prospects for applications in optical computing systems and parallel data processing.

Spatial occupancy models for large data sets

Science.gov (United States)

Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

2013-01-01

Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

Science.gov (United States)

Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

2017-05-01

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

Bayesian disease mapping: hierarchical modeling in spatial epidemiology

National Research Council Canada - National Science Library

Lawson, Andrew

2013-01-01

.... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...

Evaluating water erosion prediction project model using Cesium-137-derived spatial soil redistribution data

Science.gov (United States)

The lack of spatial soil erosion data has been a major constraint on the refinement and application of physically based erosion models. Spatially distributed models can only be thoroughly validated with distributed erosion data. The fallout cesium-137 has been widely used to generate spatial soil re...

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

Science.gov (United States)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

The static gravitational field near spatial infinity

International Nuclear Information System (INIS)

Beig, R.

1980-01-01

A static solution to Einstein's equations, which is asymptotically flat near spatial infinity, is shown to be asymptotically Schwarzschildian. As an application of this result a technical lemma on the existence of asymptotically flat harmonic coordinates near infinity is proved. (author)

Colorful ESL Test Papers And Spatial Intelligence:

Directory of Open Access Journals (Sweden)

Dennis Moradkhan

2014-11-01

Full Text Available The purpose of this research was to find out whether introducing color as an element which may appeal to spatially-intelligent candidates affects their performance on ESL grammar tests. 52 participants were given two parallel grammar tests, one in black and white and the other bearing the full spectrum of colors in the natural daylight. In order to identify the candidates with visual-spatial learning style, the participants and their teachers were asked to respond to Visual-Spatial Identifier rating scale. Based on the results, no significant relationship was found between the performance of candidates on the colorful and black and white grammar tests and their visual-spatial intelligence. It was concluded that other variables including the method of applying colors, the type and combination of colors as well as the differential impact of different colors on candidates with different cultural backgrounds needed to be addressed before any conclusions can be drawn about the application of color in language assessment.

Location-Based Mapping Services to Support Collaboration in Spatially Distributed Workgroups

Science.gov (United States)

Meyer, Eike Michael; Wichmann, Daniel; Büsch, Henning; Boll, Susanne

Mobile devices and systems reached almost every part of our daily life. Following the mobile computing trend, also business logics of distributed, cooperative applications started to move into the mobile client applications. With this shift, the cooperation aspect may also exploit the user’s location and situation context and capabilities of the mobile device and integrate it into the actual cooperation and collaboration. In this paper, we present an approach for a Collaborative Map that exploits the spatial context of the member of a distributed group as a means to visualize and provide collaboration functionality. Then, a number of location-related cooperation methods become feasible such as getting an overview of the spatial distribution of the team members, identify an ad-hoc meeting place nearby, or chat with a group member who has a certain expertise in his or her profile. With CoMa, we move from standard collaboration tools that marginally consider spatial information towards context-aware mobile collaborative systems that can support a wide range of applications such as emergency response, maintenance work or event organization where human resources have to be coordinated in a spatial context and tasks need to be assigned dynamically depending on capabilities and situation context.

Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python

Science.gov (United States)

Laura, Jason R.; Rey, Sergio J.

2017-01-01

Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.

Cooperative Spatial Retreat for Resilient Drone Networks †

Science.gov (United States)

Kang, Jin-Hyeok; Kwon, Young-Min; Park, Kyung-Joon

2017-01-01

Drones are broadening their scope to various applications such as networking, package delivery, agriculture, rescue, and many more. For proper operation of drones, reliable communication should be guaranteed because drones are remotely controlled. When drones experience communication failure due to bad channel condition, interference, or jamming in a certain area, one existing solution is to exploit mobility or so-called spatial retreat to evacuate them from the communication failure area. However, the conventional spatial retreat scheme moves drones in random directions, which results in inefficient movement with significant evacuation time and waste of battery lifetime. In this paper, we propose a novel spatial retreat technique that takes advantage of cooperation between drones for resilient networking, which is called cooperative spatial retreat (CSR). Our performance evaluation shows that the proposed CSR significantly outperforms existing schemes. PMID:28467390

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

Science.gov (United States)

Brock, William A.; Carpenter, Stephen R.; Ellison, Aaron M.; Livina, Valerie N.; Seekell, David A.; Scheffer, Marten; van Nes, Egbert H.; Dakos, Vasilis

2014-01-01

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data. PMID:24658137

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic.

Science.gov (United States)

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set-proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters.

Spatial Correlation Of Streamflows: An Analytical Approach

Science.gov (United States)

Betterle, A.; Schirmer, M.; Botter, G.

2016-12-01

The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the

Spatial-temporal event detection in climate parameter imagery.

Energy Technology Data Exchange (ETDEWEB)

McKenna, Sean Andrew; Gutierrez, Karen A.

2011-10-01

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

Real-time spatial optimization : based on the application in wood supply chain management

International Nuclear Information System (INIS)

Scholz, J.

2010-01-01

Real-time spatial optimization - a combination of Geographical Information Science and Technology and Operations Research - is capable of generating optimized solutions to given spatial problems in real-time. The basic concepts to develop a real-time spatial optimization system are outlined in this thesis. Geographic Information Science delivers the foundations for acquiring, storing, manipulating, visualizing and analyzing spatial information. In order to develop a system that consists of several independent components the concept of Service Oriented Architectures is applied. This facilitates communication between software systems utilizing standardized services that ensure interoperability. Thus, standards in the field of Geographic Information are inevitable for real-time spatial optimization. By exploiting the ability of mobile devices to determine the own position paired with standardized services Location Based Services are created. They are of interest in order to gather real-time data from mobile devices that are of importance for the optimization process itself. To optimize a given spatial problem, the universe of discourse has to be modeled accordingly. For the problem addressed in this thesis - Wood Supply Chain management - Graph theory is used. In addition, the problem of Wood Supply Chain management can be represented by a specific mathematical problem class, the Vehicle Routing problem - specifically the Vehicle Routing Problem with Pickup and Delivery and Time Windows. To optimize this problem class, exact and approximate solution techniques exist. Exact algorithms provide optimal solutions and guarantee their optimally, whereas approximate techniques - approximation algorithms or heuristics - do not guarantee that a global optimum is found. Nevertheless, the are capable of handling large problem instances in reasonable time. For optimizing the Wood Supply Chain Adaptive Large Neighborhood Search is selected as appropriate optimization technique

Detection of precursory deformation using a TLS. Application to spatial prediction of rockfalls.

Science.gov (United States)

Abellán, Antonio; Vilaplana, Joan Manuel; Calvet, Jaume; Rodriguez, Xavier

2010-05-01

Different applications on the use of Terrestrial Laser Scanner (TLS) on rock slopes are undergoing rapid development, mainly in the characterization of 3D discontinuities and the monitoring of rock slopes. The emphasis of this research is on detection of precursory deformation and its application to spatial prediction of rockfalls. The pilot study area corresponds to the main scarp of an old slide located at Puigcercós (Catalonia, Spain). 3D temporal variations of the terrain were analyzed by comparing sequential TLS datasets. Five areas characterized by centimetric precursory deformations were detected in the study area. Of these deformations, (a) growing deformation across three areas culminated in a rockfall occurrence; and (b) another growing deformation across two areas was detected, making a subsequent rockfall likely. The areas with precursory deformations detected in Puigcercós showed the following characteristics: (a) a sub-vertical fracture delimiting the moving part from the rest of the slope; (b) an increase in the horizontal displacement upwards, typical of a toppling failure mechanism (Muller 1968; Goodman and Bray, 1976). In addition, decimetric-scale rockfalls were observed in the upper part of the moving areas, which is consistent with the observations of Rosser et al., (2007). TLS ILRIS 3D technical characteristics are as follows: high accuracy (7.2 mm at a range of 50 meters), high angular resolution (e.g. 1 point every few cm), fast data acquisition: 2,500 points/second; broad coverage; high maximum range on natural slopes: ~600m. The single point distances between the surface of reference and the successive data point clouds were computed using a conventional methodology (data vs. reference comparison). The direction of comparison was defined as the normal vector of the rock face at its central part. We focused in the study of the small scale displacements towards the origin of coordinates, which reflect the pre-failure deformation on part of

Intermediate-term medium-range earthquake prediction algorithm M8: A new spatially stabilized application in Italy

International Nuclear Information System (INIS)

Romashkova, L.L.; Kossobokov, V.G.; Peresan, A.; Panza, G.F.

2001-12-01

A series of experiments, based on the intermediate-term earthquake prediction algorithm M8, has been performed for the retrospective simulation of forward predictions in the Italian territory, with the aim to design an experimental routine for real-time predictions. These experiments evidenced two main difficulties for the application of M8 in Italy. The first one is due to the fact that regional catalogues are usually limited in space. The second one concerns certain arbitrariness and instability, with respect to the positioning of the circles of investigation. Here we design a new scheme for the application of the algorithm M8, which is less subjective and less sensitive to the position of the circles of investigation. To perform this test, we consider a recent revision of the Italian catalogue, named UCI2001, composed by CCI1996, NEIC and ALPOR data for the period 1900-1985, and updated with the NEIC reduces the spatial heterogeneity of the data at the boundaries of Italy. The new variant of the M8 algorithm application reduces the number of spurious alarms and increases the reliability of predictions. As a result, three out of four earthquakes with magnitude M max larger than 6.0 are predicted in the retrospective simulation of the forward prediction, during the period 1972-2001, with a space-time volume of alarms comparable to that obtained with the non-stabilized variant of the M8 algorithm in Italy. (author)

ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories

OpenAIRE

Wałęga, Przemysław Andrzej; Bhatt, Mehul; Schultz, Carl

2015-01-01

The systematic modelling of \\emph{dynamic spatial systems} [9] is a key requirement in a wide range of application areas such as comonsense cognitive robotics, computer-aided architecture design, dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning ---a crucial requirement within dynamic spatial systems-- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) s...

Staging with spatial filters

International Nuclear Information System (INIS)

Glaze, J.

