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Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application  

PubMed Central

Background Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Results Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at integrating an initial collection of geo-referenced multi-scale indicators that were identified by Canadian specialists and end-users as relevant for the surveillance of the public health impacts of climate change. This system was developed in a multidisciplinary context involving researchers, policy makers and practitioners, using BI and web-mapping concepts (more particularly SOLAP technologies), while exploring new solutions for frequent automatic updating of data and for providing contextual warnings for users (to minimize the risk of data misinterpretation). According to the project participants, the final system succeeds in facilitating surveillance activities in a way not achievable with today's GIS. Regarding the experiments on frequent automatic updating and contextual user warnings, the results obtained indicate that these are meaningful and achievable goals but they still require research and development for their successful implementation in the context of surveillance and multiple organizations. Conclusion Surveillance of climate-related health vulnerabilities may be more efficiently supported using a combination of BI and GIS concepts, and more specifically, SOLAP technologies (in that it facilitates and accelerates multi-scale spatial and temporal analysis to a point where a user can maintain an uninterrupted train of thought by focussing on "what" she/he wants (not on "how" to get it) and always obtain instant answers, including to the most complex queries that take minutes or hours with OLTP systems (e.g., aggregated, temporal, comparative)). The developed system respects Newell's cognitive band of 10 seconds when performing knowledge discovery (exploring data, looking for hypotheses, validating models). The developed system provides new operators for easily and rapidly exploring multidimensional data at different levels of granularity, for different regions and epochs, and for visualizing the results in synchronized maps, tables and charts. It is naturally adapted to deal with multiscale indicators such as those used in the surveillance community, as confirmed by thi

Bernier, Eveline; Gosselin, Pierre; Badard, Thierry; Bedard, Yvan



Index Selection for OLAP  

Microsoft Academic Search

On-line analytical processing (OLAP) is a recent and important application of database systems. Typically, OLAP data is presented as a multidimensional “data cube.” OLAP queries are complex and can take many hours or even days to run, if executed directly on the raw data. The most common method of reducing execution time is to precompute some of the queries into

Himanshu Gupta; Venky Harinarayan; Anand Rajaraman; Jeffrey D. Ullman



Extendible Arrays for Statistical Databases and OLAP Applications  

Microsoft Academic Search

Online analytical processing (OLAP) is becoming increasingly important as today's organizations frequently make business decisions based on statistical analysis of their enterprise data. This data is multidimensional and is derived from transactional data using various levels of aggregation. As the business model changes frequently, the multidimensional arrays must be extended in terms of the value ranges of each dimension and

Doron Rotem; J. Leon Zhao



Research and Application on OLAP-based Farm Products Examination Model  

Microsoft Academic Search

Abstract The technology of Data ,Warehouse ,is being ,widely used,in decision ,making ,and ,data ,analysis. Data Warehouse,generalizes ,and ,consolidates multidimensional(MD) data. Hence, Data Warehouse has become,an important ,platform for OLAP which is based ona MD data model. Therefore, dimensional modeling is a key factor in OLAP data analysis. Inthis paper, we address the technology of dimensional modeling based on Data

Minghua Han; Chunhua Ju



Towards OLAP security design — survey and research issues  

Microsoft Academic Search

With the use of data warehousing and online analytical processing (OLAP) for decision support applications new security issues arise. The goal of this paper is to introduce an OLAP security design methodology, pointing out fields that require further re- search work. We present possible access control requirements categorized by their complexity. OLAP security mechanisms and their implementations in commercial systems

Torsten Priebe; Günther Pernul



A Conceptual Modeling Approach for OLAP Personalization  

NASA Astrophysics Data System (ADS)

Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.

Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan


Range queries in dynamic OLAP data cubes  

Microsoft Academic Search

A range query applies an aggregation operation (e.g., SUM) over all selected cells of an OLAP data cube where the selection is specified by providing ranges of values for numeric dimensions. Range sum queries on data cubes are a powerful analysis tool. Many application domains require that data cubes are updated often and the information provided by analysis tools are

Weifa Liang; Hui Wang; Maria E. Orlowska



OLAP Cube Visualization of Hydrologic Data Catalogs  

NASA Astrophysics Data System (ADS)

As part of the CUAHSI Hydrologic Information System project, we assemble comprehensive observations data catalogs that support CUAHSI data discovery services (WaterOneFlow services) and online mapping interfaces (e.g. the Data Access System for Hydrology, DASH). These catalogs describe several nation-wide data repositories that are important for hydrologists, including USGS NWIS and EPA STORET data collections. The catalogs contain a wealth of information reflecting the entire history and geography of hydrologic observations in the US. Managing such catalogs requires high performance analysis and visualization technologies. OLAP (Online Analytical Processing) cube, 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, to the analysis of the catalogs from several agencies. In this initial report, we focus on the OLAP technology as applied to catalogs, and preliminary results of the analysis. Specifically, we describe the challenges of generating OLAP cube dimensions, and defining aggregations and views for data catalogs as opposed to observations data themselves. The initial results are related to hydrologic data availability from the observations data catalogs. The results reflect geography and history of available data totals from USGS NWIS and EPA STORET repositories, and spatial and temporal dynamics of available measurements for several key nutrient-related parameters.

Zaslavsky, I.; Rodriguez, M.; Beran, B.; Valentine, D.; van Ingen, C.; Wallis, J. C.



Improving Expression Power in Modeling OLAP Hierarchies  

NASA Astrophysics Data System (ADS)

Data warehouses and OLAP systems form an integral part of modern decision support systems. In order to exploit both systems to their full capabilities hierarchies must be clearly defined. Hierarchies are important in analytical applications, since they provide users with the possibility to represent data at different abstraction levels. However, even though there are different kinds of hierarchies in real-world applications and some are already implemented in commercial tools, there is still a lack of a well-accepted conceptual model that allows decision-making users express their analysis needs. In this paper, we show how the conceptual multidimensional model can be used to facilitate the representation of complex hierarchies in comparison to their representation in the relational model and commercial OLAP tool, using as an example Microsoft Analysis Services.

Malinowski, Elzbieta


A Formal Framework of Aggregation for the OLAP-OLTP Model  

Microsoft Academic Search

OLAP applications are widely used in business applications. They are of- ten (implicitly) defined on top of OLTP systems and extensively use aggregation and transformation functions. The main OLAP data structure is a multidimensional ta- ble with three kinds of attributes: so-called dimension attributes, implicit attributes given by aggregation functions and fact attributes. Domains of dimension attributes are structured and

Hans-Joachim Lenz; Bernhard Thalheim



Insurance Industry Decision Support: Data Marts, OLAP and Predictive Analytics  

Microsoft Academic Search

Motivation. Data Warehouses and Data Marts increase the power and efficiency of an Insurance company's Business Intelligence capabilities by supporting queries, OLAP and data mining. Web- enabling of these applications makes them more user-friendly. The potential benefits greatly outweigh the costs. Data warehouse\\/data mart implementation streamlines information delivery for decision support and significantly simplifies development of general linear predictive models

George Bukhbinder; Michael Krumenaker; Abraham Phillips


Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes  

Microsoft Academic Search

With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and OLAP of spatial data. In this paper, we study methods for spatial OLAP, by integration of nonspatial OLAP methods with spatial database implementation techniques. A spatial

Nebojsa Stefanovic; Jiawei Han; Krzysztof Koperski



Preference-Based Recommendations for OLAP Analysis  

NASA Astrophysics Data System (ADS)

This paper presents a framework for integrating OLAP and recommendations. We focus on the anticipatory recommendation process that assists the user during his OLAP analysis by proposing to him the forthcoming analysis step. We present a context-aware preference model that matches decision-makers intuition, and we discuss a preference-based approach for generating personalized recommendations.

Jerbi, Houssem; Ravat, Franck; Teste, Olivier; Zurfluh, Gilles


Securing OLAP Data Cubes Against Privacy Breaches  

Microsoft Academic Search

An OLAP (On-line Analytic Processing) system with insufficient security countermeasures may disclose sensitive information and breach an individual's privacy. Both unauthorized accesses and malicious inferences may lead to such inappropriate disclosures. Existing access control models in relational databases are unsuitable for the multi-dimensional data cubes used by OLAP. Inference control methods in statistical databases are expensive and apply to limited

Lingyu Wang; Sushil Jajodia; Duminda Wijesekera



High-Dimensional OLAP: A Minimal Cubing Approach  

Microsoft Academic Search

Data cube has been playing an essential role in fast OLAP (online analytical processing) in many multi-dimensional data warehouses. However, there exist data sets in applications like bioinformatics, statistics, and text pro- cessing that are characterized by high dimen- sionality, e.g., over 100 dimensions, and mod- erate size, e.g., around 106 tuples. No feasible data cube can be constructed with

Xiaolei Li; Jiawei Han; Hector Gonzalez



Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis  

Microsoft Academic Search

BACKGROUND: Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a

Matthew Scotch; Bambang Parmanto; Valerie Monaco



Hierarchical reorganization of dimensions in OLAP visualizations.  


In this paper, we propose a new method for the visual reorganization of online analytical processing (OLAP) cubes that aims at improving their visualization. Our method addresses dimensions with hierarchically organized members. It uses a genetic algorithm that reorganizes k-ary trees. Genetic operators perform permutations of subtrees to optimize a visual homogeneity function. We propose several ways to reorganize an OLAP cube depending on which set of members is selected for the reorganization: all of the members, only the displayed members, or the members at a given level (level by level approach). The results that are evaluated by using optimization criteria show that our algorithm has a reliable performance even when it is limited to 1 minute runs. Our algorithm was integrated in an interactive 3D interface for OLAP. A user study was conducted to evaluate our approach with users. The results highlight the usefulness of reorganization in two OLAP tasks. PMID:24029904

Lafon, Sébastien; Bouali, Fatma; Guinot, Christiane; Venturini, Gilles



Hierarchical Reorganization of Dimensions in OLAP Visualizations.  


In this paper, we propose a new method for the visual reorganization of OLAP cubes that aims at improving their visualization. The proposed algorithm addresses dimensions with hierarchically organized members. It uses a genetic algorithm that reorganizes k-ary trees. Genetic operators perform permutations of subtrees to optimize a visual homogeneity function. We propose several ways to reorganize an OLAP cube depending on which set of members is selected for the reorganization: all of the members, only the displayed members, or the members at a given level (level by level approach). The results that are evaluated by using optimization criteria show that our algorithm has a reliable performance even when it is limited to 1 minute runs. Our algorithm has been integrated in an interactive 3D interface for OLAP. A user study has been conducted to evaluate our approach with users. The results highlight the usefulness of reorganization in two OLAP tasks. PMID:23775480

Lafon, Sebastien; Bouali, Fatma; Guinot, Christiane; Venturini, Gilles



Nested Data Cubes for OLAP (Extended Abstract)  

Microsoft Academic Search

. Nested data cubes (NDCs in short) are a generalization ofother OLAP models such as f-tables [3] and hypercubes [2], but also ofclassical structures as sets, bags, and relations. This model adds to theprevious models flexibility in viewing the data, in that it allows for theassignment of priorities to the different dimensions of the multidimensionalOLAP data.We also present an algebra

Stijn Dekeyser; Bart Kuijpers; Jan Paredaens; Jef Wijsen



CAMS: OLAPing Multidimensional Data Streams Efficiently  

NASA Astrophysics Data System (ADS)

In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.

Cuzzocrea, Alfredo


The building of Customer Relationship Management system based on OLAP  

Microsoft Academic Search

This paper introduces the concepts of OLAP into Customer Relationship Management (CRM) system and puts forward a framework of CRM system based on OLAP, which effectively resolves insufficient heterogeneous compatibility and heavy workload on the server in the traditional CRM system. It elaborates on the working process of CRM system based on OLAP with a specific example. It summarizes the

Gao Guohong; Xu Lijun; Fu Junhui; Qu Peixin



Range queries in OLAP data cubes  

Microsoft Academic Search

A range query applies an aggregation operation over all selected cells of an OLAP data cube where the selection is specified by providing ranges of values for numeric dimensions. We present fast algorithms for range queries for two types of aggregation operations: SUM and MAX. These two operations cover techniques required for most popular aggregation operations, such as those supported

Ching-Tien Ho; Rakesh Agrawal; Nimrod Megiddo; Ramakrishnan Srikant



Connecting traditional sciences with the OLAP and data mining paradigms  

NASA Astrophysics Data System (ADS)

The paradigms of OLAP, multidimensional modeling and data mining have first emerged in the areas of market analysis and finance to address various needs of people working in these areas. Does this mean that they are useful and applicable in these areas only? Or, can they also be applicable in the other more traditional areas of science and engineering? What characterize the systems for which these paradigms are suitable? What are the goals of these paradigms? How do they relate to the traditional body of knowledge that has been developed throughout the centuries in the areas of mathematics, statistics, systems science and engineering? Where, how and to what extent can we leverage the conventional wisdom that has been accumulated in the aforementioned disciplines to develop a foundational basis for the above paradigms? The goal of this paper is to address these questions at the foundational level. We argue that the paradigms of OLAP, multidimensional modeling and data mining can also be applied successfully to complex engineering systems, such as membrane-based water/wastewater treatment plants, for example. We develop mathematically-based axiomatic definition of the concepts of 'dimension,' 'dimension level,' 'dimension hierarchy' and 'measure' using set theory and equivalence relations.

Guergachi, Aziz A.



Security in Data Warehouses and OLAP Systems  

Microsoft Academic Search

Unlike in operational databases, aggregation and derivation play a major role in on-line analytical processing (OLAP) systems\\u000a and data warehouses. Unfortunately, the process of aggregation and derivation can also pose challenging security problems.\\u000a Aggregated and derived data usually look innocent to traditional security mechanisms, such as access control, and yet such\\u000a data may carry enough sensitive information to cause security

Lingyu Wang; Sushil Jajodia


Range Queries in OLAP Data Cubes  

Microsoft Academic Search

A range query applies an aggregation operation over all selectedcells of an OLAP data cube where the selection isspecified by providing ranges of values for numeric dimensions.We present fast algorithms for range queries for twotypes of aggregation operations: SUM and MAX. These twooperations cover techniques required for most popular aggregationoperations, such as those supported by SQL.For range-sum queries, the essential

Ching-Tien Ho; Rakesh Agrawal; Nimrod Megiddo; Ramakrishnan Srikant



Mining Exceptions And Quantitative Association Rules In Olap Data Cube  

Microsoft Academic Search

People nowadays are relying more and more on OLAP data to find business solutions. Atypical OLAP data cube usually contains four to eight dimensions, with two to six hierarchicallevels and tens to hundreds of categories for each dimension. It is often too large andhas too many levels for users to browse it effectively. In this thesis we propose a systemprototype

Qing Chen



Effectiveness of OLAP-Based Sales Analysis in Retail Enterprises  

Microsoft Academic Search

Data warehouse and online analytical processing (OLAP) are two significant information technology (IT) strategies. To commercial enterprises, merchandise sales play important and special role. With the market competition getting fierce, managers see information as a critical resource and require methods that let them exploit it for competitive advantage. The development of data warehouse and OLAP make it possible to use

Chunhua Ju; Minghua Han



InfoNetOLAP: OLAP and Mining of Information Networks  

Microsoft Academic Search

\\u000a Databases and data warehouse systems have been evolving from handling normalized spreadsheets stored in relational databases\\u000a to managing and analyzing diverse application-oriented data with complex interconnecting structures. Responding to this emerging\\u000a trend, information networks have been growing rapidly and showing their critical importance in many applications, such as\\u000a the analysis of XML, social networks, Web, biological data, multimedia data, and

Chen Chen; Feida Zhu; Xifeng Yan; Jiawei Han; Philip Yu; Raghu Ramakrishnan



Efficiently Computing and Querying Multidimensional OLAP Data Cubes over Probabilistic Relational Data  

Microsoft Academic Search

\\u000a Focusing on novel database application scenarios, where datasets arise more and more in uncertain and imprecise formats, in this paper we propose a novel framework for efficiently computing and querying multidimensional OLAP data cubes\\u000a over probabilistic data, which well-capture previous kinds of data. Several models and algorithms supported in our proposed\\u000a framework are formally presented and described in details, based

Alfredo Cuzzocrea; Dimitrios Gunopulos



An efficient communication strategy for mobile agent based distributed spatial data mining application  

NASA Astrophysics Data System (ADS)

An efficient communication strategy is proposed in this paper, which aims to improve the response time and availability of mobile agent based distributed spatial data mining applications. When dealing with decomposed complex data mining tasks or On-Line Analytical Processing (OLAP), mobile agents authorized by the specified user need to coordinate and cooperate with each other by employing given communication method to fulfill the subtasks delegated to them. Agent interactive behavior, e.g. messages passing, intermediate results exchanging and final results merging, must happen after the specified path is determined by executing given routing selection algorithm. Most of algorithms exploited currently run in time that grows approximately quadratic with the size of the input nodes where mobile agents migrate between. In order to gain enhanced communication performance by reducing the execution time of the decision algorithm, we propose an approach to reduce the number of nodes involved in the computation. In practice, hosts in the system are reorganized into groups in terms of the bandwidth between adjacent nodes. Then, we find an optimal node for each group with high bandwidth and powerful computing resources, which is managed by an agent dispatched by agent home node. With that, the communication pattern can be implemented at a higher level of abstraction and contribute to improving the overall performance of mobile agent based distributed spatial data mining applications.

Han, Guodong; Wang, Jiazhen



Discovery-driven exploration of OLAP data cubes  

Microsoft Academic Search

Analysts predominantly use OLAP data cubes to identify regions of anomalies that may represent problem areas or new opportunities.\\u000a The current OLAP systems support hypothesis-driven exploration of data cubes through operations such as drill-down, roll-up,\\u000a and selection. Using these operations, an analyst navigates unaided through a huge search space looking at large number of\\u000a values to spot exceptions. We propose

Sunita Sarawagi; Rakesh Agrawal; Nimrod Megiddo


Discovery-Driven Exploration of OLAP Data Cubes  

Microsoft Academic Search

.Analysts predominantly use OLAP data cubes to identifyregions of anomalies that may represent problem areas or new opportunities.The current OLAP systems support hypothesis-driven explorationof data cubes through operations such as drill-down, roll-up, and selection.Using these operations, an analyst navigates unaided through ahuge search space looking at large number of values to spot exceptions.We propose a new discovery-driven exploration paradigm that

Sunita Sarawagi; Rakesh Agrawal; Nimrod Megiddo



From Analysis to Interactive Exploration: Building Visual Hierarchies from OLAP Cubes  

Microsoft Academic Search

We present a novel framework for comprehensive exploration of OLAP data by means of user-defined dynamic hierarchical visualiza- tions. The multidimensional data model behind the OLAP architecture is particularly suitable for sophisticated analysis of large data volumes. However, the ultimate benefit of applying OLAP technology depends on the \\

Svetlana Vinnik; Florian Mansmann



Ix-cubes: iceberg cubes for data warehousing and olap on xml data  

Microsoft Academic Search

With increasing amount of data being stored in XML for- mat, OLAP queries over these data become important. OLAP queries have been well studied in the relational database sys- tems. However, the evaluation of OLAP queries over XML data is not a trivial extension of the relational solutions, especially when a schema is not available. In this paper, we introduce

Fianny Ming-fei Jiang; Jian Pei; Ada Wai-chee Fu



cgmOLAP: Efficient Parallel Generation and Querying of Terabyte Size ROLAP Data Cubes  

Microsoft Academic Search

In this demo we present the cgmOLAP server, the first fully functional parallel OLAP system able to build data cubes at a rate of more than 1 Ter- abyte per hour. cgmOLAP incorporates a vari- ety of novel approaches for the parallel computa- tion of full cubes, partial cubes, and iceberg cubes as well as new parallel cube indexing schemes.

Ying Chen; Andrew Rau-chaplin; Frank K. H. A. Dehne; Todd Eavis; D. Green; E. Sithirasenan



A Genetic Selection Algorithm for OLAP Data Cubes  

Microsoft Academic Search

Multidimensional data analysis, as supported by OLAP (online analytical processing) systems, requires the computation of many aggregate functions over a large volume of historically collected data. To decrease the query time and to provide various viewpoints for the analysts, these data are usually organized as a multi-dimensional data model, called data cubes. Each cell in a data cube corresponds to

Wen-yang Lin; I-chung Kuo



A Genetic Selection Algorithm for OLAP Data Cubes  

Microsoft Academic Search

Multidimensional data analysis, as supported by OLAP (online analytical processing) systems, requires the computation of many aggregate functions over a large volume of historically collected data. To decrease the query time and to provide various viewpoints for the analysts, these data are usually organized as a multidimensional data model, called data cubes. Each cell in a data cube corresponds to

Wen-Yang Lin; I-Chung Kuo



OLAP: A Fast, Easy, Affordable Executive Information System--Finally!  

ERIC Educational Resources Information Center

The University of Rochester's experience with online analytical processing (OLAP), part of its executive information system, is reported. The server, a multiuser, local area network (LAN)-based database loaded from legacy systems or a data warehouse, can rapidly manipulate and display data, and allows quick creation and changing of analytical…

Stewart, Henry M.



Multidimensional (OLAP) Analysis for Designing Dynamic Learning Strategy  

NASA Astrophysics Data System (ADS)

Learning strategy in an intelligent learning system is generally elaborated on the basis of assessment of the following factors: learner's time for reaction, content of the learning object, amount of learning material in a learning object, learning object specification, e-learning medium and performance control. Current work proposes architecture for dynamic learning strategy design by implementing multidimensional analysis model of learning factors. The analysis model concerns on-line analytical processing (OLAP) of learner's data structured as multidimensional cube. Main components of the architecture are analysis agent for performing the OLAP operations on learner data cube, adaptation generator and knowledge selection agent for performing adaptive navigation in the learning object repository. The output of the analysis agent is involved in dynamic elaboration of learning strategy that fits best to learners profile and behavior. As a result an adaptive learning path for individual learner and for learner groups is generated.

Rozeva, A.; Deliyska, B.



View Discovery in OLAP Databases through Statistical Combinatorial Optimization  

SciTech Connect

The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of ``views'' of an OLAP database as a combinatorial object of all projections and subsets, and ``view discovery'' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline ``hop-chaining'' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a ``spiraling'' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.

Joslyn, Cliff A.; Burke, Edward J.; Critchlow, Terence J.



Range-Max\\/Min Query in OLAP Data Cube  

Microsoft Academic Search

A range query applies an aggregation operation over all selected cells of an OLAP data cube where the selection is specified\\u000a by ranges of continuous values for numeric dimensions. Much work has been done with one type of aggregations: SUM. But little\\u000a work has been done with another type of aggregations: MAX\\/MIN besides the tree-based algorithm. In this paper, we

Hua-gang Li; Tok Wang Ling; Sin Yeung Lee



Overcoming Limitations of Approximate Query Answering in OLAP  

Microsoft Academic Search

Two important limitations of approximate query answering in OLAP are recognized and investigated. These limitations are: (i) scalability of the techniques, i.e. their reliability on highly-dimensional data cubes; and (ii) need for guarantees on the degree of approximation of the answers. In this paper, we focus on the first limitation, and propose adopting the well-known Karhunen-Loeve transform (KLT) to obtain

Alfredo Cuzzocrea



Selective Materialization: An Efficient Method for Spatial Data Cube Construction  

Microsoft Academic Search

. On-line analytical processing (OLAP) has gained its popularityin database industry. With a huge amount of data stored in spatialdatabases and the introduction of spatial components to many relationalor object-relational databases, it is important to study the methods forspatial data warehousing and on-line analytical processing of spatialdata. In this paper, we study methods for spatial OLAP, by integrationof nonspatial on-line

Jiawei Han; Nebojsa Stefanovic; Krzysztof Koperski



A distortion based technique for preserving privacy in OLAP data cube  

Microsoft Academic Search

This paper is about privacy preservation of the data in OLAP data cube. Data cube is a multidimensional view of a database, which helps in analysis of data from different perspectives. Preserving privacy of individual's data while providing aU data available for the analysis is one of the main challenges for OLAP systems. Because legitimate queries on aggregated values lead

Sara Mumtaz; Azhar Rauf; Shah Khusro



Web 2.0 OLAP: From Data Cubes to Tag Clouds  

NASA Astrophysics Data System (ADS)

Increasingly, business projects are ephemeral. New Business Intelligence tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds are a popular community-driven visualization technique. Hence, we investigate tag-cloud views with support for OLAP operations such as roll-ups, slices, dices, clustering, and drill-downs. As a case study, we implemented an application where users can upload data and immediately navigate through its ad hoc dimensions. To support social networking, views can be easily shared and embedded in other Web sites. Algorithmically, our tag-cloud views are approximate range top-k queries over spontaneous data cubes. We present experimental evidence that iceberg cuboids provide adequate online approximations. We benchmark several browser-oblivious tag-cloud layout optimizations.

Aouiche, Kamel; Lemire, Daniel; Godin, Robert


Multiple-Objective Compression of Data Cubes in Cooperative OLAP Environments  

Microsoft Academic Search

Traditional data cube compression techniques do not consider the yet relevant problem of compressing data cubes in the presence\\u000a of multiple objectives rather than only one (e.g., a given space bound). Starting from next-generation OLAP scenarios where\\u000a this problem makes sense, such as those drawn by cooperative OLAP environments, in this paper we fulfill this lack via (i) introducing and

Alfredo Cuzzocrea



Photorefractive Spatial Solitons: Fundamentals and Applications.  

National Technical Information Service (NTIS)

In this program, we have studied, experimentally and theoretically, the fundamental properties of photorefractive spatial solitons and the features of the interactions between and among them. We brought the topic of photorefractive solitons to the very fr...

M. Segev



Applications of a spatial extension to CIELAB  

Microsoft Academic Search

We describe computational experiments to predict the perceived quality of multi-level halftone images. Our computationswere based on a spatial color difference metric, S-CIELAB, that is an extension of CIELAB, a widelyused industry standard. CIELAB predicts the discriminability of large uniform color patches. S-CIELAB includes apre-processing stage that accounts for certain aspects of the spatial sensitivity to different colors. From simulationsapplied

X M Zhang; J. e. Farrell; B. a. Wandell


An Experimental Evaluation of an Alternative to the Pivot Table for Ad Hoc Access to OLAP Data  

Microsoft Academic Search

This paper examines the usability of the orthodox interface to access business intelligence data held in OLAP- based systems - the pivot table. An alternative to the pivot table is described, based on Erik Thomsen's simple diagramming technique for designing OLAP data structures. That interface is compared to the pivot table in a laboratory-based experiment. The results show that the

Peter O'Donnell; Nick Draper



The M-OLAP Cube Selection Problem: A Hyper-polymorphic Algorithm Approach  

NASA Astrophysics Data System (ADS)

OLAP systems depend heavily on the materialization of multidimensional structures to speed-up queries, whose appropriate selection constitutes the cube selection problem. However, the recently proposed distribution of OLAP structures emerges to answer new globalization's requirements, capturing the known advantages of distributed databases. But this hardens the search for solutions, especially due to the inherent heterogeneity, imposing an extra characteristic of the algorithm that must be used: adaptability. Here the emerging concept known as hyper-heuristic can be a solution. In fact, having an algorithm where several (meta-)heuristics may be selected under the control of a heuristic has an intrinsic adaptive behavior. This paper presents a hyper-heuristic polymorphic algorithm used to solve the extended cube selection and allocation problem generated in M-OLAP architectures.

Loureiro, Jorge; Belo, Orlando


Transformation of Spatial Data Format for Interoperability between GIS Applications  

Microsoft Academic Search

In todays information age, an application to be claimed being interoperable has many benefits and advantages. Our attempt is to propose transformation methods on spatial attributes so that interoperability between spatial data can be obtained. Interoperability state can only be obtained by equalizing two attributes utilized in identifying a location, which are coordinate of the location and LoD of the

Rahmat Budiarto; Pradeep Isawasan; Maulana Abdul Aziz



Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits  

NASA Astrophysics Data System (ADS)

This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

Tsutsumi, Morito; Seya, Hajime




USGS Publications Warehouse

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

Miller, Betty, M.; Domaratz, Michael, A.



Application of spatial light modulators for microlithography  

NASA Astrophysics Data System (ADS)

The Fraunhofer IPMS and Micronic Laser Systems AB have developed a technology for the maskless DUV microlithography using spatial light modulation (SLM). This technology uses an array of micromirrors as a pro-programable mask, which allows writing up to 1 million pixels with a framerate of up to 2 kHz. The SLM is fabricated at the IPMS using its high-voltage CMOS process. The mirrors are fabricated by surface micromachining using a polymer as sacrificial layer. The mirrors are operated in an analog mode to allow sub-pixel placement of the features.

Dauderstaedt, Ulrike A.; Duerr, Peter; Karlin, Tord; Schenk, Harald; Lakner, Hubert



Radiographic applications of spatial frequency multiplexing  

NASA Technical Reports Server (NTRS)

The application of spacial frequency encoding techniques which allow different regions of the X-ray spectrum to be encoded on conventional radiographs was studied. Clinical considerations were reviewed, as were experimental studies involving the encoding and decoding of X-ray images at different energies and the subsequent processing of the data to produce images of specific materials in the body.

Macovski, A.



High spatial resolution probes for neurobiology applications  

NASA Astrophysics Data System (ADS)

Position-sensitive biological neural networks, such as the brain and the retina, require position-sensitive detection methods to identify, map and study their behavior. Traditionally, planar microelectrodes have been employed to record the cell's electrical activity with device limitations arising from the electrode's 2-D nature. Described here is the development and characterization of an array of electrically conductive micro-needles aimed at addressing the limitations of planar electrodes. The capability of this array to penetrate neural tissue improves the electrode-cell electrical interface and allows more complicated 3-D networks of neurons, such as those found in brain slices, to be studied. State-of-the-art semiconductor fabrication techniques were used to etch and passivate conformally the metal coat and fill high aspect ratio holes in silicon. These are subsequently transformed into needles with conductive tips. This process has enabled the fabrication of arrays of unprecedented dimensions: 61 hexagonally close-packed electrodes, ˜200 ?m tall with 60 ?m spacing. Electroplating the tungsten tips with platinum ensure suitable impedance values (˜600 k? at 1 kHz) for the recording of neuronal signals. Without compromising spatial resolution of the neuronal recordings, this array adds a new and exciting dimension to the study of biological neural networks.

Gunning, D. E.; Kenney, C. J.; Litke, A. M.; Mathieson, K.



Construction and application of a spatial hurricane climatology  

NASA Astrophysics Data System (ADS)

The tracking of hurricanes, largely controlled by the organization of the presiding pressure systems, determines whether or not any given hurricane will strike a coastline. Some of the climatic influences, such as the North Atlantic Oscillation, show annual- or decadal-variability. This means that particular locations will have typical hurricane tracks that may vary with the climate. Therefore, it makes physical sense to summarize large sets of hurricane tracks by creating an average track. A hurricane climatology describes the typical hurricane to affect a location. This dissertation proposes expanding the hurricane climatology by adding a spatial dimension in the form of an average track. This is referred to as a spatial hurricane climatology. Since a hurricane track is a polyline, the construction of a spatial hurricane climatology requires averaging spatial polyline data. The technique introduced in this dissertation uses distance maps to average a set of polylines. Three applications of spatial hurricane climatologies are also detailed in this work. First they are used to construct historical hurricane chronologies. This has the possibility of providing an additional 150 years of hurricane data, providing a glimpse into hurricanes prior to the American industrial revolution. The second application is a risk analysis of local-scale hurricane winds. The technique uses statistics of past hurricanes and places them in a deterministic model. This can be performed for any coastal area, and provides wind gusts and economic loss estimations for a once-in-100-year event. Because the statistics are easy to manipulate, this allows for simple analysis of the affects of climate change. This is done as the final application of the technique. These are only a few examples of the uses of spatial hurricane climatologies, and the ideas presented in this research provide a basis for future studies on spatial hurricane patterns, as well as the analysis of spatial polyline data in general.

Scheitlin, Kelsey


Sparse common spatial patterns in brain computer interface applications  

Microsoft Academic Search

The Common Spatial Pattern (CSP) method is a powerful technique for feature extraction from multichannel neural activity and widely used in brain computer interface (BCI) applications. By linearly combining signals from all channels, it maximizes variance for one condition while minimizing for the other. However, the method overfits the data in presence of dense recordings and limited amount of training

Fikri Goksu; N. Firat Ince; Ahmed H. Tewfik



Bayesian approaches for adaptive spatial sampling : an example application.  

SciTech Connect

BAASS (Bayesian Approaches for Adaptive Spatial Sampling) is a set of computational routines developed to support the design and deployment of spatial sampling programs for delineating contamination footprints, such as those that might result from the accidental or intentional environmental release of radionuclides. BAASS presumes the existence of real-time measurement technologies that provide information quickly enough to affect the progress of data collection. This technical memorandum describes the application of BAASS to a simple example, compares the performance of a BAASS-based program with that of a traditional gridded program, and explores the significance of several of the underlying assumptions required by BAASS. These assumptions include the range of spatial autocorrelation present, the value of prior information, the confidence level required for decision making, and ''inside-out'' versus ''outside-in'' sampling strategies. In the context of the example, adaptive sampling combined with prior information significantly reduced the number of samples required to delineate the contamination footprint.

Johnson, R. L.; LePoire, D.; Huttenga, A.; Quinn, J.



Data warehouse and web-based OLAP for hotspot distribution in Indonesia  

Microsoft Academic Search

This work aims to develop a Web-based OLAP (Online Analytical Processing) integrated with a data warehouse for hotspot distribution data. The data warehouse development adopts the three-tier data warehouse architecture. The data are represented in multidimensional model using the star scheme which consists of one data cube with two dimension tables i.e. the dimension time and the dimension location, and

Gananda Hayardisi; Imas S. Sitanggang; Lailan Syaufina



Flexible Data Cube for Range-Sum Queries in Dynamic OLAP Data Cubes  

Microsoft Academic Search

The data cube is frequently adopted to implement On-Line Analytical Processing (OLAP) and provides aggregate information to support the analysis of contents of databases and data warehouses. Range-sum queries require accessing large data cubes and adding the contents of massive cells immediately. Techniques have thus been proposed to accelerate range-sum queries by applying pre-aggregated specified cells of data cubes. However,

Chien-I Lee; Yu-Chiang Li


An Adaptive Peer›to›Peer Network for Distributed Caching of OLAP Results  

Microsoft Academic Search

Peer-to-Peer (P2P) systems are becoming increasingly pop- ular as they enable users to exchange digital information by participating in complex networks. Such systems are in- expensive, easy to use, highly scalable and do not require central administration. Despite their advantages, however, limited work has been done on employing database systems on top of P2P networks. Here we propose the PeerOLAP

Panos Kalnisy; Wee Siong; Lee Tanx


An adaptive peer-to-peer network for distributed caching of OLAP results  

Microsoft Academic Search

Peer-to-Peer (P2P) systems are becoming increasingly popular as they enable users to exchange digital information by participating in complex networks. Such systems are inexpensive, easy to use, highly scalable and do not require central administration. Despite their advantages, however, limited work has been done on employing database systems on top of P2P networks.Here we propose the PeerOLAP architecture for supporting

Panos Kalnis; Wee Siong Ng; Beng Chin Ooi; Dimitris Papadias; Kian-Lee Tans



Management model application at nested spatial levels in Mediterranean Basins  

NASA Astrophysics Data System (ADS)

In the EU Water Framework Directive (WFD) implementation processes, hydrological and water quality models can be powerful tools that allow to design and test alternative management strategies, as well as judging their general feasibility and acceptance. Although in recent decades several models have been developed, their use in Mediterranean basins, where rivers have a temporary character, is quite complex and there is limited information in literature which can facilitate model applications and result evaluations in this region. The high spatial variability which characterizes rainfall events, soil hydrological properties and land uses of Mediterranean basin makes more difficult to simulate hydrological and water quality in this region than in other Countries. This variability also has several implications in modeling simulations results especially when simulations at different spatial scale are needed for watershed management purpose. It is well known that environmental processes operating at different spatial scale determine diverse impacts on water quality status (hydrological, chemical, ecological). Hence, the development of management strategies have to include both large scale (watershed) and local spatial scales approaches (e.g. stream reach). This paper presents the results of a study which analyzes how the spatial scale affects the results of hydrologic process and water quality of model simulations in a Mediterranean watershed. Several aspects involved in modeling hydrological and water quality processes at different spatial scale for river basin management are investigated including model data requirements, data availability, model results and uncertainty. A hydrologic and water quality model (SWAT) was used to simulate hydrologic processes and water quality at different spatial scales in the Candelaro river basin (Puglia, S-E Italy) and to design management strategies to reach as possible WFD goals. When studying a basin to assess its current status and anthropogenic pressures acting on it to define management policies, three spatial levels must be taken into account: the basin, sub-basin and reach level. The common experience showed that different issues can be properly assessed and handled at these three levels. Furthermore different difficulties and problems affect modeling at the same spatial levels. The basin scale is the geographical unit (as required by the WFD) in which coherent management policy must be designed and a Program of Measures must be implemented. At this spatial level a comprehensive understanding of processes acting in the basin area is synthesized (i.e. nutrient loads delivered to the sea). In Mediterranean region land use is commonly very fragmented and also because of complex geomorphology the use of remote sensing can be not easy or sufficient to derive reliable land use maps of agricultural areas. The sub-basin level (<100 km2) is the most suited to gather information on land and water resources use, agricultural practices and pressures by using direct surveys and local knowledge. At this spatial resolution soil and rainfall variability are somehow "averaged" and the model simulation tend to attenuate the complex, local patterns of runoff generation. As a results, an acceptable flow modeling is possible, being this a common issue in the Mediterranean areas where intermittency of rivers is the rule. The reach level is the spatial unit in which physical and ecological processes can be assessed. It is sufficiently narrow to observe peculiarities of geomorphology and water works (i.e. check dams, water abstractions) that can greatly interact with natural flow. At this level modeling often fails in simulating actual streamflow. At local scale field observations can help also to overcome recorded flow measurements inconsistencies, due to the difficulties in metering low flows (i.e. rivulets can detour and skip flow meters) that often lead to underestimate extreme low flow. The modeling of Mediterranean river basins is then rather a challenge and the understanding of potenti

Lo Porto, Antonio; De Girolamo, Anna Maria; Froebrich, Jochen



RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries  

NASA Astrophysics Data System (ADS)

Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at different levels of detail with On-Line Analytical Processing (OLAP) operators such as drill-down and roll-up. The granularity levels which compose a dimension hierarchy are usually fixed during the design step of the data warehouse, according to the identified analysis needs of the users. However, in practice, the needs of users may evolve and grow in time. Hence, to take into account the users’ analysis evolution into the data warehouse, we propose to integrate personalization techniques within the OLAP process. We propose two kinds of OLAP personalization in the data warehouse: (1) adaptation and (2) recommendation.

Bentayeb, Fadila; Favre, Cécile


Applications of spatial light modulators in atom optics.  


We discuss the application of spatial light modulators (SLMs) to the field of atom optics. We show that SLMs may be used to generate a wide variety of optical potentials that are useful for the guiding and dipole trapping of atoms. This functionality is demonstrated by the production of a number of different light potentials using a single SLM device. These include Mach-Zender interferometer patterns and the generation of a bottle-beam. We also discuss the current limitations in SLM technology with regard to the generation of both static and dynamically deformed potentials and their use in atom optics. PMID:19461719

McGloin, David; Spalding, G; Melville, H; Sibbett, W; Dholakia, K



Spatial heterodyne interferometry techniques and applications in semiconductor wafer manufacturing  

NASA Astrophysics Data System (ADS)

Spatial heterodyning is an interferometric technique that allows a full complex optical wavefront to be recorded and quickly reconstructed with a single image capture. Oak Ridge National Laboratory (ORNL) has combined a high-speed, image capture technique with a Fourier reconstruction algorithm to produce a method for recovery of both the phase and magnitude of the optical wavefront. Single frame spatial heterodyne interferometry (SHI) enables high-speed inspection applications such as those needed in the semiconductor industry. While the wide range of materials on wafers make literal interpretation of surface topology difficult, the wafers contain multiple copies of the same die and die-to-die comparisons are used to locate defects in high-aspect-ratio structures such as contacts, vias, and trenches that are difficult to detect with other optical techniques. Metrology with SHI has also been investigated by ORNL, in particular the use of SHI to perform metrology of line widths and heights on photolithographic masks for semiconductor wafer production. Several types of masks are currently in use with phase shifting techniques being employed to extend the wafer printing resolution. With the ability to measure the phase of the wavefront, SHI allows a more complete inspection and measurement of the phase shifting regions.

Bingham, Philip R.; Tobin, Kenneth W.; Hanson, Gregory R.; Simpson, John T.



Spatial and statistical GIS Applications for geological and environmental courses  

NASA Astrophysics Data System (ADS)

Building student's career through undergraduate and graduate courses integrated with modern statistical and GIS software foster a competitive curriculum for their future employment. We present examples that may be introduced in geological courses (e.g. mineralogy, geomorphology, geochronology, structural geology, tectonics, stratigraphy) and environmental courses (natural hazards, hydrology, atmospheric science). Univariate and multivariate statistical models can be used for the interpretation and mapping of the geological and environmental problems. Some of the main statistical univariate models such as the normal distribution as well as the multivariate methods such as the principal component analysis, cluster analysis and factor analysis are the basic methods for understanding the variables of the environmental and geological problems. Examples are presented describing the basic steps for the solution of the problems. Some of the geological problems in different scales are the interpretation of 3D structural data, identification of suitable outcrops for mapping shear sense kinematic indicators. categorical or cluster analysis on lineations depending on their origin, topology of mineral assemblages and spatial distribution of their c-axis, distinguishing paleo-elevations using cluster analysis in geomorphological structures using LiDAR intensity and elevation data for determination of meander evolution patterns and prediction of vulnerable sites for flooding or landsliding. Other applications in atmospheric and hydrology science are the prediction of ground level ozone and the decomposition of water use time series. Those fundamental statistical and spatial concepts may be used in the field or in the lab. In the lab, modern computers and friendly interface user software allow students to process data using advanced statistical methods and GIS techniques. Modern applications in tablets or smart phones may complement field work. Teaching those methods can facilitate advanced mapping, optimize sample collection distribution, field decisions, and later lab data processing.

Marsellos, A.; Tsakiri, K.



Range Sum Queries in Dynamic OLAP Data Cubes  

Microsoft Academic Search

Range sum queries play an important role in analyzing data in data cubes. Many application domains require that data cubes should be updated quite often to provide real time information. Previous techniques for range sum queries, however, can incur an update cost of O(nd) in the worst case, where d is the number of dimensions of the data cube and

Hua-gang Li; Tok Wang Ling; Sin Yeung Lee; Zheng Xuan Loh



Fundamental properties of spatial light modulators for Fourier transform applications  

NASA Astrophysics Data System (ADS)

The performance of Fourier transform optical processors, e.g. optical correlators, beam steering systems, associative memories, etc., depends intimately both on the physical characteristics of the particular spatial light modulator (SLM) and on the particular algorithms that map the signal into the available modulation range of the device. For the most general Fourier systems the information/signal is complex-valued. This is an essential requirement for multi- spot beam steering systems and composite pattern recognition filters. Since practical and/or affordable SLM's only represent a limited range of values in the complex plane (e.g. phase-only or quantized phase), numerous approaches have been proposed and demonstrated for representing, approximating, encoding or mapping complex values to the available SLM states. The best approach depends on the space bandwidth product of the signal, the number of SLM pixels, the computation time of the encoding algorithm, the time available for the application, and the quality of the optical processor, as measured by an application-specific performance metric. Based on the low pixel count and the high cost per pixel of most current SLM's we argue for encoding algorithms that map one signal value to one pixel value, as opposed to group-oriented encoding. This maximized the usable area of the frequency plane. We also recommend algorithms that maximize the fidelity over the entire frequency range as opposed to maximum diffraction efficiency/minimum mean squared error design. These ideas are illustrated with several simulated and experimental results for pseudorandom, minimum Euclidean distance, error diffusion and hybrid/blended encoding algorithms.

Cohn, Robert W.



Datum Transformation of Spatial Data and Application in Cadastre  

NASA Astrophysics Data System (ADS)

In Turkey, cadastral works have been started with local-based works in 1924 and speeded up after 1950's by using photogrammetry. Different measurement methods, coordinate systems and scales have been used in these works. As a result of primary cadastral activities two main products are generated; cadastral maps and title deeds. After this, cadastral data live on the maps, by cadastral activities carried out by cadastral offices and title deed data live on the registrations by land registration activities carried out by land registration offices. Up to 2005 different references systems such as local (graphic) and ED50 have been used for Cadastral maps production. 2000's Land Registry and Cadastre Information System (TAKB?S) Project has started as a pilot application by Land Registry and Cadastre (TKGM). After completion of pilot project spreading activities started in 2005 and still has been ongoing. On the other hand The government has taken the decision to finish primary cadastral activities within three years. The primary cadastral activities completed at the end of 2008. And also TKGM has completed metadata portal in 2008. At last, cadastral map updating (renovation) started in 2009 by using digital orthophoto with 30 cm GSD. Today people have great expectations in accomplishing digital cadastral services, they need correct, reliable, easy and quick accessible land register and cadastral survey information. Even such request expressed in INPIRE directive by using ISO 191XX data standards. This means we have great hard work for spatial data conversion, datum and data transformation for map and cadastral data harmonization. This paper presents results of investigation of used cadastral maps and used datums of the TKGM and possible transformation methods of datum and some recommendations for future applications.

K?sa, A.; Erkek, B.; Ekin, L.



Applications of liquid crystal spatial light modulators in optical communications  

Microsoft Academic Search

Advances in liquid crystal (LC) materials and VLSI technology have enabled the development of multi-phase spatial light modulators (SLM) that can perform high-resolution, dynamic optical beam positioning as well as temporal and spatial beam shaping in the 1550 nm optical communication window. These attractive features can effectively be used to achieve optical switching, optical spectral equalization, tunable optical filtering and

Selam Ahderom; Mherdad Raisi; Kungmang Lo; Kamal E Alameh; Rafie Mavaddat



Spatial Fractal Dimension Ds and Its Application in Earthquake Prediction.  

National Technical Information Service (NTIS)

Using the correlation function approach to calculate the spatial fractal dimension of D(sub s), this paper studies the variation features of the pre-strong earthquake spatial fractal dimension D(sub s) associated with M > or = 6 events occurring in Yunnan...

J. Cai J. Tang Z. Xu



Application of Fourier analysis to multispectral/spatial recognition  

NASA Technical Reports Server (NTRS)

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.

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



Bayesian spatial transformation models with applications in neuroimaging data  

PubMed Central

Summary The aim of this paper 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. Our STMs 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.

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



GIS application on spatial landslide analysis using statistical based models  

NASA Astrophysics Data System (ADS)

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

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



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


Results of lidar modeling based on spatial-angular filtering efficiency criteria are presented. Their analysis shows that the low spatial-angular filtering efficiency of traditional visible and near-infrared systems is an important cause of low signal/background-radiation ratio (SBR) at the photodetector input The low SBR may be responsible for considerable measurement errors and ensuing the low accuracy of the retrieval of atmospheric optical parameters. As shown, the most effective protection against sky background radiation for groundbased biaxial lidars is the modifying of their angular field according to a spatial-angular filtering efficiency criterion. Some effective approaches to achieve a high filtering efficiency for the receiving system optimization are discussed. PMID:12510915

Agishev, Ravil R; Comeron, Adolfo



Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment  

NASA Astrophysics Data System (ADS)

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ; 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7-8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals. The retrieved soundings are also tested in a regional data assimilation WRF 3D-var system to evaluate the potential assist in the NWP model.

Liu, C.; Liu, G.; Lin, T.



Application of fuzzy logic technology for spatial load forecasting  

SciTech Connect

Utilities are required to provide reliable power to customers. In the design stages, utilities need to plan ahead for anticipated future load growth under different possible scenarios. Their decisions and designs can affect the gain or loss of millions of dollars for their companies as well as customer satisfaction and future economic growth in their territory. This paper proposes and describes the general methodology to use fuzzy logic to fuse the available information for spatial load forecasting. The proposed scheme can provide distribution planners other alternatives to aggregate their information for spatial load forecasting.