1974-01-01

It is known that small scale beam instabilities limit the focusable energy that can be achieved from a terawatt laser chain. Spatial filters are currently being used on CYCLOPS to ameliorate this problem. Realizing the full advantage of such a filter, however, may require certain staging modifications. A staging methodology is discussed that should be applicable to the CYCLOPS, 381, and SHIVA systems. Experiments are in progress on CYCLOPS that will address directly the utility of the proposed approach

Study of a high spatial resolution {sup 10}B-based thermal neutron detector for application in neutron reflectometry: the Multi-Blade prototype

Energy Technology Data Exchange (ETDEWEB)

Piscitelli, F; Buffet, J C; Clergeau, J F; Cuccaro, S; Guérard, B; Khaplanov, A; Manna, Q La; Rigal, J M; Esch, P Van, E-mail: piscitelli@ill.fr [Institut Laue-Langevin (ILL), 6, Jules Horowitz, 38042, Grenoble (France)

2014-03-01

Although for large area detectors it is crucial to find an alternative to detect thermal neutrons because of the {sup 3}He shortage, this is not the case for small area detectors. Neutron scattering science is still growing its instruments' power and the neutron flux a detector must tolerate is increasing. For small area detectors the main effort is to expand the detectors' performances. At Institut Laue-Langevin (ILL) we developed the Multi-Blade detector which wants to increase the spatial resolution of {sup 3}He-based detectors for high flux applications. We developed a high spatial resolution prototype suitable for neutron reflectometry instruments. It exploits solid {sup 10}B-films employed in a proportional gas chamber. Two prototypes have been constructed at ILL and the results obtained on our monochromatic test beam line are presented here.

Towards democracy in spatial planning through spatial information built by communities: The investigation of spatial information built by citizens from participatory mapping to volunteered geographic information in Indonesia

Science.gov (United States)

Yudono, Adipandang

2017-06-01

Recently, crowd-sourced information is used to produce and improve collective knowledge and community capacity building. Triggered by broadening and expanding access to the Internet and cellular telephones, the utilisation of crowd-sourcing for policy advocacy, e-government and e-participation has increased globally [1]. Crowd-sourced information can conceivably support government’s or general social initiatives to inform, counsel, and cooperate, by engaging subjects and empowering decentralisation and democratization [2]. Crowd-sourcing has turned into a major technique for interactive mapping initiatives by urban or rural community because of its capability to incorporate a wide range of data. Continuously accumulated spatial data can be sorted, layered, and envisioned in ways that even beginners can comprehend with ease. Interactive spatial visualization has the possibility to be a useful democratic planning tool to empower citizens participating in spatial data provision and sharing in government programmes. Since the global emergence of World Wide Web (WWW) technology, the interaction between information providers and users has increased. Local communities are able to produce and share spatial data to produce web interfaces with territorial information in mapping application programming interfaces (APIs) public, such as Google maps, OSM and Wikimapia [3][4][5]. In terms of the democratic spatial planning action, Volunteered Geographic Information (VGI) is considered an effective voluntary method of helping people feel comfortable with the technology and other co-participants in order to shape coalitions of local knowledge. This paper has aim to investigate ‘How is spatial data created by citizens used in Indonesia?’ by discussing the characteristics of spatial data usage by citizens to support spatial policy formulation, starting with the history of participatory mapping to current VGI development in Indonesia.

Spatial filtering velocimetry of objective speckles for measuring out-of-plane motion

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Yura, H. T.; Hanson, Steen Grüner

2012-01-01

This paper analyzes the dynamics of objective laser speckles as the distance between the object and the observation plane continuously changes. With the purpose of applying optical spatial filtering velocimetry to the speckle dynamics, in order to measure out-of-plane motion in real time......, a rotational symmetric spatial filter is designed. The spatial filter converts the speckle dynamics into a photocurrent with a quasi-sinusoidal response to the out-of-plane motion. The spatial filter is here emulated with a CCD camera, and is tested on speckles arising from a real application. The analysis...

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...

Balancing geo-privacy and spatial patterns in epidemiological studies

Directory of Open Access Journals (Sweden)

Chien-Chou Chen

2017-11-01

Full Text Available To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker intended to mask the residential locations of patients or cases in a geographic information system (GIS. To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool’s performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100 were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals’ spatial information.

AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

Science.gov (United States)

Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya

2015-01-01

A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis. PMID:25678911

AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

Directory of Open Access Journals (Sweden)

Xiang Zhao

2015-01-01

Full Text Available A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs which can (1 assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2 allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

APPLICATION OF SPATIAL MODELLING APPROACHES, SAMPLING STRATEGIES AND 3S TECHNOLOGY WITHIN AN ECOLGOCIAL FRAMWORK

Directory of Open Access Journals (Sweden)

H.-C. Chen

2012-07-01

Full Text Available How to effectively describe ecological patterns in nature over broader spatial scales and build a modeling ecological framework has become an important issue in ecological research. We test four modeling methods (MAXENT, DOMAIN, GLM and ANN to predict the potential habitat of Schima superba (Chinese guger tree, CGT with different spatial scale in the Huisun study area in Taiwan. Then we created three sampling design (from small to large scales for model development and validation by different combinations of CGT samples from aforementioned three sites (Tong-Feng watershed, Yo-Shan Mountain, and Kuan-Dau watershed. These models combine points of known occurrence and topographic variables to infer CGT potential spatial distribution. Our assessment revealed that the method performance from highest to lowest was: MAXENT, DOMAIN, GLM and ANN on small spatial scale. The MAXENT and DOMAIN two models were the most capable for predicting the tree's potential habitat. However, the outcome clearly indicated that the models merely based on topographic variables performed poorly on large spatial extrapolation from Tong-Feng to Kuan-Dau because the humidity and sun illumination of the two watersheds are affected by their microterrains and are quite different from each other. Thus, the models developed from topographic variables can only be applied within a limited geographical extent without a significant error. Future studies will attempt to use variables involving spectral information associated with species extracted from high spatial, spectral resolution remotely sensed data, especially hyperspectral image data, for building a model so that it can be applied on a large spatial scale.

Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

Science.gov (United States)

Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

Non-standard spatial statistics and spatial econometrics

CERN Document Server

Griffith, Daniel A

2011-01-01

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

Free-space communication with over 100 spatial modes

CSIR Research Space (South Africa)

Rosales-Guzmán, C

2016-10-01

Full Text Available Congress 2016: Advanced Solid State Lasers (ASSL); Applications of Lasers for Sensing and Free Space Communications (LS&C), 30 October - 3 November 2016, Boston, Massachusetts, United States Free-space communication with over 100 spatial modes...

Pre-aggregation for Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

Motivated by the increasing need to analyze complex uncertain multidimensional data (e.g., in order to optimize and personalize location-based services), this paper proposes novel types of {\\em probabilistic} OLAP queries that operate on aggregate values that are probability distributions...... and the techniques to process these queries. The paper also presents the methods for computing the probability distributions, which enables pre-aggregation, and for using the pre-aggregated distributions for further aggregation. In order to achieve good time and space efficiency, the methods perform approximate...... multidimensional data analysis that is considered in this paper (i.e., approximate processing of probabilistic OLAP queries over probability distributions)....

Structural properties of recursively partitionable graphs with connectivity 2

DEFF Research Database (Denmark)

Baudon, Olivier; Bensmail, Julien; Foucaud, Florent

2017-01-01

, namely the ones of being online arbitrarily partitionable and recursively arbitrarily partitionable (OL-AP and R-AP for short, respectively), in which the subgraphs induced by a partition of G must not only be con-nected but also ful_l additional conditions. In this paper, we point out some structural...... properties of OL-AP and R-AP graphs with connectivity 2. In particular, we show that deleting a cut pair of these graphs results in a graph with a bounded number of components, some of whom have a small number of vertices. We obtain these results by studying a simple class of 2-connected graphs called...

Development of Spatial Database for Regional Development in Romania

Directory of Open Access Journals (Sweden)

Anda BELCIU (VELICANU

2014-01-01

Full Text Available eographical Information Systems are used in solving many regional development related problems, around the world. Starting from some national programs to famous international ones, such as INSPIRE program, each such initiative uses geospatial data as well in the process of building regional development strategies. This paper presents the main technical components of a geographical information system, meaning the spatial database, the web mapping server and the APIs used to embed the maps into web applications. The development steps for a pre-alpha version of a web GIS application dedicated to the regional development in Romania are also shown. The software tools which were integrated in order to develop the online application were Oracle Spatial, where geospatial data was stored, GeoServer, an open source web mapping server used to generate the map out of the data from Oracle Spatial’s tables and ASP.NET as a web framework for building the website.

Spatial evaluation of larvae of Culicidae (Diptera from different breeding sites: application of a geospatial method and implications for vector control

Directory of Open Access Journals (Sweden)

Rafael Piovezan

2012-09-01

Full Text Available Spatial evaluation of Culicidae (Diptera larvae from different breeding sites: application of a geospatial method and implications for vector control. This study investigates the spatial distribution of urban Culicidae and informs entomological monitoring of species that use artificial containers as larval habitats. Collections of mosquito larvae were conducted in the São Paulo State municipality of Santa Bárbara d' Oeste between 2004 and 2006 during house-to-house visits. A total of 1,891 samples and nine different species were sampled. Species distribution was assessed using the kriging statistical method by extrapolating municipal administrative divisions. The sampling method followed the norms of the municipal health services of the Ministry of Health and can thus be adopted by public health authorities in disease control and delimitation of risk areas. Moreover, this type of survey and analysis can be employed for entomological surveillance of urban vectors that use artificial containers as larval habitat.

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

NARCIS (Netherlands)

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

1997-01-01

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

TERRITORIAL AND SPATIAL IDENTITY: NEW APPROARCH TO THE BASIC CONCEPTS

Directory of Open Access Journals (Sweden)

I. Yu. Okunev

2018-01-01

Full Text Available Contrary to popular belief, the spatial aspect of political processes is  determined not only by objective factors. Space affects politics not  only directly, but also indirectly, through subjective and sometimes  distorted notions of space, formed by man. To study this subjective world, geography has its own terminology, some of which  are in dialectical connection with the concepts of «objective»  geography (territoriality vs. spatiality, absolute vs. relative space,  and some are unique for the discourse of this science (heterotopy,  spatial inversion, spatial experience, the place of memory, spatial  myth, and co-spatiality. The key to political geography is the notion of territorial and spatial identity, because they link ideas  about space with the political behavior of the individual. Recently,  the applied sphere of political geography has been actively  developing, based on the application of identity knowledge - territory branding based on place policy.

Topic Modeling for OLAP on Multidimensional Text Databases: Topic Cube and its Applications

Data.gov (United States)

National Aeronautics and Space Administration — As the amount of textual information grows explosively in various kinds of business systems, it becomes more and more desirable to analyze both structured data...

Application of Parallel Hierarchical Matrices in Spatial Statistics and Parameter Identification

KAUST Repository

Litvinenko, Alexander

2018-04-20

Parallel H-matrices in spatial statistics 1. Motivation: improve statistical model 2. Tools: Hierarchical matrices [Hackbusch 1999] 3. Matern covariance function and joint Gaussian likelihood 4. Identification of unknown parameters via maximizing Gaussian log-likelihood 5. Implementation with HLIBPro

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...