Chow, M.Y. [North Carolina State Univ., Raleigh, NC (United States). Dept. of Electrical and Computer Engineering] [North Carolina State Univ., Raleigh, NC (United States). Dept. of Electrical and Computer Engineering; Tram, H. [ABB Power T and D Company Inc., Cary, NC (United States)] [ABB Power T and D Company Inc., Cary, NC (United States)



Spatial monitoring of geographic patterns: an application to crime analysis  

Microsoft Academic Search

This paper describes a new procedure for detecting changes over time in the spatial pattern of point events, combining the nearest neighbor statistic and cumulative sum methods. The method results in the rapid detection of deviations from expected geographic patterns. It may also be used for various subregions and may be implemented using time windows of differing length to search

P. Rogerson; Y. Sun



3D spatial interaction: applications for art, design, and science  

Microsoft Academic Search

3D interfaces use motion sensing, physical input, and spatial interaction techniques to effectively control highly dynamic virtual content. Now, with the advent of the Nintendo Wii, Sony Move, and Microsoft Kinect, game developers and researchers must create compelling interface techniques and game-play mechanics that make use of these technologies. At the same time, it is becoming increasingly clear that emerging

Joseph J. LaViola; Daniel F. Keefe



Random vectors and spatial analysis by geostatistics for geotechnical applications  

Microsoft Academic Search

Geostatistics is extended to the spatial analysis of vector variables by defining the estimation variance and vector variogram in terms of the magnitude of difference vectors. Many random variables in geotechnology are in vectorial terms rather than scalars, and its structural analysis requires those sample variable interpolations to construct and characterize structural models. A better local estimator will result in

Dae S. Young



Unified Pairwise Spatial Relations: An Application to Graphical Symbol Retrieval  

NASA Astrophysics Data System (ADS)

In this paper, we present a novel unifying concept of pairwise spatial relations. We develop two way directional relations with respect to a unique point set, based on topology of the studied objects and thus avoids problems related to erroneous choices of reference objects while preserving symmetry. The method is robust to any type of image configuration since the directional relations are topologically guided. An automatic prototype graphical symbol retrieval is presented in order to establish its expressiveness.

Santosh, K. C.; Wendling, Laurent; Lamiroy, Bart


A Query Cache Tool for Optimizing Repeatable and Parallel OLAP Queries  

NASA Astrophysics Data System (ADS)

On-line analytical processing against data warehouse databases is a common form of getting decision making information for almost every business field. Decision support information oftenly concerns periodic values based on regular attributes, such as sales amounts, percentages, most transactioned items, etc. This means that many similar OLAP instructions are periodically repeated, and simultaneously, between the several decision makers. Our Query Cache Tool takes advantage of previously executed queries, storing their results and the current state of the data which was accessed. Future queries only need to execute against the new data, inserted since the queries were last executed, and join these results with the previous ones. This makes query execution much faster, because we only need to process the most recent data. Our tool also minimizes the execution time and resource consumption for similar queries simultaneously executed by different users, putting the most recent ones on hold until the first finish and returns the results for all of them. The stored query results are held until they are considered outdated, then automatically erased. We present an experimental evaluation of our tool using a data warehouse based on a real-world business dataset and use a set of typical decision support queries to discuss the results, showing a very high gain in query execution time.

Santos, Ricardo Jorge; Bernardino, Jorge


Tract-Based Spatial Statistics: Application to Mild Cognitive Impairment  

PubMed Central

Rationale and Objectives. The primary objective of the current investigation was to characterize white matter integrity in different subtypes of mild cognitive impairment (MCI) using tract-based spatial statistics of diffusion tensor imaging. Materials and Methods. The study participants were divided into 4 groups of 30 subjects each as follows: cognitively healthy controls, amnestic MCI, dysexecutive MCI, and Alzheimer's disease (AD). All subjects underwent a comprehensive neuropsychological assessment, apolipoprotein E genotyping, and 3-tesla MRI. The diffusion tensor was reconstructed and then analyzed using tract-based spatial statistics. The changes in brain white matter tracts were also examined according to the apolipoprotein E ?4 status. Results. Compared with controls, amnestic MCI patients showed significant differences in the cerebral white matter, where changes were consistently detectable in the frontal and parietal lobes. We found a moderate impact of the apolipoprotein E ?4 status on the extent of white matter disruption in the amnestic MCI group. Patients with AD exhibited similar but more extensive alterations, while no significant changes were observed in dysexecutive MCI patients. Conclusion. The results from this study indicate that amnestic MCI is the most likely precursor to AD as both conditions share significant white matter damage. By contrast, dysexecutive MCI seems to be characterized by a distinct pathogenesis.

Wai, Yau-Yau; Hsu, Wen-Chuin; Fung, Hon-Chung; Lee, Jiann-Der; Chan, Hsiao-Lung; Tsai, Ming-Lun; Lin, Yu-Chun; Wu, Yih-Ru; Ying, Leslie; Wang, Jiun-Jie



Spatially inhomogeneous polarization and its application in beam shaping  

NASA Astrophysics Data System (ADS)

This work focuses on spatially inhomogeneous polarization and how it can be applied to the laser beam shaping field. As an example of spatially inhomogeneous polarization, cylindrical vector beams are studied both theoretically and experimentally. Vector diffraction theory is applied to study beam focusing properties. It can be demonstrated that by changing the beam parameters such as pupil size, intensity profile and polarization state across the wave-front, beam shaping can be performed for high numerical aperture (NA) systems. A direct method to experimentally quantify the longitudinal component (z-component), which the beam shaping relies on, is proposed and carried out. The new concept of spiral polarization is proposed and verified by simulation using vector diffraction theory. This polarization has the capability of performing high NA beam shaping independent of numerical aperture. For low numerical aperture systems, the concept of a polarization plate from the design point of view is put forward to obtain the smallest flat-top shaped focus. The simulated annealing algorithm is adopted as a method to numerically design the proper polarization plate. Experiments have been carried out to demonstrate the flat-top focal spot obtained with a properly designed polarization plate which verifies the validity of the new concept. Fourier Optics theory is employed to demonstrate that the flat-top focal spot obtainable from the polarization plate has the theoretically smallest size.

Hao, Bing


Nonparametric Spatial Models for Extremes: Application to Extreme Temperature Data*  

PubMed Central

Summary Estimating the probability of extreme temperature events is difficult because of limited records across time and the need to extrapolate the distributions of these events, as opposed to just the mean, to locations where observations are not available. Another related issue is the need to characterize the uncertainty in the estimated probability of extreme events at different locations. Although the tools for statistical modeling of univariate extremes are well-developed, extending these tools to model spatial extreme data is an active area of research. In this paper, in order to make inference about spatial extreme events, we introduce a new nonparametric model for extremes. We present a Dirichlet-based copula model that is a flexible alternative to parametric copula models such as the normal and t-copula. The proposed modelling approach is fitted using a Bayesian framework that allow us to take into account different sources of uncertainty in the data and models. We apply our methods to annual maximum temperature values in the east-south-central United States.

Fuentes, Montserrat; Henry, John; Reich, Brian



Optimizing spatial filters with kernel methods for BCI applications  

NASA Astrophysics Data System (ADS)

Brain Computer Interface (BCI) is a communication or control system in which the user's messages or commands do not depend on the brain's normal output channels. The key step of BCI technology is to find a reliable method to detect the particular brain signals, such as the alpha, beta and mu components in EEG/ECOG trials, and then translate it into usable control signals. In this paper, our objective is to introduce a novel approach that is able to extract the discriminative pattern from the non-stationary EEG signals based on the common spatial patterns(CSP) analysis combined with kernel methods. The basic idea of our Kernel CSP method is performing a nonlinear form of CSP by the use of kernel methods that can efficiently compute the common and distinct components in high dimensional feature spaces related to input space by some nonlinear map. The algorithm described here is tested off-line with dataset I from the BCI Competition 2005. Our experiments show that the spatial filters employed with kernel CSP can effectively extract discriminatory information from single-trial EGOG recorded during imagined movements. The high recognition of linear discriminative rates and computational simplicity of "Kernel Trick" make it a promising method for BCI systems.

Zhang, Jiacai; Tang, Jianjun; Yao, Li



Multi-Scale Partitions: Application to Spatial and Statistical Databases  

Microsoft Academic Search

We study the impact of scale on data representation from both the modelling and querying points of view. While our starting point was geographi- cal applications, statistical databases also address this problem of data represen- tation at various levels of abstraction. From these requirements, we propose a model which allows: (i) database querying without exact knowledge of the data abstraction

Philippe Rigaux; Michel Scholl



Radio Frequency Interference Removal through the Application of Spatial Filtering Techniques on the Parkes Multibeam Receiver  

NASA Astrophysics Data System (ADS)

This paper addresses the first practical application of spatial filtering techniques to data taken with a multibeam receiver. Spatial filters make use of the relative arrival times of a signal at multiple sensors to identify and separate signals from different directions. The method is a consequence of the Karhunen-Loève theorem and relies on the eigen decomposition of the covariance matrix formed from the multiple signal paths. The effectiveness of the spatial filtering techniques is demonstrated on observations of the Vela pulsar taken with the Parkes 20 cm Multibeam receiver. The experiment was highly successful, and the results show spatial filtering methods provide powerful tools for interference mitigation with an array feed receiver. Extensions of the algorithm to reduce computational requirements and allow application on short (submillisecond) timescales are also explored.

Kocz, J.; Briggs, F. H.; Reynolds, J.



Application of cooled spatial light modulator for high power nanosecond laser micromachining.  


The application of a commercially available spatial light modulator (SLM) to control the spatial intensity distribution of a nanosecond pulsed laser for micromachining is described for the first time. Heat sinking is introduced to increase the average power handling capabilities of the SLM beyond recommended limits by the manufacturer. Complex intensity patterns are generated, using the Inverse Fourier Transform Algorithm, and example laser machining is demonstrated. The SLM enables both complex beam shaping and also beam steering. PMID:20721094

Beck, Rainer J; Parry, Jonathan P; MacPherson, William N; Waddie, Andrew; Weston, Nick J; Shephard, Jonathan D; Hand, Duncan P



Modeling Non-Linear Spatial Dynamics: A Family of Spatial STAR Models and an Application to U.S. Economic Growth  

Microsoft Academic Search

This paper investigates non-linearity in spatial processes models and allows for a gradual regime-switching structure in the form of a smooth transition autoregressive process. Until now, applications of the smooth transition autoregressive (STAR) model have been largely confined to the time series context. The paper focuses on extending the non-linear smooth transition perspective to spatial processes models, in which spatial

Valerien O. Pede; Raymond J. G. M. Florax; Matthew T. Holt



Spatial analysis of image registration methodologies for fusion applications  

NASA Astrophysics Data System (ADS)

Data registration is the foundational step for fusion applications such as change detection, data conflation, ATR, and automated feature extraction. The efficacy of data fusion products can be limited by inadequate selection of the transformation model, or characterization of uncertainty in the registration process. In this paper, three components of image-to-image registration are investigated: 1) image correspondence via feature matching, 2) selection of a transformation function, and 3) estimation of uncertainty. Experimental results are presented for photogrammetric versus non-photogrammetric transfer of point features for four different sensor types and imaging geometries. The results demonstrate that a photogrammetric transfer model is generally more accurate at point transfer. Moreover, photogrammetric methods provide a reliable estimation of accuracy through the process of error propagation. Reliable local uncertainty derived from the registration process is particularly desirable information to have for subsequent fusion processes. To that end, uncertainty maps are generated to demonstrate global trends across the test images. Recommendations for extending this methodology to non-image data types are provided.

Doucette, Peter J.; Theiss, Henry J.; Mikhail, Edward M.; Motsko, Dennis J.



Integrating GIS and GPS into a spatially-variable-rate herbicide application system  

NASA Astrophysics Data System (ADS)

A spatially variable rate herbicide application system was developed and a site-specific evaluation of its field performance and accuracy was conducted. The system was capable of automatically changing on-the-go the application rate of active ingredients (AI) to meet the requirements of current sprayer field location. A 4.2 ha field was sampled on an 18.3 m grid for soil texture and percent organic matter (%OM). The soil texture ranged from sandy loam to clay, while the %OM ranged from 0.98 to 2.73 percent. For the preemergence herbicide selected, a herbicide management table was used to determine the appropriate AI application rate for each area of the field depending on spatial variation of field parameter data (soil texture and %OM). For the sampled field, the AI application rate ranged from 3510 mL/ha to 5260 mL/ha. A geographical information system (GIS) software was utilized to develop a georeferenced map (management map) of field application rates. A direct nozzle injection field sprayer was equipped with a real-time differentially corrected global positioning system (DGPS). A control program was developed to retrieve the desired application rate from the GIS map utilizing position data (latitude and longitude) supplied by the DGPS system. The retrieved application rate was sent, in a voltage format, to a 21X datalogger which was used to change on-the-go the AI flow rate to correspond with the desired application rate at a specific sprayer ground speed and field position. Results revealed that the DGPS system maintained, on the average, an accuracy of one meter. However, a distance error of location determination produced by the DGPS system reached 30.84 m with a correction message age of 98 seconds. For the four application rates used in the study, the highest average application rate error (average difference between desired and calculated application rates) and CV values were 2.0 percent and 0.07 percent, respectively for the analyzed samples. The maximum application rate error was 14 percent for 96 percent of the field data points (96 percent of the time). These results showed that the control system was accurate in producing the desired application rate. On the average, the greatest reaction time of the system was 2.2 seconds. The spatial analysis showed that most application rate errors occurred near transition zones. These analysis also revealed that the contour lines of the calculated application rate maps followed the same pattern and coincide with the management map contour lines. The developed spatially variable rate herbicide application system was found to accurately reproduce the application rate management map in a repeatable fashion.

Al-Gaadi, Khalid Ali



Application of optical processing to adaptive phased array radar  

NASA Astrophysics Data System (ADS)

The results of the investigation of the applicability of optical processing to Adaptive Phased Array Radar (APAR) data processing will be summarized. Subjects that are covered include: (1) new iterative Fourier transform based technique to determine the array antenna weight vector such that the resulting antenna pattern has nulls at desired locations; (2) obtaining the solution of the optimal Wiener weight vector by both iterative and direct methods on two laboratory Optical Linear Algebra Processing (OLAP) systems; and (3) an investigation of the effects of errors present in OLAP systems on the solution vectors.

Carroll, C. W.; Vijaya Kumar, B. V. K.



Assessing the applicability of the spatial autocorrelation method: A theoretical approach  

Microsoft Academic Search

We present a rigorous theoretical framework that allows one to assess the range of applicability of the spatial autocorrelation (SPAC) method, a technique of microtremor exploration that is widely used to infer phase velocities of Rayleigh waves using vertical-motion records from a circular array of seismic sensors. The magnitude of systematic errors (biases) that depend on the number of seismic

Ikuo Cho; Taku Tada; Yuzo Shinozaki



Phase conjugation of mode scrambled optical beams Application to spatial recovery and interbeam temporal information exchange  

NASA Astrophysics Data System (ADS)

Coupling of temporal information between two beams is demonstrated using a combination of a multimode fiber and a photorefractive passive phase conjugation mirror. It is shown that the polarization and spatial properties are fully recovered but temporal information is exchanged. The theoretical explanation for these phenomena and possible applications are discussed.

Yahalom, Ram; Kyuma, Kazuo; Yariv, Amnon



Parallelized genetic optimization of spatial light modulator addressing for diffractive applications.  


We describe a new technique for optimizing the addressing of spatial light modulators in dynamic holographic applications. The method utilizes 200 times parallelization using imaging of subholograms in combination with genetic optimization. Compared to a fixed linear addressing curve for all different gratings, the diffraction efficiency can be improved by up to 25% for a Holoeye Pluto LCoS modulator. PMID:24663371

Haist, Tobias; Lingel, Christian; Adler, Rodolfo; Osten, Wolfgang



Progressive phase conjugation and its application in reconfigurable spatial-mode extraction and conversion  

NASA Astrophysics Data System (ADS)

We develop a new technology, which is referred to as progressive phase conjugation (PPC), in which phase conjugation is electrically performed without requiring a coherent reference beam by fusion using a reference-free spatial phase detection and spatial phase modulation. This method enables remote setting of a phase detector from the signal transmitter without an additional transmission line for the reference beam. It also enables realization of high-speed and dynamic wavefront compensation owing to its open-loop architecture using the single-shot phase detection method. Therefore, the PPC is applicable to a wide range of optical communication technologies, including the reconfigurable spatial-mode extraction and conversion of mode transmission in a multi-mode fiber (MMF). In our experiment, spatial modes are generated by directing a laser beam into a MMF with a 50-micron core diameter. At the output side of the optical fiber, the phase distributions of the spatial modes are detected using the reference-free phase detector constructed by combining a spatial filtering method with holographic diversity interferometry using two CCD imagers. Then, the phase conjugate distribution of the detected phase pattern is displayed on a LCOS-type SLM. We confirm that the PPC system can extract a specific mode pattern with a considerably low crosstalk of less than 1% by displaying the corresponding phase-conjugation pattern on the SLM. In addition, we demonstrated a reconfigurable spatial-mode conversion by the phase control technology using the SLM. By applying the spatial phase modulation to an optical beam incident on the SLM, the spatial mode of the output beam is flexibly changed.

Okamoto, Atsushi; Maeda, Tomohiro; Hirasaki, Yuki; Tomita, Akihisa; Sato, Kunihiro



Hybrid modeling of spatial continuity for application to numerical inverse problems  

USGS Publications Warehouse

A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km2 Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km2 fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km2 transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.

Friedel, Michael J.; Iwashita, Fabio



Randomness in Computing and Simulations for Spherical and Spatial Geoscience Applications  

NASA Astrophysics Data System (ADS)

Mathematical randomness has long been studied and in computing, different simulation approaches have been investigated and implemented in all kinds of stochastic computations. Following a brief overview of true (or physical), pseudo, chaotic and quasi-random number generation, some equi-distributed and low discrepancy sequences will be discussed in view of their well-known applications in Monte Carlo simulations. For spherical and spatial computations and simulations, a number of statistical and related considerations are important for geoscience applications. In particular, nonlinear domain and other transformations generally complicate the stochastic simulations and their inferences. Various sample applications will illustrate the complexities with suggested methodologies and some practical recommendations.

Blais, J. A.



The application of inverse methods to spatially-distributed acoustic sources  

NASA Astrophysics Data System (ADS)

Acoustic inverse methods, based on the output of an array of microphones, can be readily applied to the characterisation of acoustic sources that can be adequately modelled as a number of discrete monopoles. However, there are many situations, particularly in the fields of vibroacoustics and aeroacoustics, where the sources are distributed continuously in space over a finite area (or volume). This paper is concerned with the practical problem of applying inverse methods to such distributed source regions via the process of spatial sampling. The problem is first tackled using computer simulations of the errors associated with the application of spatial sampling to a wide range of source distributions. It is found that the spatial sampling criterion for minimising the errors in the radiated far-field reconstructed from the discretised source distributions is strongly dependent on acoustic wavelength but is only weakly dependent on the details of the source field itself. The results of the computer simulations are verified experimentally through the application of the inverse method to the sound field radiated by a ducted fan. The un-baffled fan source with the associated flow field is modelled as a set of equivalent monopole sources positioned on the baffled duct exit along with a matrix of complimentary non-flow Green functions. Successful application of the spatial sampling criterion involves careful frequency-dependent selection of source spacing, and results in the accurate reconstruction of the radiated sound field. Discussions of the conditioning of the Green function matrix which is inverted are included and it is shown that the spatial sampling criterion may be relaxed if conditioning techniques, such as regularisation, are applied to this matrix prior to inversion.

Holland, K. R.; Nelson, P. A.



Jackson State University's Center for Spatial Data Research and Applications: New facilities and new paradigms  

NASA Technical Reports Server (NTRS)

Jackson State University recently established the Center for Spatial Data Research and Applications, a Geographical Information System (GIS) and remote sensing laboratory. Taking advantage of new technologies and new directions in the spatial (geographic) sciences, JSU is building a Center of Excellence in Spatial Data Management. New opportunities for research, applications, and employment are emerging. GIS requires fundamental shifts and new demands in traditional computer science and geographic training. The Center is not merely another computer lab but is one setting the pace in a new applied frontier. GIS and its associated technologies are discussed. The Center's facilities are described. An ARC/INFO GIS runs on a Vax mainframe, with numerous workstations. Image processing packages include ELAS, LIPS, VICAR, and ERDAS. A host of hardware and software peripheral are used in support. Numerous projects are underway, such as the construction of a Gulf of Mexico environmental data base, development of AI in image processing, a land use dynamics study of metropolitan Jackson, and others. A new academic interdisciplinary program in Spatial Data Management is under development, combining courses in Geography and Computer Science. The broad range of JSU's GIS and remote sensing activities is addressed. The impacts on changing paradigms in the university and in the professional world conclude the discussion.

Davis, Bruce E.; Elliot, Gregory



High-resolution Fresnel zone plates for x-ray applications by spatial-frequency multiplication  

Microsoft Academic Search

We propose a scheme for deriving a high-resolution zone plate from a coarser one by interfering the light from two positive-order foci. We give a theorteical analysis of the process, which we call spatial-frequency multiplication. The analysis requires calculation of diffracted intensities far off axis, and we derive validity conditions for the application of approximate methods to this calculation. Specifically,

W. B. Yun; M. R. Howells



Robust Distance-Based Clustering with Applications to Spatial Data Mining  

Microsoft Academic Search

.    In this paper we present a method for clustering geo-referenced data suitable for applications in spatial data mining, based\\u000a on the medoid method. The medoid method is related to k -MEANS, with the restriction that cluster representatives be chosen from among the data elements. Although the medoid method\\u000a in general produces clusters of high quality, especially in the

Vladimir Estivill-castro; Michael E. Houle



High-Q polymer resonators with spatially controlled photo-functionalization for biosensing applications  

NASA Astrophysics Data System (ADS)

We demonstrate the applicability of polymeric whispering gallery mode resonators fabricated on silicon as biosensors. Optical measurements on the passive resonators in the visible spectral range yield Q-factors as high as 1.3×107. Local, covalent surface functionalization, is achieved by spatially controlled UV-exposure of a derivative of the photoreactive crosslinker benzophenone. Protein detection is shown using the specific binding of the biotin-streptavidin system.

Beck, Torsten; Mai, Martin; Grossmann, Tobias; Wienhold, Tobias; Hauser, Mario; Mappes, Timo; Kalt, Heinz



Application Composition based on WMS Layers for Supporting Spatial Data Infrastructure  

NASA Astrophysics Data System (ADS)

Web-based spatial data services are essential building blocks for Spatial Data Infrastructure (SDI). WMS, WFS and WCS are adopted increasingly to provide interoperable access to facilitate the integration of different web applications with a large number of data from various scientific domains. However, these services are widely dispersed and hard to be found, accessed, and utilized, this is especially true when we want to develop an application to mashing up multiple layers from multiple servers. To tackle this problem, we proposed a layer-based service oriented integration framework, focusing on the integration of distributed WMS resources, including 1) a Service Capabilities Clearing House (SCCH) to preprocess and store the services’ capability information of WMS, WFS and WCS. 2) a layer-based search engine with spatial, temporal and performance criteria to find more accurate records. 3) API and layer-based metadata to make the framework open and interoperable. 4) Customized 2-D, 3-D, and 4-D visualization interface for application integration. Acknowledgement: The research is supported by FGDC 2009 CAP program (project # G09AC00103,

Li, Z.; Wu, H.; Yang, C.



Spatially controlled electro-stimulated DNA adsorption and desorption for biochip applications.  