Nuclear waste repository characterization: a spatial estimation/identification approach

International Nuclear Information System (INIS)

Candy, J.V.; Mao, N.

1981-03-01

This paper considers the application of spatial estimation techniques to a groundwater aquifer and geological borehole data. It investigates the adequacy of these techniques to reliably develop contour maps from various data sets. The practice of spatial estimation is discussed and the estimator is then applied to a groundwater aquifer system and a deep geological formation. It is shown that the various statistical models must first be identified from the data and evaluated before reasonable results can be expected

Application of decision support systems in county urban planning: a proposal for Macaé county

Directory of Open Access Journals (Sweden)

GALANTE, A. C.

2008-06-01

Full Text Available The Macaé County is one of the greatest economy of the state of Rio de Janeiro. With the use of the information technology is possible to create a powerful tool for supporting the decision making processing for this County, aiding the process of improvement of life quality. For that one, intends to use a Decision Support System able to give different kind of information of County areas, like health and education. For the union of all information the datawarehouse technology will be used. For query implementation the technologies of OLAP and GIS are used together. Therefore, those technologies together make a powerful tool for aiding the decision making process of the Macaé County.

ASSET Queries: A Set-Oriented and Column-Wise Approach to Modern OLAP

Science.gov (United States)

Chatziantoniou, Damianos; Sotiropoulos, Yannis

Modern data analysis has given birth to numerous grouping constructs and programming paradigms, way beyond the traditional group by. Applications such as data warehousing, web log analysis, streams monitoring and social networks understanding necessitated the use of data cubes, grouping variables, windows and MapReduce. In this paper we review the associated set (ASSET) concept and discuss its applicability in both continuous and traditional data settings. Given a set of values B, an associated set over B is just a collection of annotated data multisets, one for each b(B. The goal is to efficiently compute aggregates over these data sets. An ASSET query consists of repeated definitions of associated sets and aggregates of these, possibly correlated, resembling a spreadsheet document. We review systems implementing ASSET queries both in continuous and persistent contexts and argue for associated sets' analytical abilities and optimization opportunities.

Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

Directory of Open Access Journals (Sweden)

A. Venäläinen

2017-07-01

Full Text Available The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount of wind damage for certain forest stand configurations.

Technical Progress and Development Directions of Oceanic Spatial Information Datum

Directory of Open Access Journals (Sweden)

BAO Jingyang

2017-10-01

Full Text Available This paper briefly analyzes the basic development and technical situation of oceanic spatial information datum, reviews the main processes of oceanic vertical datum and correlative oceanic tidal study, such as improvement and perfect methods of determining tidal station vertical datum, realizing form of vertical datum controlled by tidal station, effect on maintaining vertical datum by long-term tidal station, oceanic tidal model establishing, and also construction and transformation of tidal datum, and then forecasts the key development directions of oceanic spatial information datum on high-accuracy marine position service, vertical datum and the transferring model refinement and spatial datum application.

Empirical spatial econometric modelling of small scale neighbourhood

Science.gov (United States)

Gerkman, Linda

2012-07-01

The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

Science.gov (United States)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Detecting spatial regimes in ecosystems | Science Inventory ...

Science.gov (United States)

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

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.

Toward seamless hydrologic predictions across spatial scales

Directory of Open Access Journals (Sweden)

L. Samaniego

2017-09-01

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

Toward seamless hydrologic predictions across spatial scales

Science.gov (United States)

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

2017-09-01

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

Metaoptics for Spectral and Spatial Beam Manipulation

Science.gov (United States)

Raghu Srimathi, Indumathi

Laser beam combining and beam shaping are two important areas with applications in optical communications, high power lasers, and atmospheric propagation studies. In this dissertation, metaoptical elements have been developed for spectral and spatial beam shaping, and multiplexing. Beams carrying orbital angular momentum (OAM), referred to as optical vortices, have unique propagation properties. Optical vortex beams carrying different topological charges are orthogonal to each other and have low inter-modal crosstalk which allows for them to be (de)multiplexed. Efficient spatial (de)multiplexing of these beams have been carried out by using diffractive optical geometrical coordinate transformation elements. The spatial beam combining technique shown here is advantageous because the efficiency of the system is not dependent on the number of OAM states being combined. The system is capable of generating coaxially propagating beams in the far-field and the beams generated can either be incoherently or coherently multiplexed with applications in power scaling and dynamic intensity profile manipulations. Spectral beam combining can also be achieved with the coordinate transformation elements. The different wavelengths emitted by fiber sources can be spatially overlapped in the far-field plane and the generated beams are Bessel-Gauss in nature with enhanced depth of focus properties. Unique system responses and beam shapes in the far-field can be realized by controlling amplitude, phase, and polarization at the micro-scale. This has been achieved by spatially varying the structural parameters at the subwavelength scale and is analogous to local modification of material properties. With advancements in fabrication technology, it is possible to control not just the lithographic process, but also the deposition process. In this work, a unique combination of spatial structure variations in conjunction with the conformal coating properties of an atomic layer deposition tool

The Theory and Assessment of Spatial Straightness Error Matched New Generation GPS

International Nuclear Information System (INIS)

Zhang, X B; Sheng, X L; Jiang, X Q; Li, Z

2006-01-01

In order to assess spatial straightness error matched new generation Dimensional Geometrical Product Specification and Verification (GPS), the theory of spatial straightness error assessing is proposed and its advantages are analyzed based on metrology and statistics in this paper. Then, the assessing parameter system is proposed and it is testified in real application comparing to assessment result of the geometric tolerance theory. Statistical parameters of this assessing system post the different characteristics of spatial straightness error, and can reveal the impact of spatial straightness error on the accessory function more roundly to complement the single assessing parameter of geometrical tolerance for straightness error. The statistical spatial straightness tolerance and statistical spatial straightness error proposed in this paper is possible to be applied in evaluation of other error of form, orientation, location and run-out

Simple spatial scaling rules behind complex cities.

Science.gov (United States)

Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2017-11-28

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

Landscape Modelling and Simulation Using Spatial Data

Directory of Open Access Journals (Sweden)

Amjed Naser Mohsin AL-Hameedawi

2017-08-01

Full Text Available In this paper a procedure was performed for engendering spatial model of landscape acclimated to reality simulation. This procedure based on combining spatial data and field measurements with computer graphics reproduced using Blender software. Thereafter that we are possible to form a 3D simulation based on VIS ALL packages. The objective was to make a model utilising GIS, including inputs to the feature attribute data. The objective of these efforts concentrated on coordinating a tolerable spatial prototype, circumscribing facilitation scheme and outlining the intended framework. Thus; the eventual result was utilized in simulation form. The performed procedure contains not only data gathering, fieldwork and paradigm providing, but extended to supply a new method necessary to provide the respective 3D simulation mapping production, which authorises the decision makers as well as investors to achieve permanent acceptance an independent navigation system for Geoscience applications.

Multivariate max-stable spatial processes

KAUST Repository

Genton, Marc G.; Padoan, S. A.; Sang, H.

2015-01-01

Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. We develop inference for the models based on composite likelihoods. We present results of Monte Carlo simulations and an application to daily maximum wind speed and wind gust.

Multivariate max-stable spatial processes

KAUST Repository

Genton, Marc G.

2015-02-11

Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. We develop inference for the models based on composite likelihoods. We present results of Monte Carlo simulations and an application to daily maximum wind speed and wind gust.

RANCANG BANGUN SISTEM INFORMASI INVENTORI MENGGUNAKAN METODE ASSOCIATION RULES DI CV. DAMAR LANGIT

Directory of Open Access Journals (Sweden)

Zainul Fanani

2012-03-01

Kata Kunci : Sistem informasi, Inventori, Sistem Pendukung Keputusan (Decisition Support System, Association Rule, Data Mining, OLAP (Online Analitic Processing, Algoritma Apriori, Support, Confidence, Lift Rasio.

Spatial correlation genetic algorithm for fractal image compression

International Nuclear Information System (INIS)

Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

2006-01-01

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

QR code optical encryption using spatially incoherent illumination

Science.gov (United States)

Cheremkhin, P. A.; Krasnov, V. V.; Rodin, V. G.; Starikov, R. S.

2017-02-01

Optical encryption is an actively developing field of science. The majority of encryption techniques use coherent illumination and suffer from speckle noise, which severely limits their applicability. The spatially incoherent encryption technique does not have this drawback, but its effectiveness is dependent on the Fourier spectrum properties of the image to be encrypted. The application of a quick response (QR) code in the capacity of a data container solves this problem, and the embedded error correction code also enables errorless decryption. The optical encryption of digital information in the form of QR codes using spatially incoherent illumination was implemented experimentally. The encryption is based on the optical convolution of the image to be encrypted with the kinoform point spread function, which serves as an encryption key. Two liquid crystal spatial light modulators were used in the experimental setup for the QR code and the kinoform imaging, respectively. The quality of the encryption and decryption was analyzed in relation to the QR code size. Decryption was conducted digitally. The successful decryption of encrypted QR codes of up to 129  ×  129 pixels was demonstrated. A comparison with the coherent QR code encryption technique showed that the proposed technique has a signal-to-noise ratio that is at least two times higher.

Development of a Discrete Spatial-Temporal SEIR Simulator for Modeling Infectious Diseases

Energy Technology Data Exchange (ETDEWEB)

McKenna, S.A.

2000-11-01

Multiple techniques have been developed to model the temporal evolution of infectious diseases. Some of these techniques have also been adapted to model the spatial evolution of the disease. This report examines the application of one such technique, the SEIR model, to the spatial and temporal evolution of disease. Applications of the SEIR model are reviewed briefly and an adaptation to the traditional SEIR model is presented. This adaptation allows for modeling the spatial evolution of the disease stages at the individual level. The transmission of the disease between individuals is modeled explicitly through the use of exposure likelihood functions rather than the global transmission rate applied to populations in the traditional implementation of the SEIR model. These adaptations allow for the consideration of spatially variable (heterogeneous) susceptibility and immunity within the population. The adaptations also allow for modeling both contagious and non-contagious diseases. The results of a number of numerical experiments to explore the effect of model parameters on the spread of an example disease are presented.

Spatial Landau-Zener-Stueckelberg interference in spinor Bose-Einstein condensates

International Nuclear Information System (INIS)

Zhang, J.-N.; Sun, C.-P.; Yi, S.; Nori, Franco

2011-01-01

We investigate the Stueckelberg oscillations of a spin-1 Bose-Einstein condensate subject to a spatially inhomogeneous transverse magnetic field and a periodic longitudinal field. We show that the time-domain Stueckelberg oscillations result in modulations in the density profiles of all spin components due to the spatial inhomogeneity of the transverse field. This phenomenon represents the Landau-Zener-Stueckelberg interference in the space domain. Since the magnetic dipole-dipole interaction between spin-1 atoms induces an inhomogeneous effective magnetic field, interference fringes also appear if a dipolar spinor condensate is driven periodically. We also point out some potential applications of this spatial Landau-Zener-Stuekelberg interference.