The manipulation of biomolecules at solid/liquid interfaces is important for the enhanced performance of a number of biomedical devices, including biochips. This study focuses on the spatial control of surface interactions of DNA as well as the electro-stimulated adsorption and desorption of DNA by appropriate surface modification of highly doped p-type silicon. Surface modification by plasma polymerisation of allylamine resulted in a surface that supported DNA adsorption and sustained cell attachment. Subsequent high-density grafting of poly(ethylene oxide) formed a low fouling layer resistant to biomolecule adsorption and cell attachment. Spatially controlled excimer laser ablation of the surface produced patterns of re-exposed plasma polymer with high-resolution. On patterned surfaces, preferential electro-stimulated adsorption of DNA to the allylamine plasma polymer surface and subsequent desorption by the application of a negative bias was observed. Furthermore, the concept presented here was investigated for use in transfection chips. Cell culture experiments with human embryonic kidney cells, using the expression of green fluorescent protein as a reporter, demonstrated efficient and controlled transfection of cells. Electro-stimulated desorption of DNA was shown to yield significantly enhanced solid phase transfection efficiencies to values of up to 30%. The ability to spatially control DNA adsorption combined with the ability to control the binding and release of DNA by application of a controlled voltage enables an advanced level of control over DNA bioactivity on solid substrates and lends itself to biochip applications. PMID:16303297

Hook, Andrew L; Thissen, Helmut; Hayes, Jason P; Voelcker, Nicolas H



Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui  

PubMed Central

Background The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. Methods This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Results Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. Conclusions This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications.



Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics  

NASA Astrophysics Data System (ADS)

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial ?-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

Marquez-Lago, Tatiana T.; Burrage, Kevin



Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.  


In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity. PMID:17867731

Marquez-Lago, Tatiana T; Burrage, Kevin



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

USGS Publications Warehouse

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 study of the potential impacts of climate change.

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



Application of Image Analysis for Characterization of Spatial Arrangements of Features in Microstructure  

NASA Technical Reports Server (NTRS)

A number of microstructural processes are sensitive to the spatial arrangements of features in microstructure. However, very little attention has been given in the past to the experimental measurements of the descriptors of microstructural distance distributions due to the lack of practically feasible methods. We present a digital image analysis procedure to estimate the micro-structural distance distributions. The application of the technique is demonstrated via estimation of K function, radial distribution function, and nearest-neighbor distribution function of hollow spherical carbon particulates in a polymer matrix composite, observed in a metallographic section.

Louis, Pascal; Gokhale, Arun M.



Application of spatial frequency response as a criterion for evaluating thermal imaging camera performance  

NASA Astrophysics Data System (ADS)

Police, firefighters, and emergency medical personnel are examples of first responders that are utilizing thermal imaging cameras in a very practical way every day. However, few performance metrics have been developed to assist first responders in evaluating the performance of thermal imaging technology. This paper describes one possible metric for evaluating spatial resolution using an application of Spatial Frequency Response (SFR) calculations for thermal imaging. According to ISO 12233, the SFR is defined as the integrated area below the Modulation Transfer Function (MTF) curve derived from the discrete Fourier transform of a camera image representing a knife-edge target. This concept is modified slightly for use as a quantitative analysis of the camera's performance by integrating the area between the MTF curve and the camera's characteristic nonuniformity, or noise floor, determined at room temperature. The resulting value, which is termed the Effective SFR, can then be compared with a spatial resolution value obtained from human perception testing of task specific situations to determine the acceptability of the performance of thermal imaging cameras. The testing procedures described herein are being developed as part of a suite of tests for possible inclusion into a performance standard on thermal imaging cameras for first responders.

Lock, Andrew; Amon, Francine



Lack of spatial and behavioral responses to immunocontraception application in African elephants (Loxodonta africana).  


Opinions are divided as to whether human intervention to control elephant (Loxodonta africana) population growth is desirable, partly because of elephant welfare concerns. Female contraception through immunization with porcine zona pellucida (PZP) proteins is viable. The effects of sustained use and application of the PZP vaccine on elephant behavioral and spatial responses were examined by evaluating herd ranging, fission-fusion dynamics, association patterns, and reproductive and sexual behaviors. Minimal change was anticipated as a result of long calf dependence on and association with cows, a reduced but not indefinite 0% growth rate and the known mechanism of action of PZP vaccines, and minimal expected change in resource requirements necessitating behavioral or spatial use adaptations. Although behavioral effects identified in previous hormonal contraceptive trials were evident, it was demonstrated that immunocontraception caused no prolonged behavioral, social, or spatial changes over the 11-yr study period. Individually identified elephants were monitored from 1999 to 2011. Minimal, short-term social disruption, with temporary changes to the herds' core ranges, was observed during the annual treatment events, particularly in the first three treatment years, when vaccinations were conducted exclusively from the ground. Thereafter, when vaccinations were conducted aerially, minor disruptions were confined to the morning of administration only. Despite sustained treatments resulting in demographic changes of fewer calves being born, treatments did not alter spatial range use, and no adverse interherd-intraherd relations were observed. Similarly, resource requirements did not change as calving still occurred, although in fewer numbers. It was concluded that PZP immunocontraception has no detectable behavioral or social consequences in elephants over the course of 11 yr, providing a convincing argument for the use of sustained immunocontraception in the medium to long term as an important tool for elephant management. Behavioral consequences of alternative management approaches should all receive similar scrutiny to enable managers to make informed decisions when weighing management interventions. PMID:24437086

Delsink, Audrey K; Kirkpatrick, Jay; van Altena, J J; Bertschinger, Henk J; Ferreira, Sam M; Slotow, Robert



Multi-storm, multi-catchment investigation of rainfall spatial resolution requirements for urban hydrological applications  

NASA Astrophysics Data System (ADS)

Rainfall estimates of the highest possible resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made over the last few decades in high resolution measurement of rainfall at urban scales and in the modelling of urban runoff processes, a number of questions as to the actual resolution requirements for input data and models remain to be answered. With the aim of answering some of these questions, this work investigates the impact of rainfall estimates of different spatial resolutions and structures on the hydraulic outputs of models of several urban catchments with different characteristics. For this purpose multiple storm events, including convective and stratiform ones, measured by a polarimetric X-band radar located in Cabauw (NL) were selected for analysis. The original radar estimates, at 100 m and 1 min resolutions, were aggregated to coarser spatial resolutions of up to 1000 m. These estimates were then applied to the high-resolution semi distributed hydraulic models of four urban catchments of similar size (approx. 7 km2), but different morphological and land use characteristics; these are: the Herent catchment (Belgium), the Cranbrook catchment (UK), the Morée Sausset catchment (France) and the Kralingen District of Rotterdam (The Netherlands). When doing so, methodologies for standardising rainfall inputs and making results comparable were implemented. Moreover, the results were analysed considering different points at each catchment, while also taking into account the particular storm and catchment characteristics. The results obtained for the storms used in this study show that flat and less compact catchments (e.g. polder areas) may be more sensitive to the spatial resolution of rainfall estimates, as compared to catchments with higher slopes and compactness, which in general show little sensitivity to changes in spatial resolution. While this study provides interesting insights, further investigation is still required in order to obtain a more complete answer regarding rainfall resolution requirements for urban hydrological applications. Future work should include testing on higher resolution fully distributed hydro models, as well as the analysis of many more storm events.

Ochoa Rodriguez, Susana; ten Veldhuis, Marie-Claire; Bruni, Guendalina; Gires, Auguste; van Assel, Johan; Wang, Lipen; Reinoso-Rodinel, Ricardo; Ichiba, Abdellah; Kroll, Stefan; Schertzer, Daniel; Onof, Christian; Willems, Patrick



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

NASA Astrophysics Data System (ADS)

High resolution (?/?? ~ 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-?m 55Fe 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.

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



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


High resolution (???? ? 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-?m (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. PMID:23126946

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



Application of Spatially Resolved High Resolution Crystal Spectrometry to ICF Plasmas  

SciTech Connect

High resolution (?/?#3;? ~ 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-?m 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.

Kenneth W. Hill, et. al.



Application of a field-based method to spatially varying thermal transport problems in molecular dynamics  

NASA Astrophysics Data System (ADS)

This paper derives a methodology to enable spatial and temporal control of thermally inhomogeneous molecular dynamics (MD) simulations. The primary goal is to perform non-equilibrium MD of thermal transport analogous to continuum solutions of heat flow which have complex initial and boundary conditions, moving MD beyond quasi-equilibrium simulations using periodic boundary conditions. In our paradigm, the entire spatial domain is filled with atoms and overlaid with a finite element (FE) mesh. The representation of continuous variables on this mesh allows fixed temperature and fixed heat flux boundary conditions to be applied, non-equilibrium initial conditions to be imposed and source terms to be added to the atomistic system. In effect, the FE mesh defines a large length scale over which atomic quantities can be locally averaged to derive continuous fields. Unlike coupling methods which require a surrogate model of thermal transport like Fourier's law, in this work the FE grid is only employed for its projection, averaging and interpolation properties. Inherent in this approach is the assumption that MD observables of interest, e.g. temperature, can be mapped to a continuous representation in a non-equilibrium setting. This assumption is taken advantage of to derive a single, unified set of control forces based on Gaussian isokinetic thermostats to regulate the temperature and heat flux locally in the MD. Example problems are used to illustrate potential applications. In addition to the physical results, data relevant to understanding the numerical effects of the method on these systems are also presented.

Templeton, Jeremy A.; Jones, Reese E.; Wagner, Gregory J.



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

SciTech Connect

High resolution ({lambda}/{Delta}{lambda}{approx} 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-{mu}m {sup 55}Fe source, and by ray-tracing calculations. Throughput calculations agree with measurements, and predict detector counts in the range 10{sup -8}-10{sup -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.

Hill, K. W.; Bitter, M.; Delgado-Aparacio, L.; Pablant, N. A. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States); Beiersdorfer, P.; Schneider, M.; Widmann, K. [Physics Division, Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Sanchez del Rio, M. [European Synchrotron Radiation Facility, BP 220, 38043-Grenoble Cedex (France); Zhang, L. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China)



Modeling diffusion-weighted MRI as a spatially variant Gaussian mixture: Application to image denoising  

PubMed Central

Purpose: This work describes a spatially variant mixture model constrained by a Markov random field to model high angular resolution diffusion imaging (HARDI) data. Mixture models suit HARDI well because the attenuation by diffusion is inherently a mixture. The goal is to create a general model that can be used in different applications. This study focuses on image denoising and segmentation (primarily the former). Methods: HARDI signal attenuation data are used to train a Gaussian mixture model in which the mean vectors and covariance matrices are assumed to be independent of spatial locations, whereas the mixture weights are allowed to vary at different lattice positions. Spatial smoothness of the data is ensured by imposing a Markov random field prior on the mixture weights. The model is trained in an unsupervised fashion using the expectation maximization algorithm. The number of mixture components is determined using the minimum message length criterion from information theory. Once the model has been trained, it can be fitted to a noisy diffusion MRI volume by maximizing the posterior probability of the underlying noiseless data in a Bayesian framework, recovering a denoised version of the image. Moreover, the fitted probability maps of the mixture components can be used as features for posterior image segmentation. Results: The model-based denoising algorithm proposed here was compared on real data with three other approaches that are commonly used in the literature: Gaussian filtering, anisotropic diffusion, and Rician-adapted nonlocal means. The comparison shows that, at low signal-to-noise ratio, when these methods falter, our algorithm considerably outperforms them. When tractography is performed on the model-fitted data rather than on the noisy measurements, the quality of the output improves substantially. Finally, ventricle and caudate nucleus segmentation experiments also show the potential usefulness of the mixture probability maps for classification tasks. Conclusions: The presented spatially variant mixture model for diffusion MRI provides excellent denoising results at low signal-to-noise ratios. This makes it possible to restore data acquired with a fast (i.e., noisy) pulse sequence to acceptable noise levels. This is the case in diffusion MRI, where a large number of diffusion-weighted volumes have to be acquired under clinical time constraints.

Gonzalez, Juan Eugenio Iglesias; Thompson, Paul M.; Zhao, Aishan; Tu, Zhuowen



Assessing the applicability of the spatial autocorrelation method: A theoretical approach  

NASA Astrophysics Data System (ADS)

We present a rigorous theoretical framework that allows one to assess the range of applicability of the spatial autocorrelation (SPAC) method, a technique of microtremor exploration that is widely used to infer phase velocities of Rayleigh waves using vertical-motion records from a circular array of seismic sensors. The magnitude of systematic errors (biases) that depend on the number of seismic sensors deployed around the circle, and the magnitude of systematic errors that arise from the presence of incoherent noise, are both evaluated analytically, and their general properties are discussed. The relationship between the magnitude of stochastic errors, inherent in the analysis results, and the duration of measurement (or to put it more accurately, the data's degree of freedom) is also elucidated. The validity of our theory is corroborated by checks against the results of both real data analysis and numerical experiments, and an example is given of how the theory can be adapted to account for practical situations encountered in the field. Discussions on the range of applicability of the SPAC method, which have heretofore often fallen back on empirical observations, have now obtained a theoretical ground on which to stand, providing a basis for strategies to make maximal use of the SPAC method's capabilities.

Cho, Ikuo; Tada, Taku; Shinozaki, Yuzo



XD(xanthene dyes)-DC-PVA (dichromated polyvinyl alcohol) for holographic recording: measurement of the spatial resolution and applications  

NASA Astrophysics Data System (ADS)

We report on the characterization of some photopolymer recording materials based on DC-PVA films sensitized or non- sensitized by some xanthene dyes. The limit of the spatial resolution was determined for different sample preparation techniques. It is well known that the quality of the recorded hologram depends on the spatial resolution of the recording material. A bad resolution will reduce the visibility of the reconstructed wave and damages the reconstructed image. It is therefore important to characterize the spatial resolution of the holographic recording material. In this work we compare the result obtained with two different techniques for preparing the DC- PVA plates. Interference patterns with different spatial frequencies are recorded in the material and the modulation transfer function of each pattern is measured in order to get the limit of the spatial resolution of each material. By the way each sample is characterized by the MTF curve versus spatial frequency and the end-user can choose the well- suited material for this particular application taking into account other parameters such as exposure time, intensity, etc. After the characterization of the materials we test their ability for some applications.

Cornelissen, Thierry; De Veuster, Christophe; Couture, Jean J.; Renotte, Yvon L. M.; Lion, Yves F.



Graph OLAP: a multi-dimensional framework for graph data analysis  

Microsoft Academic Search

Databases and data warehouse systems have been evolving from handling normalized spreadsheets stored in relational databases,\\u000a to managing and analyzing diverse application-oriented data with complex interconnecting structures. Responding to this emerging\\u000a trend, graphs have been growing rapidly and showing their critical importance in many applications, such as the analysis of\\u000a XML, social networks, Web, biological data, multimedia data and spatiotemporal

Chen Chen; Xifeng Yan; Feida Zhu; Jiawei Han; Philip S. Yu



Using Geo-Spatial Technologies for Field Applications in Higher Geography Education  

ERIC Educational Resources Information Center

Today's important geo-spatial technologies, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Google Earth have been widely used in geography education. Transferring spatially oriented data taken by GPS to the GIS and Google Earth has provided great benefits in terms of showing the usage of spatial technologies for field…

Karatepe, Akif



Growth and Characterization of Chalcogenide Alloy Nanowires with Controlled Spatial Composition Variation for Optoelectronic Applications  

NASA Astrophysics Data System (ADS)

The energy band gap of a semiconductor material critically influences the operating wavelength of an optoelectronic device. Realization of any desired band gap, or even spatially graded band gaps, is important for applications such as lasers, light-emitting diodes (LEDs), solar cells, and detectors. Compared to thin films, nanowires offer greater flexibility for achieving a variety of alloy compositions. Furthermore, the nanowire geometry permits simultaneous incorporation of a wide range of compositions on a single substrate. Such controllable alloy composition variation can be realized either within an individual nanowire or between distinct nanowires across a substrate. This dissertation explores the control of spatial composition variation in ternary alloy nanowires. Nanowires were grown by the vapor-liquid-solid (VLS) mechanism using chemical vapor deposition (CVD). The gas-phase supersaturation was considered in order to optimize the deposition morphology. Composition and structure were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy (EDS), and x-ray diffraction (XRD). Optical properties were investigated through photoluminescence (PL) measurements. The chalcogenides selected as alloy endpoints were lead sulfide (PbS), cadmium sulfide (CdS), and cadmium selenide (CdSe). Three growth modes of PbS were identified, which included contributions from spontaneously generated catalyst. The resulting wires were found capable of lasing with wavelengths over 4000 nm, representing the longest known wavelength from a sub-wavelength wire. For CdxPb1-xS nanowires, it was established that the cooling process significantly affects the alloy composition and structure. Quenching was critical to retain metastable alloys with x up to 0.14, representing a new composition in nanowire form. Alternatively, gradual cooling caused phase segregation, which created heterostructures with light emission in both the visible and mid-infrared regimes. The CdSSe alloy system was fully explored for spatial composition variation. CdSxSe1-x nanowires were grown with composition variation across the substrate. Subsequent contact printing preserved the designed composition gradient and led to the demonstration of a variable wavelength photodetector device. CdSSe axial heterostructure nanowires were also achieved. The growth process involved many variables, including a deliberate and controllable change in substrate temperature. As a result, both red and green light emission was detected from single nanowires.

Nichols, Patricia


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

NASA Technical Reports Server (NTRS)

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.

Efron, Uzi (editor)



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

NASA Astrophysics Data System (ADS)

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.

Efron, Uzi


Advanced strategies for spatially resolved analyte mapping with distributed fiber optic sensors for environmental and process applications  

NASA Astrophysics Data System (ADS)

The evolution of approaches to simultaneous real-time acquisition of analytical data from multiple locations is analyzed. Greatest emphasis is placed on optical time-of- flight (OTOF) chemical detection when the measurements are taken along the length of a single continuous extended-length 'distributed' sensing element. The attractive features of such distributed sensing element fabricated by immobilization of chemically sensitive reagents directly into the original cladding of a conventional plastic-clad silica (PCS) optical fiber are demonstrated. Several signal generation and processing methods are devised to address the requirements for spatially resolved chemical sensing. These requirements include high signal levels, a fairly uniform detection limit over the length of the sensing fiber, measurements with dynamically quenched fluorophores, and high spatial resolution. Applications of OTOF distributed chemical sensors for spatially resolved analyte mapping for environmental and process applications are discussed.

Potyrailo, Radislav A.; Hieftje, Gary M.



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

NASA Astrophysics Data System (ADS)

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.

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



A spatially distributed energy balance snowmelt model for application in mountain basins  

USGS Publications Warehouse

Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.

Marks, D.; Domingo, J.; Susong, D.; Link, T.; Garen, D.



Large-Time Spatial Covariance of Concentration of Conservative Solute and Application to the Cape Cod Tracer Test  

Microsoft Academic Search

Most studies on conservative transport in stationary velocity fields have focused on the description of the concentration mean. In this work, we use a Lagrangian methodology to develop an analytical expression for the spatial covariance of the concentration, based on the central limit theorem and applicable to large times after injection. We use this expression to analyze the conservative tracer

Marilena Pannone; Peter K. Kitanidis




EPA Science Inventory

The Automated Geospatial Watershed Assessment (AGWA) tool is a desktop application that uses widely available standardized spatial datasets to derive inputs for multi-scale hydrologic models (Miller et al., 2007). The required data sets include topography (DEM data), soils, clima...


Model Driven Approach for Accessing Distributed Spatial Data Using Web Services - Demonstrated for Cross-Border GIS Applications  

Microsoft Academic Search

SUMMARY The paper addresses current research issues in the field of interoperability of heterogeneous GI systems. Special emphasis is placed on heterogeneity at the level of conceptual data models. This problem is discussed in the context of cross-border web-based GIS applications which involve the combination of spatial data on the same type of real world objects from different countries. Existing



Spatial variation of soil nutrients in a dairy farm and its implications for site-specific fertilizer application  

Microsoft Academic Search

The spatial variation of extractable (Morgan's) soil phosphorus (P), potassium (K), magnesium (Mg), pH and lime requirement (LR) in a permanent dairy farm in southeastern Ireland, was investigated using conventional statistics, geostatistics and a geographical information system (GIS) to produce nutrient maps and to provide information for site-specific fertilizer application. A total of 537 soil samples were collected based on

Weijun Fu; Hubert Tunney; Chaosheng Zhang



Relative Prefix Sums: An Efficient Approach for Querying Dynamic OLAP Data Cubes  

Microsoft Academic Search

Range sum queries on data cubes are a powerful tool for analysis. A range sum query applies an aggregation operation (e.g., SUM) over all selected cells in a data cube, where the selection is specified by providing ranges of values for numeric dimensions. Many application domains require that information provided by analysis tools be current or \\

Steven Geffner; Divyakant Agrawal; Amr El Abbadi; Terence R. Smith



Application of Spatial Continuous Wavelet Transforms to Identify Noise in Regional Airborne Electromagnetic Data  

NASA Astrophysics Data System (ADS)

As mapping of groundwater resources with airborne electromagnetics expands into more urban areas, it is increasingly important to identify sources of cultural noise in acquired data sets. A number of methods have been proposed to reduce the impact of cultural coupling on acquired data. While intense local calibration to increase the signal to noise ratio has been used, most often in practice, the transients associated with these noise sources are manually identified and filtered out during data processing. This can be a challenging task, particularly as datasets grow large (e.g. up to terabytes of data). In response to this, we propose a method for identifying noise in airborne electromagnetic data based on a spatial application of the continuous wavelet transform (CWT). We apply a continuous wavelet transform to three airborne electromagnetic surveys collected in the Edmonton-Calgary Corridor as part of a groundwater inventory sponsored by the Alberta Geological Survey and Environment Alberta. The three surveys consist of 210 flightlines covering approximately 18 000 linear kilometers with roughly 13 m sounding spacing. B-field and dB/dt data from a three-component 20-channel GeoTEM multicoil system, were recorded at 5 on-time and 15 off-time channels with a total measurement time of 16.664 ms per sounding. The nominal height of vertical axis transmitter was 120 m; the current pulse was 670 A, and the pulse-width was 4.045 ms. Wavelet transforms are localized in time and frequency, similar to a windowed Fourier transform, and are used to identify dominant frequencies within a signal as a function of time or space. While there are a number of options for wavelet functions, we convolve a Morlet wavelet with the data signal at 120 distance scales on a logarithmic scale from 0.1 to 30 km. We calculate the CWT along each flightline for all off-time channels. We then calculate the wavelet power normalized by the data variance, and bin results into 4 bins of spatial scales: 1:4 km, 4:9 km, 9:15 km, and 15:30 km. The average normalized power within a scale bin for each sounding and time-channel are combined into four 2D maps. The maps show similar results over several time-channels, which allows us to average results in three time bins: early- (channels 6-12), mid- (channels 13-16), and late-time (channels 17-20). The B-field and dB/dt power maps contain highly linear and angular features that manifest differently in the two data sets and do not correlate with subsurface structure. Comparison of power maps from the two data types suggests that cultural noise is most prevalent at short spatial scales, which is consistent with the finite spatial continuity of infrastructure, and at late-time, when geologic signals are weakest and the signal to noise ratio is smallest. We conclude from these results that a CWT approach can be used to identify areas in which cultural noise impacts collected data. Future work is required to assess the magnitude of this impact and to filter the signals from cultural noise from the data.

Nenna, V.; Pidlisecky, A.



Foreground Segmentation in Depth Imagery Using Depth and Spatial Dynamic Models for Video Surveillance Applications  

PubMed Central

Low-cost systems that can obtain a high-quality foreground segmentation almost independently of the existing illumination conditions for indoor environments are very desirable, especially for security and surveillance applications. In this paper, a novel foreground segmentation algorithm that uses only a Kinect depth sensor is proposed to satisfy the aforementioned system characteristics. This is achieved by combining a mixture of Gaussians-based background subtraction algorithm with a new Bayesian network that robustly predicts the foreground/background regions between consecutive time steps. The Bayesian network explicitly exploits the intrinsic characteristics of the depth data by means of two dynamic models that estimate the spatial and depth evolution of the foreground/background regions. The most remarkable contribution is the depth-based dynamic model that predicts the changes in the foreground depth distribution between consecutive time steps. This is a key difference with regard to visible imagery, where the color/gray distribution of the foreground is typically assumed to be constant. Experiments carried out on two different depth-based databases demonstrate that the proposed combination of algorithms is able to obtain a more accurate segmentation of the foreground/background than other state-of-the art approaches.

del-Blanco, Carlos R.; Mantecon, Tomas; Camplani, Massimo; Jaureguizar, Fernando; Salgado, Luis; Garcia, Narciso



Design and Development of an Open Source Software Application for the Characterization of Spatially Variable Fields  

NASA Astrophysics Data System (ADS)

The characterization of the structural parameters of spatially variable fields (SVFs) is essential to understanding the variability of hydrological processes such as infiltration, evapotranspiration, groundwater contaminant transport, etc. SVFs can be characterized using a Bayesian inverse method called Method of Anchored Distributions (MAD). This method characterizes the structural parameters of SVFs using prior information of structural parameter fields, indirect measurements, and simulation models allowing the transfer of valuable information to a target variable field. An example SVF in hydrology is hydraulic conductivity, which may be characterized by head pressure measurements through a simulation model such as MODFLOW. This poster will present the design and development of a free and open source inverse modeling desktop software application and extension framework called MAD# for the characterization of the structural parameters of SVFs using MAD. The developed software is designed with a flexible architecture to support different simulation models and random field generators and includes geographic information system (GIS) interfaces for representing, analyzing, and understanding SVFs. This framework has also been made compatible with Mono, a cross-platform implementation of C#, for a wider usability.

Gunnell, D. K.; Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.



Classifying spatial patterns of brain activity with machine learning methods: application to lie detection.  


Patterns of brain activity during deception have recently been characterized with fMRI on the multi-subject average group level. The clinical value of fMRI in lie detection will be determined by the ability to detect deception in individual subjects, rather than group averages. High-dimensional non-linear pattern classification methods applied to functional magnetic resonance (fMRI) images were used to discriminate between the spatial patterns of brain activity associated with lie and truth. In 22 participants performing a forced-choice deception task, 99% of the true and false responses were discriminated correctly. Predictive accuracy, assessed by cross-validation in participants not included in training, was 88%. The results demonstrate the potential of non-linear machine learning techniques in lie detection and other possible clinical applications of fMRI in individual subjects, and indicate that accurate clinical tests could be based on measurements of brain function with fMRI. PMID:16169252

Davatzikos, C; Ruparel, K; Fan, Y; Shen, D G; Acharyya, M; Loughead, J W; Gur, R C; Langleben, D D



Optimization and Application of Median Filter Corrections to Relieve Diverse Spatial Patterns in Microtiter Plate Data  

PubMed Central

The standard (STD) 5 × 5 hybrid median filter (HMF) was previously described as a nonparametric local backestimator of spatially arrayed microtiter plate (MTP) data. As such, the HMF is a useful tool for mitigating global and sporadic systematic error in MTP data arrays. Presented here is the first known HMF correction of a primary screen suffering from systematic error best described as gradient vectors. Application of the STD 5 × 5 HMF to the primary screen raw data reduced background signal deviation, thereby improving the assay dynamic range and hit confirmation rate. While this HMF can correct gradient vectors, it does not properly correct periodic patterns that may present in other screening campaigns. To address this issue, 1 × 7 median and a row/column 5 × 5 hybrid median filter kernels (1 × 7 MF and RC 5 × 5 HMF) were designed ad hoc, to better fit periodic error patterns. The correction data show periodic error in simulated MTP data arrays is reduced by these alternative filter designs and that multiple corrective filters can be combined in serial operations for progressive reduction of complex error patterns in a MTP data array.

Bushway, Paul J.; Azimi, Behrad; Heynen-Genel, Susanne



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

NASA Astrophysics Data System (ADS)

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.

Chatziantoniou, Damianos; Sotiropoulos, Yannis


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

NASA Astrophysics Data System (ADS)

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 the slope. A nearest neighbour (NN) filtering technique was applied to the RAW datasets (Abellán et al., 2009), enabling the accurate detection of centimetric displacements. The parameters of the precursory deformation correlated with the failure mechanism, lithology and volume of the rockfall: higher values of length and duration of the precursory deformation were found in the toppling failure mechanism, ductile materials and rockfalls that involved considerable volumes. These results are consistent with observations in the literature regarding rockfalls of higher magnitude and lower frequency (e.g.: Zvelebil and Moser, 2001; Crosta and Agliardi, 2004; Hungr et al., 2007). It is also important to mention that no precursory indicators were detected prior to each rockfall that occurred in the study areas. This could simply be due to infrequent data acquisition or insufficient instrument accuracy. The application of TLS for the spatial prediction of rockfalls should be validated through: (a) the continuation of the TLS monitoring campaign at the areas which currently show ongoing deformation; (b) the selection of new case studies at different geomorphological sites with different lithologies; and (c) the selection of new case studies with different failure mechanisms (e.g. fall, slide). These tasks are of paramount importance to understand the pre-failure behaviour of rockfalls and to implement these findings in an early warning system.

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



Design of data warehouse in teaching state based on OLAP and data mining  

NASA Astrophysics Data System (ADS)

The data warehouse and the data mining technology is one of information technology research hot topics. At present the data warehouse and the data mining technology in aspects and so on commercial, financial industry as well as enterprise's production, market marketing obtained the widespread application, but is relatively less in educational fields' application. Over the years, the teaching and management have been accumulating large amounts of data in colleges and universities, while the data can not be effectively used, in the light of social needs of the university development and the current status of data management, the establishment of data warehouse in university state, the better use of existing data, and on the basis dealing with a higher level of disposal --data mining are particularly important. In this paper, starting from the decision-making needs design data warehouse structure of university teaching state, and then through the design structure and data extraction, loading, conversion create a data warehouse model, finally make use of association rule mining algorithm for data mining, to get effective results applied in practice. Based on the data analysis and mining, get a lot of valuable information, which can be used to guide teaching management, thereby improving the quality of teaching and promoting teaching devotion in universities and enhancing teaching infrastructure. At the same time it can provide detailed, multi-dimensional information for universities assessment and higher education research.

Zhou, Lijuan; Wu, Minhua; Li, Shuang



An Application of Brunerian Theory to Instructional Simulation: Spatial Visualization, Factorial Research Designs, and Wooden Blocks.  

ERIC Educational Resources Information Center

A study was conducted to test the hypothesis that Brunerian learning theory can provide the instructional designer with a framework for developing effective learning materials. To determine three levels of spatial ability, two standardized tests--the Spatial Visualization Test (SVT) of the Dailey Vocational Tests and part VI of the…

Winer, Laura R.


MAD: a new method for inverse modeling of spatial random fields with applications in hydrogeology  

Microsoft Academic Search

We propose the Method of Anchored Distributions (MAD) for calibrating the model of a spatial random field using both local and non-local data. Using hydraulic conductivity as an example of the spatial variable of interest, local data refer to \\

Z. Zhang; Y. Rubin



Spatial Double Generalized Beta Regression Models: Extensions and Application to Study Quality of Education in Colombia  

ERIC Educational Resources Information Center

In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we…

Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente



Spatial correlations of monthly rainfall: Applications in climatology and weather modification experiments  

Microsoft Academic Search

Spatial correlations based on monthly rainfall totals from northwest Georgia for the period 1949--77 are studied. This work, a part of the Meteorological Effects of Thermal Energy Releases (METER) Program, determines natural variability rainfall trends and assists the field studies of potential precipitation effects of the Bowen Electric Generating Plant near Cartersville, Georgia. The spatial correlations, based on the overall

A. A. N. Patrinos; N. C. J. Chen; R. L. Miller



Towards the geometric optimization of potential field models - A new spatial operator tool and applications  

NASA Astrophysics Data System (ADS)

We present a new method for automated geometric modifications of potential field models. Computational developments and the increasing amount of available potential field data, especially gradient data from the satellite missions, lead to increasingly complex models and integrated modelling tools. Editing of these models becomes more difficult. Our approach presents an optimization tool that is designed to modify vertex-based model geometries (e.g. polygons, polyhedrons, triangulated surfaces) by applying spatial operators to the model that use an adaptive, on-the-fly model discretization. These operators deform the existing model via vertex-dragging, aiming at a minimized misfit between measured and modelled potential field anomaly. The parameters that define the operators are subject to an optimization process. This kind of parametrization provides a means for the reduction of unknowns (dimensionality of the search space), allows a variety of possible modifications and ensures that geometries are not destroyed by crossing polygon lines or punctured planes. We implemented a particle swarm optimization as a global searcher with restart option for the task of finding optimal operator parameters. This approach provides us with an ensemble of model solutions that allows a selection and geologically reasonable interpretations. The applicability of the tool is demonstrated in two 2D case studies that provide models of different extent and with different objectives. The first model is a synthetic salt structure in a horizontally layered background model. Expected geometry modifications are considerably small and localized and the initial models contain rather little information on the intended salt structure. A large scale example is given in the second study. Here, the optimization is applied to a sedimentary basin model that is based on seismic interpretation. With the aim to evaluate the seismically derived model, large scale operators are applied that mainly cause depth adjustments to the model horizons.

Haase, Claudia; Götze, Hans-Jürgen



Application of Data Fusion in the Production and Updating of Spatial Data  

NASA Astrophysics Data System (ADS)

The increasing spatial data provide abundant material for data fusion, and the purpose of the paper is to apply data fusion into the production and updating of spatial data. After outlining the general framework and workflow, the processing contents and methods are specified in sequence. Facing various spatial data from different sources, how to design proper data fusion scheme is the toppriority problem. The method of analyzing and assessing various spatial data is introduced referring to images, which is shown by concrete examples. Then the technical workflow of multi-source data integration is present to eliminate differences and relevant contents are also specified. After building the relationships of homologous entities through spatial data matching, the data fusion which is similar to cartographic generalization in essence can be implemented. Different ways of updating spatial data is introduced to keep the currency of existing data. At last, the spatial data with good quality can be obtained. The efficient and reliability of the methodology in this paper has been proved through practical production.

Chen, H.; Sun, Q.; Xu, L.; Xiong, Z.



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

NASA Technical Reports Server (NTRS)

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

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



Application of spatial Poisson process models to air mass thunderstorm rainfall  

NASA Technical Reports Server (NTRS)

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.




EPA Science Inventory

Ecological systems are generally considered among the most complex because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. Hierarchy theory, as well as empirical evidence, suggests that comp...


Optimum and applications of photorefractive spatial light modulator in optical pattern recognition  

NASA Astrophysics Data System (ADS)

With excellent physical properties the photorefractive crystals, such as BSO (Bi12SiO20), BaTiO3 and GaAs materials, have, can be widely used in optical correlator to implement auto pattern recognition. As the basic devices in optical correlator, the properties of optically-addressed spatial light modulator are very important. By analyzing the dynamic process of the BSO spatial light modulator, especially the changes of the read-out light while in writing under various operation modes, the distinctness between various operation modes is summarize. Furthermore, considered with the photo-induced current pulses, the method to optimize the BSO spatial light modulator is proposed. The BSO spatial light modulator working in optimum operation mode is used to design a optical correlator to implement auto pattern recognition.

Li, Xiujian; Hu, Wenhua; Jia, Hui; Yang, Jiankun; Yang, Yisheng; Guo, Shaofeng



Bayesian Parametric Accelerated Failure Time Spatial Model and its Application to Prostate Cancer  

PubMed Central

Prostate cancer is the most common cancer diagnosed in American men and the second leading cause of death from malignancies. There are large geographical variation and racial disparities existing in the survival rate of prostate cancer. Much work on the spatial survival model is based on the proportional hazards model, but few focused on the accelerated failure time model. In this paper, we investigate the prostate cancer data of Louisiana from the SEER program and the violation of the proportional hazards assumption suggests the spatial survival model based on the accelerated failure time model is more appropriate for this data set. To account for the possible extra-variation, we consider spatially-referenced independent or dependent spatial structures. The deviance information criterion (DIC) is used to select a best fitting model within the Bayesian frame work. The results from our study indicate that age, race, stage and geographical distribution are significant in evaluating prostate cancer survival.

Zhang, Jiajia; Lawson, Andrew B.



Robust and Optimal Control of Spatially Interconnected Systems, With Application to Coordinated Vehicle Control.  

National Technical Information Service (NTIS)

The research supported by this grant consisted of developing improved algorithms and theory for designing and analyzing robust control systems for spatially interconnected systems. There are many examples of such systems, including automated highway syste...

R. D'Andrea



Biased photovoltaic spatial solitons and their application in nonlinear guided waves  

NASA Astrophysics Data System (ADS)

We study theoretically the properties of waveguides induced by one-dimensional steady-state biased photovoltaic spatial solitons, and show that the waveguides can be induced by both bright and dark spatial solitons in the biased photovoltaic- photorefractive crystal such as LiNbO3. We also derive wave equations for the probe beam in the general condition and low-amplitude condition.

Liu, Jinsong



Application of GIS for the modeling of spatial distribution of air pollutants in Tehran  

NASA Astrophysics Data System (ADS)

Spatial modeling of air pollutants in the mega cities such as Tehran is a useful method for the estimation of pollutants in the non-observed positions in Tehran. In addition, spatial modeling can determine the level of pollutants in different regions of Tehran. There are some typical interpolation techniques (e.g., Inverse Distance Weighting (IDW), Thin Plate Splines (TPS), Kriging and Cokriging) for spatial modeling of air pollutants. In this study, different interpolation methods are compared for spatial modeling of carbon monoxide in Tehran. The three-hourly data of wind speed and direction was received from 5 meteorological stations in Tehran. The hourly data of carbon monoxide in 2008 have been extracted of 16 air pollution monitoring stations in Tehran. The hourly data of 3 selected days in 2008 (72 hours) and similarly, the daily data of 36 days in 2008 (3 days in each month) were utilized for spatial modeling in this study. Different typical interpolation techniques were implemented on different hourly and daily data using ArcGIS. The percent of absolute error of each interpolation techniques for each hourly and daily interpolated data was calculated using cross validation techniques. Results demonstrated that Cokriging has better performance than other typical interpolation techniques in the hourly and daily modeling of carbon monoxide. Because it utilizes three input variables (Latitude, Longitude and altitude) data for spatial modeling but the other methods use only two input variables (Latitude and Longitude). In addition, the wind speed and direction maps were compatible with the results of spatial modeling of carbon monoxide. Kriging was the appropriate method after Cokriging.

Sargazi, Saeed; Taheri Shahraiyni, Hamid; Habibi-Nokhandan, Majid; Sanaeifar, Melika



Application of Spatial Modelling Approaches, Sampling Strategies and 3s Technology Within AN Ecolgocial Framwork  

NASA Astrophysics Data System (ADS)

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.

Chen, H.-C.; Lo, N.-J.; Chang, W.-I.; Huang, K.-Y.



Bayesian Modeling of Multivariate Spatial Binary Data with applications to Dental Caries  

PubMed Central

SUMMARY Dental research gives rise to data with potentially complex correlation structure. Assessments of dental caries yields a binary outcome indicating the presence or absence of caries experience for each surface of each tooth in a subject’s mouth. In addition to this nesting, caries outcome exhibit spatial structure among neighboring teeth. We develop a Bayesian multivariate model for spatial binary data using random effects autologistic regression that controls for the correlation within tooth surfaces and spatial correlation among neighboring teeth. Using a sample from a clinical study conducted at the Medical University of South Carolina, we compare this autologistic model with covariates to alternative models to demonstrate the improvement in predictions and also to assess the effects of covariates on caries experience.

Bandyopadhyay, Dipankar; Reich, Brian J.; Slate, Elizabeth



Unsupervised soil drainage classification and mapping through the application of spatial and nonspatial methods  

NASA Astrophysics Data System (ADS)

The accuracy of a soil map is strongly related to the level of spatial precision of its mapped properties, such as soil drainage quality, which are increasingly needed for effective soil and water management plan implementations in agriculture and natural resource management. Multivariate logistic regression analysis, geostatistics, and GIS were applied to the SSURGO soil survey data (NRCS) and continuous data (DEM) properties to classify soil drainage for Albany County, Wyoming, USA. The objectives of this study were to: (i) compare spatial soil models to nonspatial drainage classification models, (ii) determine the effects of categorical and measured soil properties on soil drainage classes, and (iii) build valid, precise, and reliable soil-landscape models for the soil drainage classification. Geomorphology, soil hydrological, chemical and physical properties, and soil erosion indices were the major predictors of soil drainage. The correct classification accuracy ranged from 57 to 99%, from 92 to 99%, and from 91 to 92% for the spatial, nonspatial, and DEM-based models, respectively. The correct classification accuracy of the interaction models were between 71 and 91%, and 95 and 97% for the spatial and nonspatial models, respectively. The narrowest confidence interval (CI, 95%) was found by the soil horizon properties, indicating the models precision and validity. Spatial models were always superior with higher chi-squares to the nonspatial models. The results showed that combined use of soil survey data and DEM can result in more accurate and precise spatial soil maps and potential need for soil drainage can be determined with this mapping method in the basin.

Akis, Rifat


An annual variation analysis of the ionospheric spatial gradient over a regional area for GNSS applications  

NASA Astrophysics Data System (ADS)

An ionospheric spatial gradient represents the ionosphere delay difference between different locations, and its variation over a specific area is important for implementing differential GNSS systems. An estimation method for the ionospheric spatial gradient over a small regional area is proposed. A plate map model is implemented for the direct estimation of the gradients. Nine years of GPS data were processed to figure out the annual variation of the mean gradient at the mid-geomagnetic latitude of 30° N. Gradients along the north-south direction have a mean of 0.65 mm/km and follow solar-cycle variations.

Kim, Jeongrae; Lee, Seung Woo; Lee, Hyung Keun



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

NASA Astrophysics Data System (ADS)

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

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



Development and application of a spatially-distributed Arctic hydrological and thermal process model (ARHYTHM)  

Microsoft Academic Search

A process-based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including

Ziya Zhang; Douglas L. Kane; Larry D. Hinzman



A spatial cognition-based urban building clustering approach and its applications  

Microsoft Academic Search

This article presents a spatial cognition analysis technique for automated urban building clustering based on urban morphology and Gestalt theory. The proximity graph is selected to present the urban mrphology. The proximity graph considers the local adjacency among buildings, providing a large degree of freedom in object displacement and aggregation. Then, three principles of Gestalt theories, proximity, similarity, and common

Zhang Liqiang; Deng Hao; Chen Dong; Wang Zhen



Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs substrates  

Microsoft Academic Search

The fabrication and characterization of an optically addressable deformable mirror for a spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5 mum thick grid of patterned photoresist supports the 2 mum thick aluminized Mylar membrane. A conductive ZnO layer is placed on the

Bahareh Haji-Saeed; Rathna Kolluru; Dana Pyburn; Roberto Leon; Sandip K. Sengupta; Markus Testorf; William Goodhue; Jed Khoury; Alvin Drehman; Charles L. Woods; John Kierstead



An application of spatial decision tree for classification of air pollution index  

Microsoft Academic Search

A decision tree is an analysis skill and a classification algorithm, whose basic principle is the combination of probability theory and an analysis tool of tree shapes. It derives a hierarchy of partition rules with respect to a target attribute of a large dataset. Nowadays, concrete coordinates exist in lots of datasets, which leads to the spatial distribution of datasets.

Minyue Zhao; Xiang Li



Applications of geographical information systems (GIS) for spatial decision support in aquaculture  

Microsoft Academic Search

Geographical information systems (GIS) are becoming an increasingly integral component of natural resource management activities worldwide. However, despite some indication that these tools are receiving attention within the aquaculture community, their deployment for spatial decision support in this domain continues to be very slow. This situation is attributable to a number of constraints including a lack of appreciation of the

Shree S. Nath; John P. Bolte; Lindsay G. Ross; Jose Aguilar-Manjarrez



Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling.  


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. PMID:22457575

Brakebill, Jw; Wolock, Dm; Terziotti, Se



Bistability and nonlinearity in optically addressed ferroelectric liquid-crystal spatial light modulators: applications to neurocomputing.  


We report the characteristics of a truly bistable optically addressed ferroelectric liquid-crystal spatial light modulator that is capable of storing binary images. We show that, in addition to this bistability, a nonlinear response and gray scales can be observed under certain operating conditions. We then report on how these capabilities can be used in implementing optical neurocomputing architectures. PMID:20725369

Killinger, M; de Bougrenet de la Tocnaye, J L; Cambon, P; Chittick, R C; Crossland, W A



Preliminary Study on the Application of OGC Interoperability Specifications in Spatial Information Grid  

Microsoft Academic Search

The sharing and interoperability of geospatial data are important issues for spatial information grid (SIG). Based on an existing SIG platform, we tentatively propose a three-level overview SIG layout. Within this new architecture, some grid service entities (GSEs) complying with Open GIS Consortium (OGC) interoperability specifications, such as Web Map Service (WMS), Web Feature Service and Web Coverage Service, are

Fang Huang; Dingsheng Liu; Guoqing Li; Jian Wang



Robust generation, properties and potential applications of quadratic spatial solitons generated by optical parametric amplification  

Microsoft Academic Search

Quadratic spatial solitary waves are predicted and observed experimentally near degeneracy for Type II optical parametric amplification in bulk KTP, by seeding an intense pump optical field with a control signal at half the pump wave frequency. The self-trapping of light at the two wavelengths has been shown to be insensitive to phase, polarization and magnitude of the control input,

R. A. Fuerst; M. T. G. Canva; G. I. Stegeman; G. Leo; G. Assanto



Support-Based Implementation of Bayesian Data Fusion for Spatial Enhancement: Applications to ASTER Thermal Images  

Microsoft Academic Search

In this letter, a general Bayesian data fusion (BDF) approach is proposed and applied to the spatial enhancement of ASTER thermal images. This method fuses information coming from the visible or near-infrared bands (15 times 15 m pixels) with the thermal infrared bands (90 times 90 m pixels) by explicitly accounting for the change of support. By relying on linear

Dominique Fasbender; Devis Tuia; Patrick Bogaert; Mikhail Kanevski



Spatial Growth of Informal Settlements in Delhi; An Application of Remote Sensing  

NASA Astrophysics Data System (ADS)

Slum development and growth is quite popular in developing countries. Many studies have been done on what social and economic factors are the drivers in establishment of informal settlements at a single cross-section of time, however limited work has been done in studying their spatial growth patterns over time. This study attempts to study a sample of 30 informal settlements that exist in the National Capital Territory of India over a period of 40 years and identify relationships between the spatial growth rates and relevant factors identified in previous socio-economic studies of slums using advanced statistical methods. One of the key contributions of this paper is indicating the usefulness of satellite imagery or remote sensing data in spatial-longitudinal studies. This research utilizes readily available LANDSAT images to recognize the decadal spatial growth from 1970 to 2000, and also in extension, calculate the BI (transformed NDVI) as a proxy for the intensity of development for the settlements. A series of regression models were run after processing the data, and the levels of significance were then studied and compared to see which relationships indicated the highest levels of significance. It was observed that the change in BI had a higher strength of relationships with the change in independent variables than the settlement area growth. Also, logarithmic and cubic models showed the highest R-Square values than any other tested models.

Prakash, Mihir


A new spatial prediction model and its application to wind records  

Microsoft Academic Search

Summary Contour maps of any meteorological variable cannot give radius or area of influences around the measurement station by considering the records at surrounding sites. The main purpose of this paper is to propose a trigonometric point cumulative semivariogram (TPCSV) concept for deciding on a spatial dependence function and then its use for regional prediction. The TPCSV provides a unique

A. D. ?ahin; Z. ?en



SpPack: spatial point pattern analysis in Excel using Visual Basic for Applications (VBA)  

Microsoft Academic Search

Many different sciences have developed many different tests to describe and characterise spatial point data. For example, all the trees in a given area may be mapped such that their x, y co-ordinates and other variables, or ‘marks’, (e.g. species, size) might be recorded. Statistical techniques can be used to explore interactions between events at different length scales and interactions

George L. W. Perry



Spatial variation of earthquake ground motion for application to soil-structure interaction  

SciTech Connect

The spatial variation of strong ground motion from fifteen earthquakes recorded by the Lotung LSST strong motion array is analyzed. The earthquakes range in magnitude from 3.7 to 7.8 and in source distance from 4 to 80 km. In all a total of 533 station pairs are used with station separations ranging from 60 to 85 meters. The spatial variation of ground motion is divided into two parts: variation in the fourier phase (coherence), and variation in the Fourier amplitude. Empirical functions describing the frequency and separation distance dependence of the coherency and amplitude variation appropriate for use in engineering analyses are derived. Taken together, the spatial variation functions given in this study provide a complete description of the statistical properties of the horizontal components of the seismic wavefield assuming plane wave propagation for the S-wave window. Since the S-waves generally cause the largest shaking, these spatial variation functions are appropriate for use in engineering analyses of large structures.