High spatial precision nano-imaging of polarization-sensitive plasmonic particles

Science.gov (United States)

Liu, Yunbo; Wang, Yipei; Lee, Somin Eunice

2018-02-01

Precise polarimetric imaging of polarization-sensitive nanoparticles is essential for resolving their accurate spatial positions beyond the diffraction limit. However, conventional technologies currently suffer from beam deviation errors which cannot be corrected beyond the diffraction limit. To overcome this issue, we experimentally demonstrate a spatially stable nano-imaging system for polarization-sensitive nanoparticles. In this study, we show that by integrating a voltage-tunable imaging variable polarizer with optical microscopy, we are able to suppress beam deviation errors. We expect that this nano-imaging system should allow for acquisition of accurate positional and polarization information from individual nanoparticles in applications where real-time, high precision spatial information is required.

What Is Spatio-Temporal Data Warehousing?

Science.gov (United States)

Vaisman, Alejandro; Zimányi, Esteban

In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.

A new multidimensional population health indicator for policy makers: absolute level, inequality and spatial clustering - an empirical application using global sub-national infant mortality data

Directory of Open Access Journals (Sweden)

Benn K.D. Sartorius

2014-11-01

Full Text Available The need for a multidimensional measure of population health that accounts for its distribution remains a central problem to guide the allocation of limited resources. Absolute proxy measures, like the infant mortality rate (IMR, are limi- ted because they ignore inequality and spatial clustering. We propose a novel, three-part, multidimensional mortality indi- cator that can be used as the first step to differentiate interventions in a region or country. The three-part indicator (MortalityABC index combines absolute mortality rate, the Theil Index to calculate mortality inequality and the Getis-Ord G statistic to determine the degree of spatial clustering. The analysis utilises global sub-national IMR data to empirically illu- strate the proposed indicator. The three-part indicator is mapped globally to display regional/country variation and further highlight its potential application. Developing countries (e.g. in sub-Saharan Africa display high levels of absolute mortality as well as variable mortality inequality with evidence of spatial clustering within certain sub-national units (“hotspots”. Although greater inequality is observed outside developed regions, high mortality inequality and spatial clustering are com- mon in both developed and developing countries. Significant positive correlation was observed between the degree of spatial clustering and absolute mortality. The proposed multidimensional indicator should prove useful for spatial allocation of healthcare resources within a country, because it can prompt a wide range of policy options and prioritise high-risk areas. The new indicator demonstrates the inadequacy of IMR as a single measure of population health, and it can also be adapted to lower administrative levels within a country and other population health measures.

Spatial Uncertainty Model for Visual Features Using a Kinect™ Sensor

Directory of Open Access Journals (Sweden)

Jae-Han Park

2012-06-01

Full Text Available This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

Spatial uncertainty model for visual features using a Kinect™ sensor.

Science.gov (United States)

Park, Jae-Han; Shin, Yong-Deuk; Bae, Ji-Hun; Baeg, Moon-Hong

2012-01-01

This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

Spatial repellents on strips of camouflage netting reduce mosquito collections in a field environment

Science.gov (United States)

Barrier treatments can be effective in reducing host seeking mosquito vectors and provide an additional layer of passive defense, reducing disease risk. Devices designed to release spatial repellents or direct application of spatial repellents to artificial surfaces can serve as efficient barriers r...

APPLICABILITY OF VARIOUS INTERPOLATION APPROACHES FOR HIGH RESOLUTION SPATIAL MAPPING OF CLIMATE DATA IN KOREA

Directory of Open Access Journals (Sweden)

A. Jo

2018-04-01

Full Text Available The purpose of this study is to create a new dataset of spatially interpolated monthly climate data for South Korea at high spatial resolution (approximately 30m by performing various spatio-statistical interpolation and comparing with forecast LDAPS gridded climate data provided from Korea Meterological Administration (KMA. Automatic Weather System (AWS and Automated Synoptic Observing System (ASOS data in 2017 obtained from KMA were included for the spatial mapping of temperature and rainfall; instantaneous temperature and 1-hour accumulated precipitation at 09:00 am on 31th March, 21th June, 23th September, and 24th December. Among observation data, 80 percent of the total point (478 and remaining 120 points were used for interpolations and for quantification, respectively. With the training data and digital elevation model (DEM with 30 m resolution, inverse distance weighting (IDW, co-kriging, and kriging were performed by using ArcGIS10.3.1 software and Python 3.6.4. Bias and root mean square were computed to compare prediction performance quantitatively. When statistical analysis was performed for each cluster using 20 % validation data, co kriging was more suitable for spatialization of instantaneous temperature than other interpolation method. On the other hand, IDW technique was appropriate for spatialization of precipitation.

Chapter J: Issues and challenges in the application of geostatistics and spatial-data analysis to the characterization of sand-and-gravel resources

Science.gov (United States)

Hack, Daniel R.

2005-01-01

Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors

SPATIAL UNCERTAINTY IN LINE-SURFACE INTERSECTIONS WITH APPLICATIONS TO PHOTOGRAMMETRY

Directory of Open Access Journals (Sweden)

J. Marshall

2012-07-01

Full Text Available The fields of photogrammetry and computer vision routinely use line-surface intersections to determine the point where a line intersects with a surface. The object coordinates of the intersection point can be found using standard geometric and numeric algorithms, however expressing the spatial uncertainty at the intersection point may be challenging, especially when the surface morphology is complex. This paper describes an empirical method to characterize the unknown spatial uncertainty at the intersection point by propagating random errors in the stochastic model using repeated random sampling methods. These methods accommodate complex surface morphology and nonlinearities in the functional model, however the penalty is the resulting probability density function associated with the intersection point may be non-Gaussian in nature. A formal hypothesis test is presented to show that straightforward statistical inference tools are available whether the data is Gaussian or not. The hypothesis test determines whether the computed intersection point is consistent with an externally-derived known truth point. A numerical example demonstrates the approach in a photogrammetric setting with a single frame image and a gridded terrain elevation model. The results show that uncertainties produced by the proposed empirical method are intuitive and can be assessed with conventional methods found in textbook hypothesis testing.

Design and realization of tourism spatial decision support system based on GIS

Science.gov (United States)

Ma, Zhangbao; Qi, Qingwen; Xu, Li

2008-10-01

In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

Spatial Relation Predicates in Topographic Feature Semantics

Science.gov (United States)

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Encouraging Spatial Talk: Using Children's Museums to Bolster Spatial Reasoning

Science.gov (United States)

Polinsky, Naomi; Perez, Jasmin; Grehl, Mora; McCrink, Koleen

2017-01-01

Longitudinal spatial language intervention studies have shown that greater exposure to spatial language improves children's performance on spatial tasks. Can short naturalistic, spatial language interactions also evoke improved spatial performance? In this study, parents were asked to interact with their child at a block wall exhibit in a…

SPATIAL DISTRIBUTION OF POVERTY AT DIFFERENT SCALES

Directory of Open Access Journals (Sweden)

Gandhi PAWITAN

2010-01-01

Full Text Available Poverty mapping is usually developed from some sources of data, such as from census and survey data. In some practical application, the poverty was measured usually by household income or expenditure of daily basic consumption. Using different scales and zoning on a particular set of spatial data may leads to problems in interpreting the results. In practice, organizations publish statistics and maps at a particular area level. Minot and Baulch (2005a discussed some consequences of using aggregated level data in poverty mapping, which may affect the validity of the output. The key point of this paper is to compare spatial distribution of the poverty at two different scale, which is the province and district level. How the spatial distribution of the poverty at province level can be use to infer the distribution at the district level. The geographical weighted regression will be applied, and the poverty data of Vietnam will be used as an illustration.

Spatial Indexing for Data Searching in Mobile Sensing Environments.

Science.gov (United States)

Zhou, Yuchao; De, Suparna; Wang, Wei; Moessner, Klaus; Palaniswami, Marimuthu S

2017-06-18

Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.

Multilevel Modelling with Spatial Interaction Effects with Application to an Emerging Land Market in Beijing, China.

Directory of Open Access Journals (Sweden)

Guanpeng Dong

Full Text Available This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic multilevel models are not specifically spatial. Lower level units may be nested into higher level ones based on a geographical hierarchy (or a membership structure--for example, census zones into regions but the actual locations of the units and the distances between them are not directly considered: what matters is the groupings but not how close together any two units are within those groupings. As a consequence, spatial interaction effects are neither modelled nor measured, confounding group effects (understood as some sort of contextual effect that acts 'top down' upon members of a group with proximity effects (some sort of joint dependency that emerges between neighbours. To deal with this, we incorporate spatial simultaneous autoregressive processes into both the outcome variable and the higher level residuals. To assess the performance of the proposed method and the classic multilevel model, a series of Monte Carlo simulations are conducted. The results show that the proposed method performs well in retrieving the true model parameters whereas the classic multilevel model provides biased and inefficient parameter estimation in the presence of spatial interactions. An important implication of the study is to be cautious of an apparent neighbourhood effect in terms of both its magnitude and statistical significance if spatial interaction effects at a lower level are suspected. Applying the new approach to a two-level land price data set for Beijing, China, we find significant spatial interactions at both the land parcel and district levels.

Application of Parallel Hierarchical Matrices and Low-Rank Tensors in Spatial Statistics and Parameter Identification

KAUST Repository

Litvinenko, Alexander

2018-03-12

Part 1: Parallel H-matrices in spatial statistics 1. Motivation: improve statistical model 2. Tools: Hierarchical matrices 3. Matern covariance function and joint Gaussian likelihood 4. Identification of unknown parameters via maximizing Gaussian log-likelihood 5. Implementation with HLIBPro. Part 2: Low-rank Tucker tensor methods in spatial statistics

Spatial-temporal noise reduction method optimized for real-time implementation

Science.gov (United States)

Romanenko, I. V.; Edirisinghe, E. A.; Larkin, D.

2013-02-01

Image de-noising in the spatial-temporal domain has been a problem studied in-depth in the field of digital image processing. However complexity of algorithms often leads to high hardware resource usage, or computational complexity and memory bandwidth issues, making their practical use impossible. In our research we attempt to solve these issues with an optimized implementation of a practical spatial-temporal de-noising algorithm. Spatial-temporal filtering was performed in Bayer RAW data space, which allowed us to benefit from predictable sensor noise characteristics and reduce memory bandwidth requirements. The proposed algorithm efficiently removes different kinds of noise in a wide range of signal to noise ratios. In our algorithm the local motion compensation is performed in Bayer RAW data space, while preserving the resolution and effectively improving the signal to noise ratios of moving objects. The main challenge for the use of spatial-temporal noise reduction algorithms in video applications is the compromise between the quality of the motion prediction and the complexity of the algorithm and required memory bandwidth. In photo and video applications it is very important that moving objects should stay sharp, while the noise is efficiently removed in both the static background and moving objects. Another important use case is the case when background is also non-static as well as the foreground where objects are also moving. Taking into account the achievable improvement in PSNR (on the level of the best known noise reduction techniques, like VBM3D) and low algorithmic complexity, enabling its practical use in commercial video applications, the results of our research can be very valuable.

Evaluating Motion. Spatial User Behavior in Virtual Environments

DEFF Research Database (Denmark)

Drachen, Anders; Canossa, Alessandro

2011-01-01

User-behaviour analysis has only recently been adapted to the context of the virtual world domain and remains limited in its application. Behaviour analysis is based on instrumentation data, automated, detailed, quantitative information about user behaviour within the virtual environment (VE......) of digital games. A key advantage of the method in comparison with existing user-research methods, such as usability- and playability-testing is that it permits very large sample sizes. Furthermore, games are in the vast majority of cases based on spatial, VEs within which the players operate and through...... which they experience the games. Therefore, spatial behaviour analyses are useful to game research and design. In this paper, spatial analysis methods are introduced and arguments posed for their use in user-behaviour analysis. Case studies involving data from thousands of players are used to exemplify...

Charge-coupled devices for particle detection with high spatial resolution

International Nuclear Information System (INIS)

Farley, F.J.; Damerell, C.J.S.; Gillman, A.R.; Wickens, F.J.

1980-10-01

The results of a study of the possible application of a thin microelectronic device (the charge-coupled device) to high energy physics as particle detectors with good spatial resolution which can distinguish between tracks emerging from the primary vertex and those from secondary vertices due to the decay of short lived particles with higher flavours, are reported. Performance characteristics indicating the spatial resolution, particle discrimination, time resolution, readout time and lifetime of such detectors have been obtained. (U.K.)

THE DEVELOPMENT OF MARINE SPATIAL PLANNING AND ITS APPLICATION FOR FLOATING FISH NET CULTURE

OpenAIRE

Dewayany Sutrisno

2017-01-01

Marine spatial planning has become the crucial issues for an archipelagic state such as Indonesia. The global market demand on marine economic species has been initiated the exploitation of the marine species which will become the hindrance in maintaining the sustainable marine biodiversity. Besides that, the degradation of marine species will also become the problem for traditional fishermen. Therefore, a model has to be employed to spatially manage the coastal waters as the alternative for ...

PERANGKAT LUNAK ANTAR MUKA GRAFIS SCHEMA DAN CUBE EDITOR MS ANALYSIS SERVICE BERBASIS WEB

Directory of Open Access Journals (Sweden)

Faizal Johan

2007-01-01

Full Text Available Aplikasi Web telah menjadi bagian yang tidak terpisahkan lagi dalam kehidupan sehari-hari. Seiring dengan meningkatnya teknologi internet membuat seorang administrator tidak perlu berada didepan komputer server untuk dapat melakukan pekerjaan administratif seperti membuat analisis proses secara online dari sebuah schema database untuk dibuat schema cube (data warehousing dan melakukan perubahan pada schema yang sudah dibuat.Untuk dapat melakukan hal tersebut SQL Server 7.0 maupun SQL Server 2000 telah menyediakan fasilitas pengaksesan tabel dimensi, cube, relasi dan koneksi database dalam Analysis Manager menggunakan DSO (Decision Support Object library component MS OLAP. Dengan adanya DSO connection, seorang administrator dapat memanipulasi schema, tabel, cube, dimension, relasi suatu schema cube dari database SQL Server secara langsung dengan menggunakan bahasa pemrograman yang mendukung, seperti MS Visual Basic, VBScript, MS Visual C++, MS.Net. Dalam penelitian ini dibuat aplikasi berbasis web yang merupakan tahap awal dari OLAP (Online Analytical Processing suatu schema database dengan menggunakan SQL Analysis Service, Analysis Manager yang memungkinkan seorang administrator database untuk dapat melakukan pekerjaan administratif khususnya membuat schema dan cube (fact table dari database yang dianalisis, membuat dan mengedit dimensi, dimana saja tanpa harus berada di komputer server. Kata Kunci : DSO, Cube, Measure,GUI, dimensi, fact table, ADO MD, SQL DMO, OLAP.

Natural language processing using online analytic processing for assessing recommendations in radiology reports.

Science.gov (United States)

Dang, Pragya A; Kalra, Mannudeep K; Blake, Michael A; Schultz, Thomas J; Stout, Markus; Lemay, Paul R; Freshman, David J; Halpern, Elkan F; Dreyer, Keith J

2008-03-01

The study purpose was to describe the use of natural language processing (NLP) and online analytic processing (OLAP) for assessing patterns in recommendations in unstructured radiology reports on the basis of patient and imaging characteristics, such as age, gender, referring physicians, radiology subspecialty, modality, indications, diseases, and patient status (inpatient vs outpatient). A database of 4,279,179 radiology reports from a single tertiary health care center during a 10-year period (1995-2004) was created. The database includes reports of computed tomography, magnetic resonance imaging, fluoroscopy, nuclear medicine, ultrasound, radiography, mammography, angiography, special procedures, and unclassified imaging tests with patient demographics. A clinical data mining and analysis NLP program (Leximer, Nuance Inc, Burlington, Massachusetts) in conjunction with OLAP was used for classifying reports into those with recommendations (I(REC)) and without recommendations (N(REC)) for imaging and determining I(REC) rates for different patient age groups, gender, imaging modalities, indications, diseases, subspecialties, and referring physicians. In addition, temporal trends for I(REC) were also determined. There was a significant difference in the I(REC) rates in different age groups, varying between 4.8% (10-19 years) and 9.5% (>70 years) (P OLAP revealed considerable differences between recommendation trends for different imaging modalities and other patient and imaging characteristics.

Children's Spatial Thinking: Does Talk about the Spatial World Matter?

Science.gov (United States)

Pruden, Shannon M.; Levine, Susan C.; Huttenlocher, Janellen

2011-01-01

In this paper we examine the relations between parent spatial language input, children's own production of spatial language, and children's later spatial abilities. Using a longitudinal study design, we coded the use of spatial language (i.e. words describing the spatial features and properties of objects; e.g. big, tall, circle, curvy, edge) from…

Planning of spatial development of tourism based on the example of spatial plan of Subotica municipality

Directory of Open Access Journals (Sweden)

Šećerov Velimir

2008-01-01

Full Text Available Planning of tourism development and its spatial disposition in Europe and world today are an important segment of the overall economic development. Having in mind its important economic and social functions, as well as its capability to intensify its other economic branches (agricultural and economic potentials, services of various types, transport and other in a certain territory, it is necessary to realize a precise valorization of tourist values in the spatial plan of municipality and to conclude at what point and at which places the tourism can represent on of development components of the entire economy of the territory to be planed. The example of the spatial plan of Subotica and main guidelines, concept and planning priorities which can be expected in the forthcoming period are presented in this paper. It is without any doubt that the municipality of Subotica with its geostrategic position, the proximity of the EU and important natural and cultural tourist potentials is a suitable space for application of contemporary principles of the tourism development planning and their correlation with other segments of integral development for the whole municipality.

IMPROVING NEAREST NEIGHBOUR SEARCH IN 3D SPATIAL ACCESS METHOD

Directory of Open Access Journals (Sweden)

A. Suhaibaha

2016-10-01

Full Text Available Nearest Neighbour (NN is one of the important queries and analyses for spatial application. In normal practice, spatial access method structure is used during the Nearest Neighbour query execution to retrieve information from the database. However, most of the spatial access method structures are still facing with unresolved issues such as overlapping among nodes and repetitive data entry. This situation will perform an excessive Input/Output (IO operation which is inefficient for data retrieval. The situation will become more crucial while dealing with 3D data. The size of 3D data is usually large due to its detail geometry and other attached information. In this research, a clustered 3D hierarchical structure is introduced as a 3D spatial access method structure. The structure is expected to improve the retrieval of Nearest Neighbour information for 3D objects. Several tests are performed in answering Single Nearest Neighbour search and k Nearest Neighbour (kNN search. The tests indicate that clustered hierarchical structure is efficient in handling Nearest Neighbour query compared to its competitor. From the results, clustered hierarchical structure reduced the repetitive data entry and the accessed page. The proposed structure also produced minimal Input/Output operation. The query response time is also outperformed compared to the other competitor. For future outlook of this research several possible applications are discussed and summarized.

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Science.gov (United States)

Davis, Bruce; Ryan, Robert; Holekamp, Kara; Vaughn, Ronald

2011-01-01

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data

The Bayesian group lasso for confounded spatial data

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

Science.gov (United States)

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

From spectral holeburning memory to spatial-spectral microwave signal processing

International Nuclear Information System (INIS)

Babbitt, Wm Randall; Barber, Zeb W; Harrington, Calvin; Mohan, R Krishna; Sharpe, Tia; Bekker, Scott H; Chase, Michael D; Merkel, Kristian D; Stiffler, Colton R; Traxinger, Aaron S; Woidtke, Alex J

2014-01-01

Many storage and processing systems based on spectral holeburning have been proposed that access the broad bandwidth and high dynamic range of spatial-spectral materials, but only recently have practical systems been developed that exceed the performance and functional capabilities of electronic devices. This paper reviews the history of the proposed applications of spectral holeburning and spatial-spectral materials, from frequency domain optical memory to microwave photonic signal processing systems. The recent results of a 20 GHz bandwidth high performance spectrum monitoring system with the additional capability of broadband direction finding demonstrates the potential for spatial-spectral systems to be the practical choice for solving demanding signal processing problems in the near future. (paper)

A Versatile and Efficient GPU Data Structure for Spatial Indexing

KAUST Repository

Schneider, Jens

2016-08-10

In this paper we present a novel GPU-based data structure for spatial indexing. Based on Fenwick trees—a special type of binary indexed trees—our data structure allows construction in linear time. Updates and prefixes can be computed in logarithmic time, whereas point queries require only constant time on average. Unlike competing data structures such as summed-area tables and spatial hashing, our data structure requires a constant amount of bits for each data element, and it offers unconstrained point queries. This property makes our data structure ideally suited for applications requiring unconstrained indexing of large data, such as block-storage of large and block-sparse volumes. Finally, we provide asymptotic bounds on both run-time and memory requirements, and we show applications for which our new data structure is useful.