Abrahamson, N. (Bechtel Civil, Inc., San Francisco, CA (United States))



Field Description with Spatial and its Application to Complex Variables Scattering and Waveguide Problems  

Microsoft Academic Search

The field description with spatial complex variables is proposed. The complex variables z, _z are chosen, where z= x+iy and _z is the complex conjugate. A contour integral in a complex plane is and the residue theorem is applied. The variables are changed by a transforming (mapping) function. The field description is applied to the boundary-value problems with arbitrary boundary.

M. Hashimoto; K. Fujisawa



Novel spatial analysis method for PET images using 3D moment invariants: applications to Parkinson's disease.  


We present a novel analysis method for positron emission tomography (PET) data that uses the spatial characteristics of the radiotracer's distribution within anatomically-defined regions of interest (ROIs) to provide an independent feature that may aid in characterizing pathological and normal states. The analysis of PET data for research purposes traditionally involves kinetic modeling of the concentration of the radiotracer over time within a ROI to derive parameters related to the uptake/binding of the radiotracer in the body. Here we describe an analysis method to quantify the spatial changes present in PET images based on 3D shape descriptors that are invariant to translation, scaling, and rotation, called 3D moment invariants (3DMIs). An ROI can therefore be characterized not only by the radiotracer's uptake rate constant or binding potential within the ROI, but also the 3D spatial shape and distribution of the radioactivity throughout the ROI. This is particularly relevant in Parkinson's disease (PD), where both the kinetic and the spatial distribution of the tracer are known to change due to disease: the posterior parts of the striatum (in particular in the putamen) are affected before the anterior parts. Here we show that 3DMIs are able to quantify the spatial distribution of PET radiotracer images allowing for discrimination between healthy controls and PD subjects. More importantly, 3DMIs are found to be well correlated with subjects' scores on the United Parkinson's Disease Rating Scale (a clinical measure of disease severity) in all anatomical regions studied here (putamen, caudate and ventral striatum). On the other hand, kinetic parameters only show significant correlation to clinically-assessed PD severity in the putamen. We also find that 3DMI-characterized changes in spatial patterns of dopamine release in response to l-dopa medication are significantly correlated with PD severity. These findings suggest that quantitative studies of a radiotracer's spatial distribution may provide complementary information to kinetic modeling that is relatively robust to intersubject variability and may contribute novel information in PET neuroimaging studies. PMID:23246861

Gonzalez, Marjorie E; Dinelle, Katherine; Vafai, Nasim; Heffernan, Nicole; McKenzie, Jess; Appel-Cresswell, Silke; McKeown, Martin J; Stoessl, A Jon; Sossi, Vesna



Efficient sampling for spatial uncertainty qualification in multibody system dynamics applications.  

SciTech Connect

We present two methods for efficiently sampling the response (trajectory space) of multibody systems operating under spatial uncertainty, when the latter is assumed to be representable with Gaussian processes. In this case, the dynamics (time evolution) of the multibody systems depends on spatially indexed uncertain parameters that span infinite-dimensional spaces. This places a heavy computational burden on existing methodologies, an issue addressed herein with two new conditional sampling approaches. When a single instance of the uncertainty is needed in the entire domain, we use a fast Fourier transform technique. When the initial conditions are fixed and the path distribution of the dynamical system is relatively narrow, we use an incremental sampling approach that is fast and has a small memory footprint. Both methods produce the same distributions as the widely used Cholesky-based approaches. We illustrate this convergence at a smaller computational effort and memory cost for a simple non-linear vehicle model.

Schmitt, K.; Anitescu, M.; Negrut, D.; Mathematics and Computer Science; Univ. of Wisconsin



Shear-modulus estimation by application of spatially-modulated impulsive acoustic radiation force.  


We present a method for determining the shear modulus of an elastic material wherein a spatially-modulated acoustic radiation force is used to generate a disturbance of known spatial frequency (wavelength). The propagation of this initial displacement as a shear wave is measured using ultrasound tracking methods and the temporal frequency of the shear wave is estimated. Given the known wavelength and material density and the measured estimate of temporal frequency, the shear modulus at the point of excitation may be calculated easily. Using this method, the shear moduli of two gelatin phantoms was estimated to be 1.4 and 5.8 kPa, in good agreement with 1.5 and 5.6 kPa values determined though quasistatic material testing. PMID:17679324

McAleavey, Stephen A; Menon, Manoj; Orszulak, Jarrod



Fine estimators of two-dimensional parameters and application to spatial shift estimation  

Microsoft Academic Search

This paper presents a fast technique for fine estimation of two-dimensional (2-D) parameters, based on a parabolic interpolation of the same ambiguity function samples, and aimed at block-oriented estimation of the spatial shift between pairs of images in video sequences. Expressions for the bias and variance of the position error and the prediction error are derived. The method is tested

Gaetano Giunta



Application and evaluation of a measured spatially variant system model for PET image reconstruction.  


Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy. System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. The purpose of this work is to improve clinical fully-3-D reconstruction without substantially increasing computation time. We present a practical method for measuring the detector blurring component of a whole-body positron emission tomography (PET) system to form an approximate system model for use with fully-3-D reconstruction. We employ Monte Carlo simulations to show that a non-collimated point source is acceptable for modeling the radial blurring present in a PET tomograph and we justify the use of a Na22 point source for collecting these measurements. We measure the system response on a whole-body scanner, simplify it to a 2-D function, and incorporate a parameterized version of this response into a modified fully-3-D OSEM algorithm. Empirical testing of the signal versus noise benefits reveal roughly a 15% improvement in spatial resolution and 10% improvement in contrast at matched image noise levels. Convergence analysis demonstrates improved resolution and contrast versus noise properties can be achieved with the proposed method with similar computation time as the conventional approach. Comparison of the measured spatially variant and invariant reconstruction revealed similar performance with conventional image metrics. Edge artifacts, which are a common artifact of resolution-modeled reconstruction methods, were less apparent in the spatially variant method than in the invariant method. With the proposed and other resolution-modeled reconstruction methods, edge artifacts need to be studied in more detail to determine the optimal tradeoff of resolution/contrast enhancement and edge fidelity. PMID:20199927

Alessio, Adam M; Stearns, Charles W; Tong, Shan; Ross, Steven G; Kohlmyer, Steve; Ganin, Alex; Kinahan, Paul E



Local and Spatial Joint Frequency Uncertainty and its Application to Rock Mass Characterisation  

Microsoft Academic Search

Stability is a key issue in any mining or tunnelling activity. Joint frequency constitutes an important input into stability\\u000a analyses. Three techniques are used herein to quantify the local and spatial joint frequency uncertainty, or possible joint\\u000a frequencies given joint frequency data, at unsampled locations. Rock quality designation is estimated from the predicted joint\\u000a frequencies. The first method is based

Steinar L. Ellefmo; Jo Eidsvik



Application potential of differential SAR interferometry in land subsidence spatial-temporal data capturing  

Microsoft Academic Search

Three Differential Synthetic Aperture Radar Interferometry (D-InSAR) methods are compared on the capability of obtaining land subsidence temporal data. These three methods including, Interferograms time-series stacking, Permanent Scatters D-InSAR(PS-InSAR) and Multi-Baseline D-InSAR are all base on interferometry phase spatial-temporal analysis to increase reliability. They are used to extract land subsidence mean velocity from time serial SAR images in nearly two

Zhaoquan Huang; Le Yu; Fan Wang



Spatial rule-based modeling: a method and its application to the human mitotic kinetochore.  


A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models. PMID:24709796

Ibrahim, Bashar; Henze, Richard; Gruenert, Gerd; Egbert, Matthew; Huwald, Jan; Dittrich, Peter



MAD: a new method for inverse modeling of spatial random fields with applications in hydrogeology  

NASA Astrophysics Data System (ADS)

We propose the Method of Anchored Distributions (MAD) for calibrating the model of a spatial random field using both local and non-local data. Using hydraulic conductivity as an example of the spatial variable of interest, local data refer to "point" measurements of conductivity or covariates that provide "point" conductivity, whereas non-local data refer to observations of a process that rely on the conductivity field. The proposed method is a general, Bayesian statistical framework. Main features include: (1) the parameterization of the spatial random field is versatile; (2) a systematic classification of all relevant data permits systematic treatment of individual datasets according to their category, making the framework very general; (3) no assumptions are made on the non-local process (a.k.a forward model), e.g. roughly linear, or small variance; (4) the result by construction provides conditional simulations of the field, i.e., by randomly sampling a distribution conditional on the data, as opposed to optimization in order to "match" the data. We will illustrate the method by synthetic examples.

Zhang, Z.; Rubin, Y.



Investigating spatial climate relations using CARTs: An application to persistent hot days in a multimodel ensemble  

NASA Astrophysics Data System (ADS)

This study introduces Classification and Regression Trees (CARTs) as a new tool to explore spatial relationships between different climate patterns in a multimodel ensemble. We demonstrate the potential of CARTs by a simple case study based on time-aggregated patterns of circulation (represented by average levels and variabilities of sea level pressure, SLP) and land surface conditions (diagnosed from the time-averaged surface water balance) from regional climate model simulations (ENSEMBLES) over Europe. These patterns are systematically screened for their relevance to the spatial distribution of persistent hot days. Present-day (ERA40) and future (A1B) climate conditions are analyzed. A CART analysis of the ERA40 reanalysis complements the results for the present-day simulations. In many models, long persistent hot days concur with low variabilities of SLP and high water balance deficits both in present and future. However, for the change patterns (A1B minus ERA40) the analysis indicates that the most robust feature is the link between aggravating persistent hot days and increasing surface water deficits. These results highlight that the factors controlling (in our case spatial) variability are not necessarily the same as those controlling associated climate change signals. Since the analysis yields a rather qualitative output, the model bias problems encountered when studying ensemble averages are alleviated.

Orlowsky, B.; Seneviratne, S. I.



Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore  

PubMed Central

A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.

Ibrahim, Bashar; Henze, Richard; Gruenert, Gerd; Egbert, Matthew; Huwald, Jan; Dittrich, Peter



Application of spatial technology in malaria research & control: some new insights.  


Geographical information System (GIS) has emerged as the core of the spatial technology which integrates wide range of dataset available from different sources including Remote Sensing (RS) and Global Positioning System (GPS). Literature published during the decade (1998-2007) has been compiled and grouped into six categories according to the usage of the technology in malaria epidemiology. Different GIS modules like spatial data sources, mapping and geo-processing tools, distance calculation, digital elevation model (DEM), buffer zone and geo-statistical analysis have been investigated in detail, illustrated with examples as per the derived results. These GIS tools have contributed immensely in understanding the epidemiological processes of malaria and examples drawn have shown that GIS is now widely used for research and decision making in malaria control. Statistical data analysis currently is the most consistent and established set of tools to analyze spatial datasets. The desired future development of GIS is in line with the utilization of geo-statistical tools which combined with high quality data has capability to provide new insight into malaria epidemiology and the complexity of its transmission potential in endemic areas. PMID:19797808

Saxena, Rekha; Nagpal, B N; Srivastava, Aruna; Gupta, S K; Dash, A P



Development of an improved spatial reconstruction technique for the HLL method and its applications  

NASA Astrophysics Data System (ADS)

The integral form of the conventional HLL fluxes are presented by taking integrals around the control volume centred on each cell interface. These integrals are demonstrated to reduce to the conventional HLL flux through simplification by assuming spatially constant conserved properties. The integral flux expressions are then modified by permitting the analytical inclusion of spatially linearly varying conserved quantities. The newly obtained fluxes (which are named HLLG fluxes for clarification, where G stands for gradient inclusion) demonstrate that conventional reconstructions at cell interfaces are invalid and can produce unstable results when applied to conventional HLL schemes. The HLLG method is then applied to the solution of the Euler Equations and Shallow Water Equations for various common benchmark problems and finally applied to a 1D fluid modeling for an argon RF discharge at low pressure. Results show that the correct inclusion of flow gradients is shown to demonstrate superior transient behavior when compared to the existing HLL solver and conventional spatial reconstruction without significantly increasing computational expense.

Smith, Matthew R.; Lin, K.-M.; Hung, C.-T.; Chen, Y.-S.; Wu, J.-S.



Spatially aware expectation maximization (SpAEM): application to prostate TRUS segmentation  

NASA Astrophysics Data System (ADS)

In this paper we introduce Spatially Aware Expectation Maximization (SpAEM), a new parameter estimation method which incorporates information pertaining to spatial prior probability into the traditional expectation- maximization framework. For estimating the parameters of a given class, the spatial prior probability allows us to weight the contribution of any pixel based on the probability of that pixel belonging to the class of interest. In this paper we evaluate SpAEM for the problem of prostate capsule segmentation in transrectal ultrasound (TRUS) images. In cohort of 6 patients, SpAEM qualitatively and quantitatively outperforms traditional EM in distinguishing the foreground (prostate) from background (non-prostate) regions by around 45% in terms of the Sorensen Dice overlap measure, when compared against expert annotations. The variance of the estimated parameters measured via Cramer-Rao Lower Bound suggests that SpAEM yields unbiased estimates. Finally, on a synthetic TRUS image, the Cramer-Von Mises (CVM) criteria shows that SpAEM improves the estimation accuracy by around 51% and 88% for prostate and background, respectively, as compared to traditional EM.

Orooji, Mahdi; Sparks, Rachel; Bloch, B. Nicolas; Feleppa, Ernest; Barratt, Dean; Madabhushi, Anant



An Integrative Hierarchical Stepwise Sampling Strategy For Spatial Sampling And Its Application In Digital Soil Mapping  

NASA Astrophysics Data System (ADS)

Sampling design plays an important role in spatial modeling. Existing methods often require large amount of samples to achieve desired mapping accuracy but imply considerable cost. When there are not enough resources for collecting a large set of samples at once, stepwise sampling approach is often the only option for collecting the needed large sample set, especially in the case of field surveying over large areas. This paper proposes an integrative hierarchical stepwise sampling strategy which makes the samples collected at different stages an integrative one. The strategy is based on samples' representativeness of the geographic feature at different scales. The basic idea is to sample at locations that are representative of large-scale spatial patterns first and then add samples that represent more local patterns in a stepwise fashion. Based on the relationships between geographic feature and its environmental covariates, the proposed sampling method approximates a hierarchy of spatial variations of the geographic feature under concern by delineating natural aggregates (clusters) of its relevant environmental covariates at different scales. The natural occurrence of such aggregates is modeled using a fuzzy c-means clustering method. We iterate through different numbers of clusters from only a few to many more to be able to reveal clusters at different spatial scales. At a particular iteration, locations that bear high similarity to the cluster prototypes are identified. If a location is consistently identified at multiple iterations it is then considered to be more representative of the general or large-scale spatial patterns. Locations that are identified less during the iterations are representative of local patterns. The integrative stepwise sampling design then gives higher sampling priority to the locations that are more representative of the large scale patterns than local ones. We applied this sampling design in a digital soil mapping case study. Different representative samples were obtained and used for soil inference. We started with samples that are the most representative of the large scale patterns and then gradually include the samples representative of local patterns. Field evaluation indicated that the additions of more samples with lower representativeness lead to improvements of accuracy with a decreasing marginal gain. When cost-effectiveness is considered, the representative grade could provide essential information on the number and order of samples to be sampled for an effective sampling design.

Yang, L.; Zhu, A.; Qi, F.; Qin, C.; Li, B.; Pei, T.



Compact, transmissive two-dimensional spatial disperser design with application in simultaneous endoscopic imaging and laser microsurgery.  


Minimally invasive surgery procedures benefit from a reduced size of endoscopic devices. A prospective path to implement miniaturized endoscopy is single optical-fiber-based spectrally encoded imaging. While simultaneous spectrally encoded inertial-scan-free imaging and laser microsurgery have been successfully demonstrated in a large table setup, a highly miniaturized optical design would promote the development of multipurpose endoscope heads. This paper presents a highly scalable, entirely transmissive axial design for a spectral 2D spatial disperser. The proposed design employs a grating prism and a virtual imaged phased array (VIPA). Based on semi-analytical device modeling, we performed a systematic parameter analysis to assess the spectral disperser's manufacturability and to obtain an optimum application-specific design. We found that, in particular, a low grating period combined with a high optical input bandwidth and low VIPA tilt showed favorable results in terms of a high spatial resolution, a small device diameter, and a large field of view. Our calculations reveal that a reasonable imaging performance can be achieved with system diameters of below 5 mm, which renders the proposed 2D spatial disperser design highly suitable for use in future endoscope heads that combine mechanical-scan-free imaging and laser microsurgery. PMID:24514122

Metz, Philipp; Adam, Jost; Gerken, Martina; Jalali, Bahram



The application of the fast, multi-hit, pixel imaging mass spectrometry sensor to spatial imaging mass spectrometry  

NASA Astrophysics Data System (ADS)

Imaging mass spectrometry is a powerful technique that allows chemical information to be correlated to a spatial coordinate on a sample. By using stigmatic ion microscopy, in conjunction with fast cameras, multiple ion masses can be imaged within a single experimental cycle. This means that fewer laser shots and acquisition cycles are required to obtain a full data set, and samples suffer less degradation as overall collection time is reduced. We present the first spatial imaging mass spectrometry results obtained with a new time-stamping detector, named the pixel imaging mass spectrometry (PImMS) sensor. The sensor is capable of storing multiple time stamps in each pixel for each time-of-flight cycle, which gives it multi-mass imaging capabilities within each pixel. A standard velocity-map ion imaging apparatus was modified to allow for microscope mode spatial imaging of a large sample area (approximately 5 × 5 mm2). A variety of samples were imaged using PImMS and a conventional camera to determine the specifications and possible applications of the spectrometer and the PImMS camera.

Brouard, M.; Halford, E.; Lauer, A.; Slater, C. S.; Winter, B.; Yuen, W. H.; John, J. J.; Hill, L.; Nomerotski, A.; Clark, A.; Crooks, J.; Sedgwick, I.; Turchetta, R.; Lee, J. W. L.; Vallance, C.; Wilman, E.




Microsoft Academic Search

Manure applications can enhance phosphorus (P) contamination of nearby waters. Erosion related P contamination is due to runoff water and eroding sediment carrying dissolved and particulate P, respectively. Environmental conditions, soil properties and management affect soil erosion, but minimizing P loss requires considering other factors (rate, method, timing of manure application; soil test P level). As a result, new indices

J. H. Grove; E. M. Pena-Yewtukhiw


Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.  


The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. PMID:24705202

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C



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

PubMed Central

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.

Gustafsson, Johan O. R.; Oehler, Martin K.; Ruszkiewicz, Andrew; McColl, Shaun R.; Hoffmann, Peter



High-speed one-dimensional spatial light modulator for Laser Direct Imaging and other patterning applications  

NASA Astrophysics Data System (ADS)

Fraunhofer IPMS has developed a one-dimensional high-speed spatial light modulator in cooperation with Micronic Mydata AB. This SLM is the core element of the Swedish company's new LDI 5sp series of Laser-Direct-Imaging systems optimized for processing of advanced substrates for semiconductor packaging. This paper reports on design, technology, characterization and application results of the new SLM. With a resolution of 8192 pixels that can be modulated in the MHz range and the capability to generate intensity gray-levels instantly without time multiplexing, the SLM is applicable also in many other fields, wherever modulation of ultraviolet light needs to be combined with high throughput and high precision.

Schmidt, Jan-Uwe; Dauderstaedt, Ulrike A.; Duerr, Peter; Friedrichs, Martin; Hughes, Thomas; Ludewig, Thomas; Rudloff, Dirk; Schwaten, Tino; Trenkler, Daniela; Wagner, Michael; Wullinger, Ingo; Bergstrom, Andreas; Bjoernangen, Peter; Jonsson, Fredrik; Karlin, Tord; Ronnholm, Peter; Sandstrom, Torbjorn



Spatial input variables applications for hydrological simulation of south Wyoming watershed: case study of Muddy Creek via MIKE SHE  

NASA Astrophysics Data System (ADS)

With the abundant online data sources, there are great advantages of hydrological simulation for the American watershed management. Not only are the conventional station-based data conveniently accessible, but also the spatial data provide the great possibility for the hydrological approaches. This case study demonstrates the possible applications and access source for the hydrological modeling, which might be used as reference. The modeling input time series or parameters origins from various sources: precipitation is from TRMM (as spatial input of hydrological model) and NOAA (station-based), evapotranspiration came from (NASA MODIS platform via ArcGIS access), temperature is delivered by NOAA database (station-based) and NASA MODIS (spatial input), the snow mask and depth also can be obtained from NOAA, NASA MODIS and NRCS, discharge data might be from USGS hydro-climate data network (HCDN). The parameters of static state are surely complete such as DEM contributed by STRM of NASA, soil related data from SSURGO and landuse related data obtained from USGS. The different institutes might focus on different aspects, temporal span, geo-locations. But supported by the various sources of data, the hydrological modeling can be setup solidly by interpolating the various data. The daily time step simulation is manually calibrated for 1 year period referred by 4 discharge gauging stations, as well as 1 year of validation period. Simulation resolution is uniformed to 200m*200m cells size according the 2600km2 of watershed domain. The case study demonstrates that the station-based and spatial data could cooperate each other and support the accurate hydrological modeling during. Based on the established model, it can be further extended for the assessment of water quality impact and sediment transportation simulation. The final goal the modeling approach is to serve the land management on hydrological response.

Liu, T.; Miller, S. N.; Chitrakar, S.



Mono-detection spatially super resolved microwave imaging for RADAR applications  

NASA Astrophysics Data System (ADS)

In this paper we present a novel RF photonic approach to radar scanning and imaging. The operating principle is based upon a system in which several (in our case two) radiating microwave sources generate and project at far field, a moving grating pattern over an object, e.g. by linearly modifying the relative phase between the microwave sources. Capturing a set of such integrated reflections (we work only with a mono detector) coming from the object at different radio frequencies (due to a simultaneously performed spectral scanning) can spatially reconstruct high resolution image of the object despite the fact that the sensing was performed with a small mono receiving antenna.

Shemer, Amir; Gabay, Isahar; Tur, Moshe; Boag, Amir; Kleinman, Haim; Zach, Shlomo; Zalevsky, Zeev



Characterization of a polycapillary focusing X-ray lens for application in spatially resolved EXAFS experiments  

NASA Astrophysics Data System (ADS)

A dispersive extended-X-ray-absorption-fine-structure (EXAFS) spectrometer based on a polycapillary focusing X-ray lens (PFXRL), a position-sensitive proportional counter and a rotating anode X-ray source is designed. When the working voltage and current of a Mo rotating anode X-ray generator are 25 kV and 100 mA, respectively, it takes 6 h to obtain the EXAFS spectrum of the Cu film. The experiments show that a dispersive EXAFS spectrometer based on a PFXRL can be applied in spatially resolved EXAFS analysis.

Sun, Tianxi; Liu, Zhiguo; Ding, Xunliang



Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs substrates  

NASA Astrophysics Data System (ADS)

The fabrication and characterization of an optically addressable deformable mirror for a spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5 ?m thick grid of patterned photoresist supports the 2 ?m thick aluminized Mylar membrane. A conductive ZnO layer is placed on the back side of the GaAs wafer. A standard Michelson interferometer is used to measure mirror deformation data as a function of illumination, applied voltage, and frequency. A simplified analysis of device operation is also presented.

Haji-Saeed, Bahareh; Kolluru, Rathna; Pyburn, Dana; Leon, Roberto; Sengupta, Sandip K.; Testorf, Markus; Goodhue, William; Khoury, Jed; Drehman, Alvin; Woods, Charles L.; Kierstead, John



Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs substrates.  