A Versatile and Efficient GPU Data Structure for Spatial Indexing

KAUST Repository

Schneider, Jens; Rautek, Peter

2016-01-01

In this paper we present a novel GPU-based data structure for spatial indexing. Based on Fenwick trees—a special type of binary indexed trees—our data structure allows construction in linear time. Updates and prefixes can be computed in logarithmic time, whereas point queries require only constant time on average. Unlike competing data structures such as summed-area tables and spatial hashing, our data structure requires a constant amount of bits for each data element, and it offers unconstrained point queries. This property makes our data structure ideally suited for applications requiring unconstrained indexing of large data, such as block-storage of large and block-sparse volumes. Finally, we provide asymptotic bounds on both run-time and memory requirements, and we show applications for which our new data structure is useful.

Radiochromic film measurement of spatial uniformity for a laser generated x-ray environment

Energy Technology Data Exchange (ETDEWEB)

Fisher, J. H.; Newlander, C. D.; Horton, R.; Fournier, K. B.; Emig, J.; Patterson, R.; Davis, J. F.; Seiler, S.; Jenkins, P. P.

2012-10-01

n existing x-ray source application (XRSA) test cassette was modified to hold multiple x-ray filter materials followed by two radiochromic film types (FWT-60 and HD-810 Gafchromic® film) to qualitatively characterize the spectral-spatial uniformity over the XRSA sample field of view. Multiple sets of film were examined and nominal set was determined. These initial, qualitative measurements suggest a low-energy regime (E < 3 keV) spatial anisotropy and spatial isotropy at higher energies (E > 3 keV).

Linear chirped slope profile for spatial calibration in slope measuring deflectometry

Energy Technology Data Exchange (ETDEWEB)

Siewert, F., E-mail: frank.siewert@helmholtz-berlin.de; Zeschke, T. [Helmholtz Zentrum Berlin für Materialien und Energie, Institut für Nanometer Optik und Technologie, Albert-Einstein-Str. 15, 12489 Berlin (Germany); Arnold, T.; Paetzelt, H. [Leibnitz Institut für Oberflächen Modifizierung Leipzig e.V., IOM, Permoserstr. 15, 04318 Leipzig (Germany); Yashchuk, V. V. [Lawerence Berkeley National Laboratory, Advanced Light Source, 1 Cyclotron Road, Berkeley, California 94720 (United States)

2016-05-15

Slope measuring deflectometry is commonly used by the X-ray optics community to measure the long-spatial-wavelength surface figure error of optical components dedicated to guide and focus X-rays under grazing incidence condition at synchrotron and free electron laser beamlines. The best performing instruments of this kind are capable of absolute accuracy on the level of 30-50 nrad. However, the exact bandwidth of the measurements, determined at the higher spatial frequencies by the instrument’s spatial resolution, or more generally by the instrument’s modulation transfer function (MTF) is hard to determine. An MTF calibration method based on application of a test surface with a one-dimensional (1D) chirped height profile of constant amplitude was suggested in the past. In this work, we propose a new approach to designing the test surfaces with a 2D-chirped topography, specially optimized for MTF characterization of slope measuring instruments. The design of the developed MTF test samples based on the proposed linear chirped slope profiles (LCSPs) is free of the major drawback of the 1D chirped height profiles, where in the slope domain, the amplitude strongly increases with the local spatial frequency of the profile. We provide the details of fabrication of the LCSP samples. The results of first application of the developed test samples to measure the spatial resolution of the BESSY-NOM at different experimental arrangements are also presented and discussed.

On-site phytoremediation applicability assessment in Alur Ilmu, Universiti Kebangsaan Malaysia based on spatial and pollution removal analyses.

Science.gov (United States)

Mahmud, Mohd Hafiyyan; Lee, Khai Ern; Goh, Thian Lai

2017-10-01

The present paper aims to assess the phytoremediation performance based on pollution removal efficiency of the highly polluted region of Alur Ilmu urban river for its applicability of on-site treatment. Thirteen stations along Alur Ilmu were selected to produce thematic maps through spatial distribution analysis based on six water quality parameters of Malaysia's Water Quality Index (WQI) for dry and raining seasons. The maps generated were used to identify the highly polluted region for phytoremediation applicability assessment. Four free-floating plants were tested in treating water samples from the highly polluted region under three different conditions, namely controlled, aerated and normal treatments. The selected free-floating plants were water hyacinth (Eichhornia crassipes), water lettuce (Pistia stratiotes), rose water lettuce (Pistia sp.) and pennywort (Centella asiatica). The results showed that Alur Ilmu was more polluted during dry season compared to raining season based on the water quality analysis. During dry season, four parameters were marked as polluted along Alur Ilmu, namely dissolve oxygen (DO), 4.72 mg/L (class III); ammoniacal nitrogen (NH 3 -N), 0.85 mg/L (class IV); total suspended solid (TSS), 402 mg/L (class V) and biological oxygen demand (BOD), 3.89 mg/L (class III), whereas, two parameters were classed as polluted during raining season, namely total suspended solid (TSS), 571 mg/L (class V) and biological oxygen demand (BOD), 4.01 mg/L (class III). The thematic maps generated from spatial distribution analysis using Kriging gridding method showed that the highly polluted region was recorded at station AL 5. Hence, water samples were taken from this station for pollution removal analysis. All the free-floating plants were able to reduce TSS and COD in less than 14 days. However, water hyacinth showed the least detrimental effect from the phytoremediation process compared to other free-floating plants, thus made it a suitable

Spatial data integration for mineral exploration, resource assessment and environmental studies: A guidebook

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-12-01

The International Atomic Energy Agency has played a significant role over the years in the improvement and use of uranium exploration techniques and data obtained through uranium exploration. Numerous documents on uranium geology and exploration methods have been published. The purpose of this document is to provide an introduction to the new tools and applications of computer based spatial data integration as used by geologists. In order to provide the experts involved in uranium exploration with information on recent developments in computer applications for spatial data integration and image processing, the IAEA convened consultants meetings in November 1991 and November 1992 to produce this guidebook, which contains information on spatially distributed data, data capture, database creation and visualization of data. Vector, and in particular, raster data types and the aspects of integration modelling are discussed. Refs, figs, tabs, 16 plates.

Spatial data integration for mineral exploration, resource assessment and environmental studies: A guidebook

International Nuclear Information System (INIS)

1994-12-01

The International Atomic Energy Agency has played a significant role over the years in the improvement and use of uranium exploration techniques and data obtained through uranium exploration. Numerous documents on uranium geology and exploration methods have been published. The purpose of this document is to provide an introduction to the new tools and applications of computer based spatial data integration as used by geologists. In order to provide the experts involved in uranium exploration with information on recent developments in computer applications for spatial data integration and image processing, the IAEA convened consultants meetings in November 1991 and November 1992 to produce this guidebook, which contains information on spatially distributed data, data capture, database creation and visualization of data. Vector, and in particular, raster data types and the aspects of integration modelling are discussed. Refs, figs, tabs, 16 plates

Spatial Indexing for Data Searching in Mobile Sensing Environments

Directory of Open Access Journals (Sweden)

Yuchao Zhou

2017-06-01

Full Text Available Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.

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.

A vestibular sensation: probabilistic approaches to spatial perception.

Science.gov (United States)

Angelaki, Dora E; Klier, Eliana M; Snyder, Lawrence H

2009-11-25

The vestibular system helps maintain equilibrium and clear vision through reflexes, but it also contributes to spatial perception. In recent years, research in the vestibular field has expanded to higher-level processing involving the cortex. Vestibular contributions to spatial cognition have been difficult to study because the circuits involved are inherently multisensory. Computational methods and the application of Bayes theorem are used to form hypotheses about how information from different sensory modalities is combined together with expectations based on past experience in order to obtain optimal estimates of cognitive variables like current spatial orientation. To test these hypotheses, neuronal populations are being recorded during active tasks in which subjects make decisions based on vestibular and visual or somatosensory information. This review highlights what is currently known about the role of vestibular information in these processes, the computations necessary to obtain the appropriate signals, and the benefits that have emerged thus far.

Clustering Module in OLAP for Horticultural Crops using SpagoBI

Science.gov (United States)

Putri, D.; Sitanggang, I. S.

2017-03-01

Horticultural crops data are organized by the Ministry of Agriculture, Republic of Indonesia. The data are presented annually in a tabular form and result a large data set. This situation makes users difficult to obtain summaries of horticultural crops data. This study aims to develop a clustering module in the SOLAP system for the distribution of horticultural crops in Indonesia and to visualize the results of clustering in a map using SpagoBI. The algorithm used for clustering is K-Means. Horticultural crops data include vegetables, ornamental plants, medicinal plants, and fruits from 2000 to 2013. The clustering module displays clustering results of horticultural crops in the form of text and table on SpagoBI. This module can also visualize the distribution of horticultural crops in the form of map on the HTML page. The application is expected to be useful for users in order to easily obtain summaries of the horticultural crops distribution data and its clusters. The summaries and clusters can be beneficial for the stakeholders to determine potential areas in Indonesia for horticultural crops.

Spatial features register: toward standardization of spatial features

Science.gov (United States)

Cascio, Janette

1994-01-01

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 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.

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.

Agent-based Algorithm for Spatial Distribution of Objects

KAUST Repository

Collier, Nathan

2012-06-02

In this paper we present an agent-based algorithm for the spatial distribution of objects. The algorithm is a generalization of the bubble mesh algorithm, initially created for the point insertion stage of the meshing process of the finite element method. The bubble mesh algorithm treats objects in space as bubbles, which repel and attract each other. The dynamics of each bubble are approximated by solving a series of ordinary differential equations. We present numerical results for a meshing application as well as a graph visualization application.

Applying Spatial-Temporal Model and Game Theory to Asymmetric Threat Prediction

National Research Council Canada - National Science Library

Wei, Mo; Chen, Genshe; Cruz, Jr., Jose B; Haynes, Leonard; Kruger, Martin

2007-01-01

.... In most Command and Control "C2" applications, the existing techniques, such as spatial-temporal point models for ECOA prediction or Discrete Choice Model "DCM", assume that insurgent attack features...

Differentiating Spatial Memory from Spatial Transformations

Science.gov (United States)

Street, Whitney N.; Wang, Ranxiao Frances

2014-01-01

The perspective-taking task is one of the most common paradigms used to study the nature of spatial memory, and better performance for certain orientations is generally interpreted as evidence of spatial representations using these reference directions. However, performance advantages can also result from the relative ease in certain…

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition.

Science.gov (United States)

Gudde, Harmen B; Griffiths, Debra; Coventry, Kenny R

2018-02-19

The memory game paradigm is a behavioral procedure to explore the relationship between language, spatial memory, and object knowledge. Using two different versions of the paradigm, spatial language use and memory for object location are tested under different, experimentally manipulated conditions. This allows us to tease apart proposed models explaining the influence of object knowledge on spatial language (e.g., spatial demonstratives), and spatial memory, as well as understanding the parameters that affect demonstrative choice and spatial memory more broadly. Key to the development of the method was the need to collect data on language use (e.g., spatial demonstratives: "this/that") and spatial memory data under strictly controlled conditions, while retaining a degree of ecological validity. The language version (section 3.1) of the memory game tests how conditions affect language use. Participants refer verbally to objects placed at different locations (e.g., using spatial demonstratives: "this/that red circle"). Different parameters can be experimentally manipulated: the distance from the participant, the position of a conspecific, and for example whether the participant owns, knows, or sees the object while referring to it. The same parameters can be manipulated in the memory version of the memory game (section 3.2). This version tests the effects of the different conditions on object-location memory. Following object placement, participants get 10 seconds to memorize the object's location. After the object and location cues are removed, participants verbally direct the experimenter to move a stick to indicate where the object was. The difference between the memorized and the actual location shows the direction and strength of the memory error, allowing comparisons between the influences of the respective parameters.

Design and study of a coplanar grid array CdZnTe detector for improved spatial resolution

International Nuclear Information System (INIS)

Ma, Yuedong; Xiao, Shali; Yang, Guoqiang; Zhang, Liuqiang

2014-01-01

Coplanar grid (CPG) CdZnTe detectors have been used as gamma-ray spectrometers for years. Comparing with pixelated CdZnTe detectors, CPG CdZnTe detectors have either no or poor spatial resolution, which directly limits its use in imaging applications. To address the issue, a 2×2 CPG array CdZnTe detector with dimensions of 7×7×5 mm 3 was fabricated. Each of the CPG pairs in the detector was moderately shrunk in size and precisely designed to improve the spatial resolution while maintaining good energy resolution, considering the charge loss at the surface between the strips of each CPG pairs. Preliminary measurements were demonstrated at an energy resolution of 2.7–3.9% for the four CPG pairs using 662 keV gamma rays and with a spatial resolution of 3.3 mm, which is the best spatial resolution ever achieved for CPG CdZnTe detectors. The results reveal that the CPG CdZnTe detector can also be applied to imaging applications at a substantially higher spatial resolution. - Highlights: • A novel structure of coplanar grid CdZnTe detector was designed to evaluate the possibility of applying the detector to gamma-ray imaging applications. • The best spatial resolution of coplanar grid CdZnTe detectors ever reported has been achieved, along with good spectroscopic performance. • Depth correction of the energy spectra using a new algorithm is presented

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…

Adaptive proxy map server for efficient vector spatial data rendering

Science.gov (United States)

Sayar, Ahmet

2013-01-01

The rapid transmission of vector map data over the Internet is becoming a bottleneck of spatial data delivery and visualization in web-based environment because of increasing data amount and limited network bandwidth. In order to improve both the transmission and rendering performances of vector spatial data over the Internet, we propose a proxy map server enabling parallel vector data fetching as well as caching to improve the performance of web-based map servers in a dynamic environment. Proxy map server is placed seamlessly anywhere between the client and the final services, intercepting users' requests. It employs an efficient parallelization technique based on spatial proximity and data density in case distributed replica exists for the same spatial data. The effectiveness of the proposed technique is proved at the end of the article by the application of creating map images enriched with earthquake seismic data records.

Spatial manipulation with microfluidics

Directory of Open Access Journals (Sweden)

Benjamin eLin

2015-04-01

Full Text Available Biochemical gradients convey information through space, time, and concentration, and are ultimately capable of spatially resolving distinct cellular phenotypes, such as differentiation, proliferation, and migration. How these gradients develop, evolve, and function during development, homeostasis, and various disease states is a subject of intense interest across a variety of disciplines. Microfluidic technologies have become essential tools for investigating gradient sensing in vitro due to their ability to precisely manipulate fluids on demand in well controlled environments at cellular length scales. This minireview will highlight their utility for studying gradient sensing along with relevant applications to biology.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Application of spatial methods to identify areas with lime requirement in eastern Croatia

Science.gov (United States)

Bogunović, Igor; Kisic, Ivica; Mesic, Milan; Zgorelec, Zeljka; Percin, Aleksandra; Pereira, Paulo

2016-04-01

With more than 50% of acid soils in all agricultural land in Croatia, soil acidity is recognized as a big problem. Low soil pH leads to a series of negative phenomena in plant production and therefore as a compulsory measure for reclamation of acid soils is liming, recommended on the base of soil analysis. The need for liming is often erroneously determined only on the basis of the soil pH, because the determination of cation exchange capacity, the hydrolytic acidity and base saturation is a major cost to producers. Therefore, in Croatia, as well as some other countries, the amount of liming material needed to ameliorate acid soils is calculated by considering their hydrolytic acidity. For this research, several interpolation methods were tested to identify the best spatial predictor of hidrolitic acidity. The purpose of this study was to: test several interpolation methods to identify the best spatial predictor of hidrolitic acidity; and to determine the possibility of using multivariate geostatistics in order to reduce the number of needed samples for determination the hydrolytic acidity, all with an aim that the accuracy of the spatial distribution of liming requirement is not significantly reduced. Soil pH (in KCl) and hydrolytic acidity (Y1) is determined in the 1004 samples (from 0-30 cm) randomized collected in agricultural fields near Orahovica in eastern Croatia. This study tested 14 univariate interpolation models (part of ArcGIS software package) in order to provide most accurate spatial map of hydrolytic acidity on a base of: all samples (Y1 100%), and the datasets with 15% (Y1 85%), 30% (Y1 70%) and 50% fewer samples (Y1 50%). Parallel to univariate interpolation methods, the precision of the spatial distribution of the Y1 was tested by the co-kriging method with exchangeable acidity (pH in KCl) as a covariate. The soils at studied area had an average pH (KCl) 4,81, while the average Y1 10,52 cmol+ kg-1. These data suggest that liming is necessary

One-dimension-based spatially ordered architectures for solar energy conversion.

Science.gov (United States)

Liu, Siqi; Tang, Zi-Rong; Sun, Yugang; Colmenares, Juan Carlos; Xu, Yi-Jun

2015-08-07

The severe consequences of fossil fuel consumption have resulted in a need for alternative sustainable sources of energy. Conversion and storage of solar energy via a renewable method, such as photocatalysis, holds great promise as such an alternative. One-dimensional (1D) nanostructures have gained attention in solar energy conversion because they have a long axis to absorb incident sunlight yet a short radial distance for separation of photogenerated charge carriers. In particular, well-ordered spatially high dimensional architectures based on 1D nanostructures with well-defined facets or anisotropic shapes offer an exciting opportunity for bridging the gap between 1D nanostructures and the micro and macro world, providing a platform for integration of nanostructures on a larger and more manageable scale into high-performance solar energy conversion applications. In this review, we focus on the progress of photocatalytic solar energy conversion over controlled one-dimension-based spatially ordered architecture hybrids. Assembly and classification of these novel architectures are summarized, and we discuss the opportunity and future direction of integration of 1D materials into high-dimensional, spatially organized architectures, with a perspective toward improved collective performance in various artificial photoredox applications.

Spatial evolution equation of wind wave growth

Institute of Scientific and Technical Information of China (English)

WANG; Wei; (王; 伟); SUN; Fu; (孙; 孚); DAI; Dejun; (戴德君)

2003-01-01

Based on the dynamic essence of air-sea interactions, a feedback type of spatial evolution equation is suggested to match reasonably the growing process of wind waves. This simple equation involving the dominant factors of wind wave growth is able to explain the transfer of energy from high to low frequencies without introducing the concept of nonlinear wave-wave interactions, and the results agree well with observations. The rate of wave height growth derived in this dissertation is applicable to both laboratory and open sea, which solidifies the physical basis of using laboratory experiments to investigate the generation of wind waves. Thus the proposed spatial evolution equation provides a new approach for the research on dynamic mechanism of air-sea interactions and wind wave prediction.

Early non-destructive biofouling detection and spatial distribution: Application of oxygen sensing optodes

KAUST Repository

Farhat, Nadia; Staal, Marc; Siddiqui, Amber; Borisov, S.M.; Bucs, Szilard; Vrouwenvelder, Johannes S.

2015-01-01

The spatial and quantitative information on biological activity will lead to better understanding of the biofouling processes, contributing to the development of more effective biofouling control strategies.

A Services-Oriented Architecture for Water Observations Data

Science.gov (United States)

Maidment, D. R.; Zaslavsky, I.; Valentine, D.; Tarboton, D. G.; Whitenack, T.; Whiteaker, T.; Hooper, R.; Kirschtel, D.

2009-04-01

becomes critical. The CUAHSI HIS solution to the scalability and heterogeneity challenges has several components. Structural differences across the data repositories are addressed by building a standard services foundation for the exchange of hydrologic data, as derived from a common information model for observational data measured at stationary points and its implementation as a relational schema (ODM) and an XML schema (WaterML). Semantic heterogeneity is managed by mapping water quantity, water quality, and other parameters collected by government agencies and academic projects to a common ontology. The WaterML-compliant web services are indexed in a community services registry called HIS Central (hiscentral.cuahsi.org). Once a web service is registered in HIS Central, its metadata (site and variable characteristics, period of record for each variable at each site, etc.) is harvested and appended to the central catalog. The catalog is further updated as the service publisher associates the variables in the published service with ontology concepts. After this, the newly published service becomes available for spatial and semantics-based queries from online and desktop client applications developed by the project. Hydrologic system server software is now deployed at more than a dozen locations in the United States and Australia. To provide rapid access to data summaries, in particular for several nation-wide data repositories including EPA STORET, USGS NWIS, and USDA SNOTEL, we convert the observation data catalogs and databases with harvested data values into special representations that support high-performance analysis and visualization. The construction of OLAP (Online Analytical Processing) cubes, often called data cubes, is an approach to organizing and querying large multi-dimensional data collections. We have applied the OLAP techniques, as implemented in Microsoft SQL Server 2005/2008, to the analysis of the catalogs from several agencies. OLAP analysis results

Spatial capture–recapture with partial identity: An application to camera traps

Science.gov (United States)

Augustine, Ben C.; Royle, J. Andrew; Kelly, Marcella J.; Satter, Christopher B.; Alonso, Robert S.; Boydston, Erin E.; Crooks, Kevin R.