The fabrication and characterization of an optically addressable deformable mirror for a spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5 microm thick grid of patterned photoresist supports the 2 microm thick aluminized Mylar membrane. A conductive ZnO layer is placed on the back side of the GaAs wafer. A standard Michelson interferometer is used to measure mirror deformation data as a function of illumination, applied voltage, and frequency. A simplified analysis of device operation is also presented. PMID:16633410

Haji-Saeed, Bahareh; Kolluru, Rathna; Pyburn, Dana; Leon, Roberto; Sengupta, Sandip K; Testorf, Markus; Goodhue, William; Khoury, Jed; Drehman, Alvin; Woods, Charles L; Kierstead, John



Joint Variable Spatial Downscaling (JVSD): A New Downscaling Method with Application to the Southeast US  

NASA Astrophysics Data System (ADS)

Joint Variable Spatial Downscaling (JVSD) is a new downscaling method developed to produce high resolution gridded hydrological datasets suitable for regional watershed modeling and assessments. JVSD differs from other statistical downscaling methods in that multiple climatic variables are downscaled simultaneously to produce realistic and consistent climate fields. JVSD includes two major steps: bias correction and spatial downscaling. In the bias correction step, JVSD uses a differencing process to create stationary joint cumulative frequency statistics of the variables being downscaled. Bias correction is then based on quantile-to-quantile mapping of these stationary frequency distributions probability space. The functional relationship between these statistics and those of the historical observation period is subsequently used to remove GCM bias. The original variables are recovered through summation of bias corrected differenced sequences. In the spatial disaggregation step, JVSD uses a historical analogue approach, with historical analogues identified simultaneously for all atmospheric fields and over all areas of the basin under study. Analysis and comparisons with 20th Century Climate in Coupled Models (20C3M) data show that JVSD reproduces the sub-grid climatic features as well as their temporal/spatial variability in the historical periods. Comparisons are also performed for precipitation and temperature with the North American regional climate change assessment program (NARCCAP) and other statistical downscaling methods over the southeastern US. The results show that JVSD performs favorably. JVSD is applied for all A1B and A2 CMIP3 GCM scenarios in the Apalachicola-Chattahoochee-Flint River Basin (southeast US) with the following general findings: (i) Mean monthly temperature exhibits increasing trends over the ACF basin for all seasons and all A1B and A2 scenarios; Most significant are the A2 temperature increases in the 2050 - 2099 time periods; (ii) In the southern ACF watersheds, mean precipitation generally exhibits a mild decline in early spring and summer and increases in late winter; For the northern ACF watersheds, mean precipitation decreases in summer and increases mildly in winter (as in the south); (iii) In addition to mean trends, the precipitation distributions stretch on both ends with higher highs (floods) and lower lows (droughts). The downscaled temperature and precipitation scenarios are the basis of a comprehensive hydrologic and water resources assessment (reported elsewhere) assessing significant water, agricultural, energy, and environmental sector impacts and underscoring the need for mitigation and adaptation measures.

Zhang, F.; Georgakakos, A. P.



Reconstruction of fully three-dimensional high spatial and temporal resolution MR temperature maps for retrospective applications.  


Many areas of MR-guided thermal therapy research would benefit from temperature maps with high spatial and temporal resolution that cover a large three-dimensional volume. This article describes an approach to achieve these goals, which is suitable for research applications where retrospective reconstruction of the temperature maps is acceptable. The method acquires undersampled data from a modified three-dimensional segmented echo-planar imaging sequence and creates images using a temporally constrained reconstruction algorithm. The three-dimensional images can be zero-filled to arbitrarily small voxel spacing in all directions and then converted into temperature maps using the standard proton resonance frequency shift technique. During high intensity focused ultrasound heating experiments, the proposed method was used to obtain temperature maps with 1.5 mm × 1.5 mm × 3.0 mm resolution, 288 mm × 162 mm × 78 mm field of view, and 1.7 s temporal resolution. The approach is validated to demonstrate that it can accurately capture the spatial characteristics and time dynamics of rapidly changing high intensity focused ultrasound-induced temperature distributions. Example applications from MR-guided high intensity focused ultrasound research are shown to demonstrate the benefits of the large coverage fully three-dimensional temperature maps, including characterization of volumetric heating trajectories and near- and far-field heating. PMID:21702066

Todd, Nick; Vyas, Urvi; de Bever, Josh; Payne, Allison; Parker, Dennis L



Robust Student's-t mixture model with spatial constraints and its application in medical image segmentation.  


Finite mixture model based on the Student's-t distribution, which is heavily tailed and more robust than Gaussian, has recently received great attention for image segmentation. A new finite Student's-t mixture model (SMM) is proposed in this paper. Existing models do not explicitly incorporate the spatial relationships between pixels. First, our model exploits Dirichlet distribution and Dirichlet law to incorporate the local spatial constrains in an image. Secondly, we directly deal with the Student's-t distribution in order to estimate the model parameters, whereas, the Student's-t distributions in previous models are represented as an infinite mixture of scaled Gaussians that lead to an increase in complexity. Finally, instead of using expectation maximization (EM) algorithm, the proposed method adopts the gradient method to minimize the higher bound on the data negative log-likelihood and to optimize the parameters. The proposed model is successfully compared to the state-of-the-art finite mixture models. Numerical experiments are presented where the proposed model is tested on various simulated and real medical images. PMID:21859612

Nguyen, Thanh Minh; Wu, Q M Jonathan



Candidate gene prioritization based on spatially mapped gene expression: an application to XLMR  

PubMed Central

Motivation: The identification of genes involved in specific phenotypes, such as human hereditary diseases, often requires the time-consuming and expensive examination of a large number of positional candidates selected by genome-wide techniques such as linkage analysis and association studies. Even considering the positive impact of next-generation sequencing technologies, the prioritization of these positional candidates may be an important step for disease-gene identification. Results: Here, we report a large-scale analysis of spatial, i.e. 3D, gene-expression data from an entire organ (the mouse brain) for the purpose of evaluating and ranking positional candidate genes, showing that the spatial gene-expression patterns can be successfully exploited for the prediction of gene–phenotype associations not only for mouse phenotypes, but also for human central nervous system-related Mendelian disorders. We apply our method to the case of X-linked mental retardation, compare the predictions to the results obtained from a previous large-scale resequencing study of chromosome X and discuss some promising novel candidates. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

Piro, Rosario M.; Molineris, Ivan; Ala, Ugo; Provero, Paolo; Di Cunto, Ferdinando



Development and application of a spatial hydrology model of Okefenokee Swamp, Georgia  

USGS Publications Warehouse

The model described herein was used to assess effects of the Suwannee River sill (a low earthen dam constructed to impound the Suwannee River within the Okefenokee National Wildlife Refuge to eliminate wildfires) on the hydrologic environment of Okefenokee Swamp, Georgia. Developed with Arc/Info Macro Language routines in the GRID environment, the model distributes water in the swamp landscape using precipitation, inflow, evapotranspiration, outflow, and standing water. Water movement direction and rate are determined by the neighborhood topographic gradient, determined using survey grade Global Positioning Systems technology. Model data include flow rates from USGS monitored gauges, precipitation volumes and water levels measured within the swamp, and estimated evapotranspiration volumes spatially modified by vegetation type. Model output in semi-monthly time steps includes water depth, water surface elevation above mean sea level, and movement direction and volume. Model simulations indicate the sill impoundment affects 18 percent of the swamp during high water conditions when wildfires are scarce and has minimal spatial effect (increasing hydroperiods in less than 5 percent of the swamp) during low water and drought conditions when fire occurrence is high but precipitation and inflow volumes are limited.

Loftin, C. S.; Kitchens, W. M.; Ansay, N.



Spatially resolved spectroscopic measurements of a dielectric barrier discharge plasma jet applicable for soft ionization  

NASA Astrophysics Data System (ADS)

An atmospheric pressure microplasma ionization source based on a dielectric barrier discharge with a helium plasma cone outside the electrode region has been developed for liquid chromatography/mass spectrometry and as ionization source for ion mobility spectrometry. It turned out that dielectric barrier discharge ionization could be regarded as a soft ionization technique characterized by only minor fragmentation similar to atmospheric pressure chemical ionization (APCI). Mainly protonated molecules were detected. In order to characterize the soft ionization mechanism spatially resolved optical emission spectrometry (OES) measurements were performed on plasma jets burning either in He or in Ar. Besides to spatial intensity distributions of noble gas spectral lines, in both cases a special attention was paid to lines of N 2+ and N 2. The obtained mapping of the plasma jet shows very different number density distributions of relevant excited species. In the case of helium plasma jet, strong N 2+ lines were observed. In contrast to that, the intensities of N 2 lines in Ar were below the present detection limit. The positions of N 2+ and N 2 distribution maxima in helium indicate the regions where the highest efficiency of the water ionization and the protonation process is expected.

Olenici-Craciunescu, S. B.; Müller, S.; Michels, A.; Horvatic, V.; Vadla, C.; Franzke, J.



Geo-spatial Service and Application based on National E-government Network Platform and Cloud  

NASA Astrophysics Data System (ADS)

With the acceleration of China's informatization process, our party and government take a substantive stride in advancing development and application of digital technology, which promotes the evolution of e-government and its informatization. Meanwhile, as a service mode based on innovative resources, cloud computing may connect huge pools together to provide a variety of IT services, and has become one relatively mature technical pattern with further studies and massive practical applications. Based on cloud computing technology and national e-government network platform, "National Natural Resources and Geospatial Database (NRGD)" project integrated and transformed natural resources and geospatial information dispersed in various sectors and regions, established logically unified and physically dispersed fundamental database and developed national integrated information database system supporting main e-government applications. Cross-sector e-government applications and services are realized to provide long-term, stable and standardized natural resources and geospatial fundamental information products and services for national egovernment and public users.

Meng, X.; Deng, Y.; Li, H.; Yao, L.; Shi, J.



Spatial three-dimensional landslide susceptibility mapping tool and its applications  

NASA Astrophysics Data System (ADS)

There are three methods of zoning landslide susceptibility: qualitative, statistical methodologies, and geotechnical model. Qualitative approaches are based on the judgment of those conducting the susceptibility or hazard assessment; the statistical approach uses a predictive function or index derived from a combination of weighted factors; and the deterministic, or physically based, models are based on the physical laws of conservation of mass, energy, and momentum. Two-dimensional deterministic models are widely used in the design of civil engineering, and the infinite slope model (one-dimensional) is always employed in the deterministic-model-based landslide hazard mapping. This article presents a new GIS (Geographic Information Systems)-based landslide susceptibility mapping system which can be used to identify the three-dimensional (3-D) landslide bodies from complex topography. All slope-related spatial information (vector or raster dataset) was integrated in the system, by dividing the study area into slope units and assuming the initial slip to be the lower part of an ellipsoid. The 3-D critical slip surface in the 3-D slope stability analysis was located by minimizing the 3-D safety factor using the Monte Carlo random simulation. The failure probability of the landslide was calculated using an approximate method in which effective cohesion, effective friction angle, and 3-D safety factor were assumed to be in normal distribution. A computational program called 3-DSlopeGIS, in which a GIS Developer kit (ArcObjects of ESRI) had been used to fulfill the GIS spatial analysis function and effective data management, has been developed to implement all the calculations of the 3-D slope problem. By using the spatial analysis functions, the data management, and the visualization of GIS for processing the complicated slope-related data, the 3-D slope stability problem is easier to be studied through a friendly visual graphical user interface. The system has been applied for mapping the landslide susceptibility of three examples: the first one for city planning, the second for predicting the possible landslide influence around a past slope disaster, and the third for mapping landslide along a national route. Based on numerous Monte Carlo simulation, the possible critical landslide bodies have been identified, which cannot be carried out by using the traditional slope stability analyses.

Xie, Mowen; Tetsuro, Esaki; Qiu, Cheng; Jia, Lin


Passive microwave derived snowmelt timing: significance, spatial and temporal variability, and potential applications  

NASA Astrophysics Data System (ADS)

Snow accumulation and melt are dynamic features of the cryosphere indicative of a changing climate. Spring melt and refreeze timing are of particular importance due to the influence on subsequent hydrological and ecological processes, including peak runoff and green-up. To investigate the spatial and temporal variability of melt timing across a sub-arctic region (the Yukon River Basin (YRB), Alaska/Canada) dominated by snow and lacking substantial ground instrumentation, passive microwave remote sensing was utilized to provide daily brightness temperatures (Tb) regardless of clouds and darkness. Algorithms to derive the timing of melt onset and the end of melt-refreeze, a critical transition period where the snowpack melts during the day and refreezes at night, were based on thresholds for Tb and diurnal amplitude variations (day and night difference). Tb data from the Special Sensor Microwave Imager (1988 to 2011) was used for analyzing YRB terrestrial snowmelt timing and for characterizing melt regime patterns for icefields in Alaska and Patagonia. Tb data from the Advanced Microwave Scanning Radiometer for EOS (2003 to 2010) was used for determining the occurrence of early melt events (before melt onset) associated with fog or rain on snow, for investigating the correlation between melt timing and forest fires, and for driving a flux-based snowmelt runoff model. From the SSM/I analysis: the melt-refreeze period lengthened for the majority of the YRB with later end of melt-refreeze and earlier melt onset; and positive Tb anomalies were found in recent years from glacier melt dynamics. From the AMSR-E analysis: early melt events throughout the YRB were most often associated with warm air intrusions and reflect a consistent spatial distribution; years and areas of earlier melt onset and refreeze had more forest fire occurrences suggesting melt timing's effects extend to later seasons; and satellite derived melt timing served as an effective input for model simulation of discharge in remote, ungauged snow-dominated basins. The melt detection methodology and results present a new perspective on the changing cryosphere, provide an understanding of melt's influence on other earth system processes, and develop a baseline from which to assess and evaluate future change. The temporal and spatial variability conveyed through the regional context of this research may be useful to communities in climate change adaptation planning.

Semmens, Kathryn Alese


Optimal steering for kinematic vehicles with applications to spatially distributed agents  

NASA Astrophysics Data System (ADS)

While there is no universal method to address control problems involving networks of autonomous vehicles, there exist a few promising schemes that apply to different specific classes of problems, which have attracted the attention of many researchers from different fields. In particular, one way to extend techniques that address problems involving a single autonomous vehicle to those involving teams of autonomous vehicles is to use the concept of Voronoi diagram. The Voronoi diagram provides a spatial partition of the environment the team of vehicles operate in, where each element of this partition is associated with a unique vehicle from the team. The partition induces a graph abstraction of the operating space that is in an one-to-one correspondence with the network abstraction of the team of autonomous vehicles; a fact that can provide both conceptual and analytical advantages during mission planning and execution. In this dissertation, we propose the use of a new class of Voronoi-like partitioning schemes with respect to state-dependent proximity (pseudo-) metrics rather than the Euclidean distance or other generalized distance functions, which are typically used in the literature. An important nuance here is that, in contrast to the Euclidean distance, state-dependent metrics can succinctly capture system theoretic features of each vehicle from the team (e.g., vehicle kinematics), as well as the environment-vehicle interactions, which are induced, for example, by local winds/currents. We subsequently illustrate how the proposed concept of state-dependent Voronoi-like partition can induce local control schemes for problems involving networks of spatially distributed autonomous vehicles by examining a sequential pursuit problem of a maneuvering target by a group of pursuers distributed in the plane. The construction of generalized Voronoi diagrams with respect to state-dependent metrics poses some significant challenges. First, the generalized distance metric may be a function of the direction of motion of the vehicle (anisotropic pseudo-distance function) and/or may not be expressible in closed form. Second, such problems fall under the general class of partitioning problems for which the vehicles' dynamics must be taken into account. The topology of the vehicle's configuration space may be non-Euclidean, for example, it may be a manifold embedded in a Euclidean space. In other words, these problems may not be reducible to generalized Voronoi diagram problems for which efficient construction schemes, analytical and/or computational, exist in the literature. This research effort pursues three main objectives. First, we present the complete solution of different steering problems involving a single vehicle in the presence of motion constraints imposed by the maneuverability envelope of the vehicle and/or the presence of a drift field induced by winds/currents in its vicinity. The analysis of each steering problem involving a single vehicle provides us with a state-dependent generalized metric, such as the minimum time-to-go/come. We subsequently use these state-dependent generalized distance functions as the proximity metrics in the formulation of generalized Voronoi-like partitioning problems. The characterization of the solutions of these state-dependent Voronoi-like partitioning problems using either analytical or computational techniques constitutes the second main objective of this dissertation. The third objective of this research effort is to illustrate the use of the proposed concept of state-dependent Voronoi-like partition as a means for passing from control techniques that apply to problems involving a single vehicle to problems involving networks of spatially distributed autonomous vehicles. To this aim, we formulate the problem of sequential/relay pursuit of a maneuvering target by a group of spatially distributed pursuers and subsequently propose a distributed group pursuit strategy that directly derives from the solution of a state-dependent Voronoi-like partitioning problem. (Abstract shortened by UMI.)

Brown, Scott; Praeger, Cheryl E.; Giudici, Michael


Image segmentation using joint spatial-intensity-shape features: application to CT lung nodule segmentation  

NASA Astrophysics Data System (ADS)

Automatic segmentation of medical images is a challenging problem due to the complexity and variability of human anatomy, poor contrast of the object being segmented, and noise resulting from the image acquisition process. This paper presents a novel feature-guided method for the segmentation of 3D medical lesions. The proposed algorithm combines 1) a volumetric shape feature (shape index) based on high-order partial derivatives; 2) mean shift clustering in a joint spatial-intensity-shape (JSIS) feature space; and 3) a modified expectation-maximization (MEM) algorithm on the mean shift mode map to merge the neighboring regions (modes). In such a scenario, the volumetric shape feature is integrated into the process of the segmentation algorithm. The joint spatial-intensity-shape features provide rich information for the segmentation of the anatomic structures or lesions (tumors). The proposed method has been evaluated on a clinical dataset of thoracic CT scans that contains 68 nodules. A volume overlap ratio between each segmented nodule and the ground truth annotation is calculated. Using the proposed method, the mean overlap ratio over all the nodules is 0.80. On visual inspection and using a quantitative evaluation, the experimental results demonstrate the potential of the proposed method. It can properly segment a variety of nodules including juxta-vascular and juxta-pleural nodules, which are challenging for conventional methods due to the high similarity of intensities between the nodules and their adjacent tissues. This approach could also be applied to lesion segmentation in other anatomies, such as polyps in the colon.

Ye, Xujiong; Siddique, Musib; Douiri, Abdel; Beddoe, Gareth; Slabaugh, Greg



Development and application of an instrument for spatially resolved Seebeck coefficient measurements  

NASA Astrophysics Data System (ADS)

The Seebeck coefficient is a key indicator of the majority carrier type (electrons or holes) in a material. The recent trend toward the development of combinatorial materials research methods has necessitated the development of a new high-throughput approach to measuring the Seebeck coefficient at spatially distinct points across any sample. The overall strategy of the high-throughput experiments is to quickly identify the region of interest on the sample at some expense of accuracy, and then study this region by more conventional techniques. The instrument for spatially resolved Seebeck coefficient measurements reported here relies on establishing a temperature difference across the entire compositionally graded thin-film and consecutive mapping of the resulting voltage as a function of position, which facilitates the temperature-dependent measurements up to 400 °C. The results of the designed instrument are verified at ambient temperature to be repeatable over 10 identical samples and accurate to within 10% versus conventional Seebeck coefficient measurements over the -100 to +150 ?V/K range using both n-type and p-type conductive oxides as test cases. The developed instrument was used to determine the sign of electrical carriers of compositionally graded Zn-Co-O and Ni-Co-O libraries prepared by combinatorial sputtering. As a result of this study, both cobalt-based materials were determined to have p-type conduction over a broad single-phase region of chemical compositions and small variation of the Seebeck coefficient over the entire investigated range of compositions and temperature.

Zakutayev, Andriy; Luciano, Frank J.; Bollinger, Vincent P.; Sigdel, Ajaya K.; Ndione, Paul F.; Perkins, John D.; Berry, Joseph J.; Parilla, Philip A.; Ginley, David S.



Scaling of spatial snow depth distribution parameters for large-scale model applications  

NASA Astrophysics Data System (ADS)

Snow depth distribution is extremely heterogeneous in mountainous terrain where the snow cover is typically influenced by large spatial gradients of incident radiation, precipitation and wind. Small-scale snow depth variations play a key role in large-scale models such as hydrologic catchment or land-surface models. Due to computational constraints, small-scale distributed modeling is, in general, rarely feasible for large regions. However, information about small-scale (sub-grid) snow coverage is essential for instance to accurately represent snow melt rates for large grid sizes. Past research has shown that for rather homogeneous landscape units the pre-melt spatial distribution of snow depth can be approximated by a log-normal distribution. However, this may no longer be valid for snow distributions over landscape units covering complex terrain. Seasonally recurring snow accumulation patterns have been reported, mostly shaped by precipitation, radiation and wind. Which process dominates, strongly depends on the considered scale. We focus on large heterogeneous landscape units on the order of a few kilometers, typically employed by hydrologic and land-surface models. In order to characterize the impact of topographic parameters on pre-melt sub grid snow depth distribution, we analyzed a new, highly resolved data set acquired at peak of winter. Snow depth data with 2 m horizontal resolution was obtained from an opto-electronic scanning data set (Sensor ADS 80, Leica Geosystems) in a large catchment located above Davos, in the eastern Swiss Alps. Sub-grid snow distribution parameters were found to scale with topographic descriptors such as mean slope and standard deviation of the summer digital elevation model. Our results suggest that parameterizations of the snow-covered fraction can be enhanced if terrain parameters are included.

Helbig, Nora; Magnusson, Jan; Jonas, Tobias




Microsoft Academic Search

Within the last few years, a new kind of applications has evolved: location-based services are on their way to become one of the leading powers within the field of information technology. At the University of Stuttgart, a research project called NEXUS has been initiated to develop an open and global platform supporting all possible types of mobile, location-based information systems.

Steffen Volz; Jan-Martin Bofinger



Wave optics simulation of spatially partially coherent beams: Applications to free space laser communications  

Microsoft Academic Search

One of the main drawbacks that prevent the extensive application of free space laser communications is the atmospheric turbulence through which the beam must propagate. For the past four decades, much attention has been devoted to finding different methods to overcome this difficulty. A partially coherent beam (PCB) has been recognized as an effective approach to improve the performance of

Xifeng Xiao



Application of spatial multi-criteria analysis to site selection for a local park: a case study in the Bergamo Province, Italy.  


This contribution discusses a site selection process for establishing a local park. It was supported by a value-focused approach and spatial multi-criteria evaluation techniques. A first set of spatial criteria was used to design a number of potential sites. Next, a new set of spatial and non-spatial criteria was employed, including the social functions and the financial costs, together with the degree of suitability for the park to evaluate the potential sites and to recommend the most acceptable one. The whole process was facilitated by a new software tool that supports spatial multiple criteria evaluation, or SMCE. The application of this tool, combined with a continual feedback by the public administration, has provided an effective methodology to solve complex decisional problem in land-use and urban planning. PMID:17888564

Zucca, Antonella; Sharifi, Ali M; Fabbri, Andrea G



Mapping Genetic Diversity of Cherimoya (Annona cherimola Mill.): Application of Spatial Analysis for Conservation and Use of Plant Genetic Resources  

PubMed Central

There is a growing call for inventories that evaluate geographic patterns in diversity of plant genetic resources maintained on farm and in species' natural populations in order to enhance their use and conservation. Such evaluations are relevant for useful tropical and subtropical tree species, as many of these species are still undomesticated, or in incipient stages of domestication and local populations can offer yet-unknown traits of high value to further domestication. For many outcrossing species, such as most trees, inbreeding depression can be an issue, and genetic diversity is important to sustain local production. Diversity is also crucial for species to adapt to environmental changes. This paper explores the possibilities of incorporating molecular marker data into Geographic Information Systems (GIS) to allow visualization and better understanding of spatial patterns of genetic diversity as a key input to optimize conservation and use of plant genetic resources, based on a case study of cherimoya (Annona cherimola Mill.), a Neotropical fruit tree species. We present spatial analyses to (1) improve the understanding of spatial distribution of genetic diversity of cherimoya natural stands and cultivated trees in Ecuador, Bolivia and Peru based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by revealing priority areas for in situ conservation, and identifying existing diversity gaps in ex situ collections. We found high levels of allelic richness, locally common alleles and expected heterozygosity in cherimoya's putative centre of origin, southern Ecuador and northern Peru, whereas levels of diversity in southern Peru and especially in Bolivia were significantly lower. The application of GIS on a large microsatellite dataset allows a more detailed prioritization of areas for in situ conservation and targeted collection across the Andean distribution range of cherimoya than previous studies could do, i.e. at province and department level in Ecuador and Peru, respectively.

van Zonneveld, Maarten; Scheldeman, Xavier; Escribano, Pilar; Viruel, Maria A.; Van Damme, Patrick; Garcia, Willman; Tapia, Cesar; Romero, Jose; Siguenas, Manuel; Hormaza, Jose I.