2018-01-01

Camera trapping surveys frequently capture individuals whose identity is only known from a single flank. The most widely used methods for incorporating these partial identity individuals into density analyses discard some of the partial identity capture histories, reducing precision, and, while not previously recognized, introducing bias. Here, we present the spatial partial identity model (SPIM), which uses the spatial location where partial identity samples are captured to probabilistically resolve their complete identities, allowing all partial identity samples to be used in the analysis. We show that the SPIM outperforms other analytical alternatives. We then apply the SPIM to an ocelot data set collected on a trapping array with double-camera stations and a bobcat data set collected on a trapping array with single-camera stations. The SPIM improves inference in both cases and, in the ocelot example, individual sex is determined from photographs used to further resolve partial identities—one of which is resolved to near certainty. The SPIM opens the door for the investigation of trapping designs that deviate from the standard two camera design, the combination of other data types between which identities cannot be deterministically linked, and can be extended to the problem of partial genotypes.

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.

Information integration for a sky survey by data warehousing

Science.gov (United States)

Luo, A.; Zhang, Y.; Zhao, Y.

The virtualization service of data system for a sky survey LAMOST is very important for astronomers The service needs to integrate information from data collections catalogs and references and support simple federation of a set of distributed files and associated metadata Data warehousing has been in existence for several years and demonstrated superiority over traditional relational database management systems by providing novel indexing schemes that supported efficient on-line analytical processing OLAP of large databases Now relational database systems such as Oracle etc support the warehouse capability which including extensions to the SQL language to support OLAP operations and a number of metadata management tools have been created The information integration of LAMOST by applying data warehousing is to effectively provide data and knowledge on-line

Pre-Aggregation with Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

2006-01-01

Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributions rather than atomic values. The paper describes how to create probability distributions from base data, and how...... the distributions can be subsequently used in pre-aggregation. Since the probability distributions can become large, we show how to achieve good time and space efficiency by approximating the distributions. We present the results of several experiments that demonstrate the effectiveness of our methods. The work...... is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services. This paper is the first to consider the approximate processing of probabilistic OLAP queries over probability distributions....

Hydrological application of the INCA model with varying spatial resolution and nitrogen dynamics in a northern river basin

Directory of Open Access Journals (Sweden)

K. Rankinen

2002-01-01

Full Text Available As a first step in applying the Integrated Nitrogen model for CAtchments (INCA to the Simojoki river basin (3160 km2, this paper focuses on calibration of the hydrological part of the model and nitrogen (N dynamics in the river during the 1980s and 1990s. The model application utilised the GIS land-use and forest classification of Finland together with a recent forest inventory based on remote sensing. In the INCA model, the Hydrologically Effective Rainfall (HER is used to drive the water flow and N fluxes through the catchment system. HER was derived from the Watershed Simulation and Forecast System (WSFS. The basic component of the WSFS is a conceptual hydrological model which simulates runoff using precipitation, potential evapotranspiration and temperature data as inputs. Spatially uniform, lumped input data were calculated for the whole river basin and spatially semi-distributed input data were calculated for each of the nine sub-basins. When comparing discharges simulated by the INCA model with observed values, a better fit was obtained with the semi-distributed data than with the spatially uniform data (R2 0.78 v. 0.70 at Hosionkoski and 0.88 v. 0.78 at the river outlet. The timing of flow peaks was simulated rather well with both approaches, although the semi-distributed input data gave a more realistic simulation of low flow periods and the magnitude of spring flow peaks. The river basin has a relatively closed N cycle with low input and output fluxes of inorganic N. During 1982-2000, the average total N flux to the sea was 715 tonnes yr–1, of which 6% was NH4-N, 14% NO3-N, and 80% organic N. Annual variation in river flow and the concentrations of major N fractions in river water, and factors affecting this variation are discussed. Keywords: northern river basin, nitrogen, forest management, hydrology, dynamic modelling, semi-distributed modelling

The impact of I(C)T in spatial planning education, 25 years of blended e-learning

OpenAIRE

Knaap, van der, W.G.M.

2014-01-01

The Wageningen spatial planning education curriculum is based on a mix of decision-oriented and design-oriented approaches. It is also intertwined with a wide range of E-learning options. The Elearning environment consists of a spectrum of applications such as model studies, spatial analysis using GIS, scenario studies, imaging results or support in the educational and the planning process. At the end of the 1980’s already divers applications were intertwined in the training of planning stude...

Data mining methods

CERN Document Server

Chattamvelli, Rajan

2015-01-01

DATA MINING METHODS, Second Edition discusses both theoretical foundation and practical applications of datamining in a web field including banking, e-commerce, medicine, engineering and management. This book starts byintroducing data and information, basic data type, data category and applications of data mining. The second chapterbriefly reviews data visualization technology and importance in data mining. Fundamentals of probability and statisticsare discussed in chapter 3, and novel algorithm for sample covariants are derived. The next two chapters give an indepthand useful discussion of data warehousing and OLAP. Decision trees are clearly explained and a new tabularmethod for decision tree building is discussed. The chapter on association rules discusses popular algorithms andcompares various algorithms in summary table form. An interesting application of genetic algorithm is introduced inthe next chapter. Foundations of neural networks are built from scratch and the back propagation algorithm is derived...

Spatial capture-recapture: a promising method for analyzing data collected using artificial cover objects

Science.gov (United States)

Sutherland, Chris; Munoz, David; Miller, David A.W.; Grant, Evan H. Campbell

2016-01-01

Spatial capture–recapture (SCR) is a relatively recent development in ecological statistics that provides a spatial context for estimating abundance and space use patterns, and improves inference about absolute population density. SCR has been applied to individual encounter data collected noninvasively using methods such as camera traps, hair snares, and scat surveys. Despite the widespread use of capture-based surveys to monitor amphibians and reptiles, there are few applications of SCR in the herpetological literature. We demonstrate the utility of the application of SCR for studies of reptiles and amphibians by analyzing capture–recapture data from Red-Backed Salamanders, Plethodon cinereus, collected using artificial cover boards. Using SCR to analyze spatial encounter histories of marked individuals, we found evidence that density differed little among four sites within the same forest (on average, 1.59 salamanders/m2) and that salamander detection probability peaked in early October (Julian day 278) reflecting expected surface activity patterns of the species. The spatial scale of detectability, a measure of space use, indicates that the home range size for this population of Red-Backed Salamanders in autumn was 16.89 m2. Surveying reptiles and amphibians using artificial cover boards regularly generates spatial encounter history data of known individuals, which can readily be analyzed using SCR methods, providing estimates of absolute density and inference about the spatial scale of habitat use.

Photography activities for developing students’ spatial orientation and spatial visualization

Science.gov (United States)

Hendroanto, Aan; van Galen, Frans; van Eerde, D.; Prahmana, R. C. I.; Setyawan, F.; Istiandaru, A.

2017-12-01

Spatial orientation and spatial visualization are the foundation of students’ spatial ability. They assist students’ performance in learning mathematics, especially geometry. Considering its importance, the present study aims to design activities to help young learners developing their spatial orientation and spatial visualization ability. Photography activity was chosen as the context of the activity to guide and support the students. This is a design research study consisting of three phases: 1) preparation and designing 2) teaching experiment, and 3) retrospective analysis. The data is collected by tests and interview and qualitatively analyzed. We developed two photography activities to be tested. In the teaching experiments, 30 students of SD Laboratorium UNESA, Surabaya were involved. The results showed that the activities supported the development of students’ spatial orientation and spatial visualization indicated by students’ learning progresses, answers, and strategies when they solved the problems in the activities.

Spatial Programming for Industrial Robots through Task Demonstration

Directory of Open Access Journals (Sweden)

Jens Lambrecht

2013-05-01

Full Text Available Abstract We present an intuitive system for the programming of industrial robots using markerless gesture recognition and mobile augmented reality in terms of programming by demonstration. The approach covers gesture-based task definition and adaption by human demonstration, as well as task evaluation through augmented reality. A 3D motion tracking system and a handheld device establish the basis for the presented spatial programming system. In this publication, we present a prototype toward the programming of an assembly sequence consisting of several pick-and-place tasks. A scene reconstruction provides pose estimation of known objects with the help of the 2D camera of the handheld. Therefore, the programmer is able to define the program through natural bare-hand manipulation of these objects with the help of direct visual feedback in the augmented reality application. The program can be adapted by gestures and transmitted subsequently to an arbitrary industrial robot controller using a unified interface. Finally, we discuss an application of the presented spatial programming approach toward robot-based welding tasks.

Precise Mapping Of A Spatially Distributed Radioactive Source

International Nuclear Information System (INIS)

Beck, A.; Caras, I.; Piestum, S.; Sheli, E.; Melamud, Y.; Berant, S.; Kadmon, Y.; Tirosh, D.

1999-01-01

Spatial distribution measurement of radioactive sources is a routine task in the nuclear industry. The precision of each measurement depends upon the specific application. However, the technological edge of this precision is motivated by the production of standards for calibration. Within this definition, the most demanding field is the calibration of standards for medical equipment. In this paper, a semi-empirical method for controlling the measurement precision is demonstrated, using a relatively simple laboratory apparatus. The spatial distribution of the source radioactivity is measured as part of the quality assurance tests, during the production of flood sources. These sources are further used in calibration of medical gamma cameras. A typical flood source is a 40 x 60 cm 2 plate with an activity of 10 mCi (or more) of 57 Co isotope. The measurement set-up is based on a single NaI(Tl) scintillator with a photomultiplier tube, moving on an X Y table which scans the flood source. In this application the source is required to have a uniform activity distribution over its surface

Empirical Research on Spatial Diffusion Process of Knowledge Spillovers

Science.gov (United States)

Jin, Xuehui

2018-02-01

Firstly, this paper gave a brief review of the core issues of previous studies on spatial distribution of knowledge spillovers. That laid the theoretical foundation for further research. Secondly, this paper roughly described the diffusion process of solar patents in Bejing-Tianjin-Hebei and the Pearl River Delta regions by means of correlation analysis based on patent information of the application date and address of patentee. After that, this paper introduced the variables of spatial distance, knowledge absorptive capacity, knowledge gap and pollution control and built the empirical model of patent, and then collecting data to test them. The results showed that knowledge absorptive capacity was the most significant factor than the other three, followed by the knowledge gap. The influence of spatial distance on knowledge spillovers was limited and the most weak influence factor was pollution control.

Spatial memory and hippocampal function: Where are we now?

Directory of Open Access Journals (Sweden)

Mark Good