Predictive Scheduling Algorithms for Real-Time Feature Extraction and Spatial Referencing: Application to Retinal Image Sequences  

Microsoft Academic Search

Real-time spatial referencing is an important al- ternative to tracking for designing spatially aware ophthalmic instrumentation for procedures such as laser photocoagulation and perimetry. It requires independent, fast registration of each image frame from a digital video stream (1024 1024 pixels) to a spatial map of the retina. Recently, we have introduced a spatial referencing algorithm that works in three

Gang Lin; Charles V. Stewart; Badrinath Roysam; Kenneth Fritzsche; Gehua Yang; Howard L. Tanenbaum



Predictive scheduling algorithms for real-time feature extraction and spatial referencing: application to retinal image sequences  

Microsoft Academic Search

Real-time spatial referencing is an important alternative to tracking for designing spatially aware ophthalmic instrumentation for procedures such as laser photocoagulation and perimetry. It requires independent, fast registration of each image frame from a digital video stream (1024 × 1024 pixels) to a spatial map of the retina. Recently, we have introduced a spatial referencing algorithm that works in three

Gang Lin; Charles V. Stewart; Badrinath Roysam; Kenneth Fritzsche; Gehua Yang; Howard L. Tanenbaum



Comparison of three temperature control systems applications for a special homemade shortwave infrared spatial remote sensor  

NASA Astrophysics Data System (ADS)

An image spectrometer of a spatial remote sensing satellite requires shortwave band ranging from 2.1?m to 3?m which is one of the most important bands in remote sensing. We designed an infrared sub-system of the image spectrometer using a homemade 640x1 InGaAs shortwave infrared sensor working on FPA system which requires high uniformity and low level of dark current. The working temperature should be -15+/-0.2 Degree Celsius. This paper compares three different kinds of methods to control temperature of the sensor. First design uses a temperature control chip Max1978 from Maxim Company. Second design uses ADN8830 from ANALOG Company. Third design is based on FPGA device APA300. Experiment shows that MAX1978 has driving mosfet inside its chip which makes the stability is not appropriate for this homemade shortwave sensor. While the ADN8830 the supply power is limited to 5V, which also limits the driving power of the chip, experiments show that ADN8830 works very well when the voltage is below 5V, but the result is not acceptable when sensor demand more driving current. The FPGA design covers all the disadvantages above, but it introduced a new problem, the electrical circuit takes much more board resources than MAX1978 and ADN8830.

Xu, Zhipeng; Wei, Jun; Li, Jianwei; Zhou, Qianting



Spatial Variability and Application of Ratios between BTEX in Two Canadian Cities  

PubMed Central

Spatial monitoring campaigns of volatile organic compounds were carried out in two similarly sized urban industrial cities, Windsor and Sarnia, ON, Canada. For Windsor, data were obtained for all four seasons at approximately 50 sites in each season (winter, spring, summer, and fall) over a three-year period (2004, 2005, and 2006) for a total of 12 sampling sessions. Sampling in Sarnia took place at 37 monitoring sites in fall 2005. In both cities, passive sampling was done using 3M 3500 organic vapor samplers. This paper characterizes benzene, toluene, ethylbenzene, o, and (m + p)-xylene (BTEX) concentrations and relationships among BTEX species in the two cities during the fall sampling periods. BTEX concentration levels and rank order among the species were similar between the two cities. In Sarnia, the relationships between the BTEX species varied depending on location. Correlation analysis between land use and concentration ratios showed a strong influence from local industries. Use one of the ratios between the BTEX species to diagnose photochemical age may be biased due to point source emissions, for example, 53 tonnes of benzene and 86 tonnes of toluene in Sarnia. However, considering multiple ratios leads to better conclusions regarding photochemical aging. Ratios obtained in the sampling campaigns showed significant deviation from those obtained at central monitoring stations, with less difference in the (m + p)/E ratio but better overall agreement in Windsor than in Sarnia.

Miller, Lindsay; Xu, Xiaohong; Wheeler, Amanda; Atari, Dominic Odwa; Grgicak-Mannion, Alice; Luginaah, Isaac



Application of an extended equalization-cancellation model to speech intelligibility with spatially distributed maskers  

PubMed Central

An extended version of the equalization-cancellation (EC) model of binaural processing is described and applied to speech intelligibility tasks in the presence of multiple maskers. The model incorporates time-varying jitters, both in time and amplitude, and implements the equalization and cancellation operations in each frequency band independently. The model is consistent with the original EC model in predicting tone-detection performance for a large set of configurations. When the model is applied to speech, the speech intelligibility index is used to predict speech intelligibility performance in a variety of conditions. Specific conditions addressed include different types of maskers, different numbers of maskers, and different spatial locations of maskers. Model predictions are compared with empirical measurements reported by Hawley et al. [J. Acoust. Soc. Am. 115, 833–843 (2004)] and by Marrone et al. [J. Acoust. Soc. Am. 124, 1146–1158 (2008)]. The model succeeds in predicting speech intelligibility performance when maskers are speech-shaped noise or broadband-modulated speech-shaped noise but fails when the maskers are speech or reversed speech.

Wan, Rui; Durlach, Nathaniel I.; Colburn, H. Steven



Bayesian Hierarchical Spatially Correlated Functional Data Analysis with Application to Colon Carcinogenesis  

PubMed Central

Summary In this article, we present new methods to analyze data from an experiment using rodent models to investigate the role of p27, an important cell-cycle mediator, in early colon carcinogenesis. The responses modeled here are essentially functions nested within a two-stage hierarchy. Standard functional data analysis literature focuses on a single stage of hierarchy and conditionally independent functions with near white noise. However, in our experiment, there is substantial biological motivation for the existence of spatial correlation among the functions, which arise from the locations of biological structures called colonic crypts: this possible functional correlation is a phenomenon we term crypt signaling. Thus, as a point of general methodology, we require an analysis that allows for functions to be correlated at the deepest level of the hierarchy. Our approach is fully Bayesian and uses Markov chain Monte Carlo methods for inference and estimation. Analysis of this data set gives new insights into the structure of p27 expression in early colon carcinogenesis and suggests the existence of significant crypt signaling. Our methodology uses regression splines, and because of the hierarchical nature of the data, dimension reduction of the covariance matrix of the spline coefficients is important: we suggest simple methods for overcoming this problem.

Baladandayuthapani, Veerabhadran; Mallick, Bani K.; Hong, Mee Young; Lupton, Joanne R.; Turner, Nancy D.; Carroll, Raymond J.



Spatial conductivity mapping of carbon nanotube composite thin films by electrical impedance tomography for sensing applications  

Microsoft Academic Search

This paper describes the application of electrical impedance tomography (EIT) to demonstrate the multifunctionality of carbon nanocomposite thin films under various types of environmental stimuli. Carbon nanotube (CNT) thin films are fabricated by a layer-by-layer (LbL) technique and mounted with electrodes along their boundaries. The response of the thin films to various stimuli is investigated by relying on electric current

Tsung-Chin Hou; Kenneth J Loh; Jerome P Lynch



The influence of input device characteristics on spatial perception in desktop-based 3D applications  

Microsoft Academic Search

In desktop applications 3D input devices are mostly operated by the non-dominant hand to control 3D viewpoint navigation, while selection and geometry manipulations are handled by the dominant hand using the regular 2D mouse. This asymmetric bi-manual interface is an alternative to commonly used keyboard and mouse input, where the non-dominant hand assists the dominant hand with keystroke input to

Alexander Kulik; Jan Hochstrate; Andre Kunert; Bernd Froehlich



Development and Application of An Efficient and Effective Approach to Simulate the Hyperspectral Reflectance Over Large Temporal and Spatial Scales  

NASA Astrophysics Data System (ADS)

Atmospheric and surface properties have been measured from space with various spatial resolutions for decades. It is very challenging to derive the mean solar spectral radiance or reflectance over large temporal and spatial scales by explicit radiative transfer computations from the large volume of instantaneous data, especially at high spectral resolution. We propose a procedurally simple but effective method to compute the solar spectral reflectance in large climate domains, in which the probability distribution function (PDF) of cloud optical depth is used to account for the wide variation of cloud properties in different sensor footprints, and to avoid the repeated computations for footprints with similar conditions. This approach is tested with MODIS/CERES data and evaluated with SCIAMACHY measured spectral reflectance. The mean difference between model and observation is about 3% for the monthly global mean reflectance. This PDF-based approach provides a simple, fast, and effective way to simulate the mean spectral reflectance over large time and space scales with a large volume of high-resolution satellite data. The application of this approach to the hyperspectral simulation for NASA's CLARRREO project is demonstrated.

Jin, Z.



The importance of accurate road data for spatial applications in public health: customizing a road network  

PubMed Central

Background Health researchers have increasingly adopted the use of geographic information systems (GIS) for analyzing environments in which people live and how those environments affect health. One aspect of this research that is often overlooked is the quality and detail of the road data and whether or not it is appropriate for the scale of analysis. Many readily available road datasets, both public domain and commercial, contain positional errors or generalizations that may not be compatible with highly accurate geospatial locations. This study examined the accuracy, completeness, and currency of four readily available public and commercial sources for road data (North Carolina Department of Transportation, StreetMap Pro, TIGER/Line 2000, TIGER/Line 2007) relative to a custom road dataset which we developed and used for comparison. Methods and Results A custom road network dataset was developed to examine associations between health behaviors and the environment among pregnant and postpartum women living in central North Carolina in the United States. Three analytical measures were developed to assess the comparative accuracy and utility of four publicly and commercially available road datasets and the custom dataset in relation to participants' residential locations over three time periods. The exclusion of road segments and positional errors in the four comparison road datasets resulted in between 5.9% and 64.4% of respondents lying farther than 15.24 meters from their nearest road, the distance of the threshold set by the project to facilitate spatial analysis. Agreement, using a Pearson's correlation coefficient, between the customized road dataset and the four comparison road datasets ranged from 0.01 to 0.82. Conclusion This study demonstrates the importance of examining available road datasets and assessing their completeness, accuracy, and currency for their particular study area. This paper serves as an example for assessing the feasibility of readily available commercial or public road datasets, and outlines the steps by which an improved custom dataset for a study area can be developed.

Frizzelle, Brian G; Evenson, Kelly R; Rodriguez, Daniel A; Laraia, Barbara A



Frequency assessment of spatially distributed generations of flood scenarios: an application on Italian territory  

NASA Astrophysics Data System (ADS)

The flooding risk impact on society cannot be understated: it influences land use and territorial planning and development at both physical and regulatory levels. To cope with it, a variety of actions can be put in place, involving multidisciplinary competences. Mitigation measures goes from the improvement of monitoring systems to the development of hydraulic structures, throughout land use restrictions, civil protection and insurance plans. All of those options present social and economic impacts, either positive or negative, whose proper estimate should rely on the assumption of appropriate - present and future - scenarios, i.e. quantitative event descriptions in terms of i) the flood hazard, with its probability of occurrence, extension, intensity, and duration, ii) the exposed values and iii) their vulnerability. At present, initial attention has been devoted to the design of flood scenarios, or ensembles of them, and to the evaluation of their frequency of occurrence. In the present work, a model for spatially distributed flood scenarios generation and frequency assessment is proposed and applied to the Italian territory. The study area has been divided into homogeneous regions according to their hydrologic, orographic and meteoclimatic characteristics. A statistical model for flood scenarios simulation has been implemented throughout a conditional approach based on MCMC simulations by using i) a historical flood events catalogue; ii) a homogeneous regions correlation matrix; and iii) an auxiliary variables data set. In this framework, the role of the information stored in the historical flood events catalogue "Aree Vulnerate Italiane" (AVI,, produced by the Italian National Research Council, is of crucial importance.

Lomazzi, M.; Roth, G.; Rudari, R.; Taramasso, A. C.; Ghizzoni, T.; Benedetti, R.; Espa, G.; Terpessi, C.



Spatial Frequency Domain Imaging: Applications in Preclinical Models of Alzheimer's Disease  

NASA Astrophysics Data System (ADS)

A clinical challenge in Alzheimer's disease (AD) is diagnosing and treating patients earlier, before symptoms of cognitive dysfunction occur. A good screening test would be sensitive to the AD brain pathology, safe, and cost-effective. Diffuse optical imaging, which measures how non-ionizing light is absorbed and scattered in tissue, may fulfill these three parameters. We imaged the brains of transgenic AD mouse models in vivo with a quantitative, camera-based, diffuse optical imaging technology called spatial frequency domain imaging (SFDI) to characterize near-infrared (650-970nm) optical biomarkers of AD. Compared to age-matched control mice, we found a decrease in light absorption --- due to lower oxygenated and total hemoglobin concentrations in the brain --- correlating to decreased blood vessel volume and density in histology. Light scattering also increased in AD mice, correlating to brain structural changes caused by neuron loss and activation of inflammatory cells. Furthermore, inhaled gas challenges revealed brain vascular function was diminished. To investigate how AD affects the small changes in blood perfusion caused by increased brain activity, we built a new SFDI system from a commercial light-emitting diode microprojector and off-the-shelf optical components and cameras to measure optical properties in the visible range (460-632nm). Our measurements showed a reduced amplitude and duration of blood vessel dilation to increased brain activity in the AD mice. Altogether, this work increased our understanding of AD pathogenesis, explored optical biomarkers of AD, and improved technology access to other research labs. These results and technologies can further be used to facilitate longitudinal drug therapy trials in mice and provide a roadmap to diffuse optical spectroscopy studies in humans.

Lin, Alexander Justin


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

SciTech Connect

Highlights: Black-Right-Pointing-Pointer Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. Black-Right-Pointing-Pointer Traditional non-spatial regression models may not provide sufficient information for better solid waste management. Black-Right-Pointing-Pointer Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. Black-Right-Pointing-Pointer Significances of global parameters may diminish at local scale for some provinces. Black-Right-Pointing-Pointer 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 scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.

Keser, Saniye [Department of Environmental Engineering, Middle East Technical University, 06800 Ankara (Turkey); Duzgun, Sebnem [Department of Mining Engineering, Middle East Technical University, 06800 Ankara (Turkey); Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara (Turkey); Aksoy, Aysegul, E-mail: [Department of Environmental Engineering, Middle East Technical University, 06800 Ankara (Turkey)



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

NASA Astrophysics Data System (ADS)

The UV laser system has been specifically designed for advanced rf gun applications, with a special emphasis on the production of high-brightness electron beams for free-electron lasers and Compton scattering light sources. The laser pulse can be shaped to a flat-top in both space and time with a duration of 10 ps FWHM, rise and fall times under 1 ps, and pulse energy of 50 micro-joules at 261.75 nm. A fiber oscillator and amplifier system generates a chirped pump pulse at 1047 nm; stretching is achieved in a chirped fiber Bragg grating; recompression to 1 ps FWHM is achieved with a single multi-layer dielectric grating based compressor. A two stage harmonic converter frequency quadruples the beam. Temporal shaping is accomplished with a Michelson-based ultrafast pulse stacking device with nearly 100% throughput.

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



Sampling from Spatial Databases  

Microsoft Academic Search

Techniques for obtaining random point samples from spatial databases are described. Random points are sought from a continuous domain that satisfy a spatial predicate which is represented in the database as a collection of polygons. Several applications of spatial sampling are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). Two

Frank Olken; Doron Rotem



Application of Spatially Distributed Hydrological Models in Ungauged Basins: an Approach to Minimize Predictive Uncertainty  

NASA Astrophysics Data System (ADS)

The quantification of stream flow in ungauged basins is one of the most challenging tasks in surface water hydrology due to non-availability of data and system heterogeneity. Therefore, the major focus of studies in ungauged basins is to develop appropriate tools for predicting accurate hydrologic response in the absence of observed data. A variety of simulation models, ranging from simple empirical models to complex physics based distributed models, are available for generating watershed response. Even though physics based distributed hydrologic models are considered best suited for the ungauged basins, uncertainty in model simulations, in the absence of any parameter estimations reflecting accurate watershed characteristics, may be very high. A successful application of these models in making hydrologic response predictions in ungauged basins requires reducing number of parameters and output uncertainty. This can be achieved by a stochastic validation of the model in the absence of observed watershed data. However, stochastic validation of model requires sufficient knowledge about the model parameters in terms of their probability distribution, which is generally not available. The current study proposes a method to minimize the predictive uncertainty of distributed hydrologic models by deriving probability distribution of sensitive parameters. The proposed methodology employs simulations of the hydrologic model using samples of parameter sets generated by Latin hypercube sampling (LHS). Initially uniform probability distribution function (PDF) for the model parameters are assumed in the absence of known PDF, for LHS. The Sobol's sensitivity method is employed to prune the number of parameters used for subsequent analysis. The posterior probability distributions of the sensitive parameters are computed using a Bayesian approach. In addition, likelihood values of simulations are used for sizing the parameter range, thereby reducing the predictive uncertainty. The updating of the PDF is continued till both the distributions (prior and posterior) converge in successive cycles of simulations. To facilitate stochastic validation of the model in ungauged basins, the PDF of the parameters are obtained for a gauged basin and transferred to hydrologically similar ungauged basins after regionalization. The proposed methodology is illustrated through a case study of two independent sub-basins in the St. Joseph River watershed, USA. The soil and water assessment tool (SWAT) model is considered for the application. The Sobol's sensitivity analysis was performed for 13 parameters that influenced the stream flow simulation in the SWAT model. The appropriate ranges of parameters which resulted in minimum uncertainty were identified for the three most sensitive parameters and the corresponding PDF's were derived. Using the derived PDF and compressed ranges of parameters, simulations of the 2nd sub-basin was performed, thereby facilitating a stochastic validation of the model. The results of the study are encouraging and suggest that the proposed method can be employed as a viable approach for building confidence in the application of distributed watershed models in ungauged basins.

Raj, C.; Sudheer, K.; Chaubey, I.




Microsoft Academic Search

Spatial regression models incorporating non-stationarity in the regression coefficients are popular. We propose a spatial variant of the Smooth Transition AutoRegressive (STAR) model that is more parsimonious than commonly used approaches and endogenously determines the extent of spatial parameter variation. Uncomplicated estimation and inference procedures are demonstrated using a neoclassical convergence model for United States counties.

Valerien O. Pede; Raymond J. G. M. Florax; Matthew T. Holt



The spatial distribution of overweight and obesity among a birth cohort of young adult Filipinos (Cebu Philippines, 2005): an application of the Kulldorff spatial scan statistic.  


Objectives:The objectives of the study were to test for spatial clustering of obesity in a cohort of young adults in the Philippines, to estimate the locations of any clusters, and to relate these to neighborhood-level urbanicity and individual-level socioeconomic status (SES).Subjects:Data are from a birth cohort of young adult (mean age 22 years) Filipino males (n=988) and females (n=820) enrolled in the Cebu Longitudinal Health and Nutrition Survey.Methods:We used the Kulldorff spatial scan statistic to detect clusters associated with unusually low or high prevalences of overweight or obesity (defined using body mass index, waist circumference and body fat percentage). Cluster locations were compared to neighborhood-level urbanicity, which was measured with a previously validated scale. Individual-level SES was adjusted for using a principal components analysis of household assets.Results:High-prevalence clusters were typically centered in urban areas, but often extended into peri-urban and even rural areas. There were also differences in clustering by both sex and the measure of obesity used. Evidence of clustering in males, but not females, was much weaker after adjustment for SES. PMID:23817443

Dahly, D L; Gordon-Larsen, P; Emch, M; Borja, J; Adair, L S



Spatial organization of the gravitropic response in plants: applicability of the revised local curvature distribution model to Triticum aestivum coleoptiles.  


The revised local curvature distribution model, which provides accurate computer simulations of the gravitropic response of mushroom stems, was found to produce accurate simulations of the gravitropic reaction of wheat (Triticum aestivum) coleoptiles. The key feature of the mathematical model that enables it to approach universality of application is the assumption that the stem has an autonomic straightening reaction (curvature compensation or 'autotropism'). In the model, the local bending rate for any segment of the organ is determined by the difference between the 'bending signal' (generated by the gravitropic signal perception system) and a 'straightening signal' (which is proportional to the local curvature of the segment). The model reveals three major differences between the gravitropic reactions of wheat coleoptiles and Coprinus mushroom stems. First, in Coprinus, the capacity for autonomic straightening is much more concentrated in the apical region of the stem. Second, local perception of the gravitropic signal, which is necessary for exact simulation in Coprinus, is not needed in wheat coleoptiles (the corresponding constant in the model can be set to zero). Third, the transmission rate of the gravitropic signal is about seven times faster in wheat coleoptiles than in the mushroom stem. Thus, we demonstrate that a single model, depending on the values given to its parameters, is able to simulate the spatial organization of the gravitropic reaction of wheat coleoptiles and Coprinus mushroom stems. The model promises to be a valuable predictive tool in guiding future research into the gravitropic reaction of axial organs of all types. PMID:11542912

Meskauskas, A; Jurkoniene, S; Moore, D



Estimation of spatial recharge distribution using environmental isotopes and hydrochemical data, I. Mathematical model and application to synthetic data  

NASA Astrophysics Data System (ADS)

A mathematical model is proposed to estimate the spatial distribution of annual recharge rates into an aquifer using environmental isotopes and hydrochemical data. The aquifer is divided into cells within which the isotopes and dissolved constituents are assumed to undergo complete mixing. For each mixing cell mass-balance equations expressing the conservation of water, isotopes and dissolved chemicals are written. These equations are solved simultaneously for unknown rates of recharge into the various cells by quadratic programming. The degree to which individual dissolved constituents may be considered conservative is tested a-priori by means of a chemical equilibrium model such as WATEQF. Constituents which do not pass this test are either disregarded or suitably assigned a small weight in the quadratic program. In Part I, the model is applied to synthetic data corrupted by random noise and its sensitivity to input errors is examined. Part II describes an application of the model to real data from the Aravaipa Valley in southern Arizona. Adar and Neuman (this volume).

Adar, Eilon M.; Neuman, Shlomo P.; Woolhiser, David A.



Estimation of spatial covariance structures by adjoint state maximum likelihood cross-validation: 3. Application to hydrochemical and isotopic data  

NASA Astrophysics Data System (ADS)

Paper 3 of this three-part series presents applications of our adjoint state maximum likelihood cross-validation (ASMLCV) method to real data from aquifers. The Madrid basin in Spain serves as the source of information about 11 hydrochemical variables (pH, electrical conductivity, silica content, and the concentration of major ions) and two isotopes (oxygen 18 and carbon 14). Due to a lack of sufficient vertical resolution, our analysis is restricted to the horizontal plane. With the exception of oxygen 18 and silica, the variables appear to be free of a horizontal drift. No discernible directional effects are seen. All variables exhibit a large nugget effect which is indicative of background noise. We conclude that more detailed and careful sampling in three dimensions is required if groundwater quality information is to become less prone to such noise and thereby more useful in the context of quantitative hydrogeological analyses. Despite the existing noise, we are able to confirm geostatistically some (though not all) of the hypotheses advanced by others about hydrochemical evolution and isotope changes in the basin. The ability of ASMLCV to filter out spatial variations from part of the measurement noise is illustrated on carbon 14 data. The same data are also used to investigate the utility of model structure identification criteria in selecting the best among a set of alternative semivariogram models.

Samper, F. Javier; Neuman, Schlomo P.



Application of three-dimensional spatial correlation properties of coherent noise in phase noise suppression for digital holographic microscopy  

NASA Astrophysics Data System (ADS)

The inherited coherent noise degrades the phase imaging quality in digital holographic microscopy (DHM). To overcome the problem, an experimental investigation on the three-dimensional (3D) spatial correlation properties of coherent noise is carried out. Multiple blank holograms are recorded without any specimen in DHM setup by consecutively shifting camera along the optical axis, and a series of phase distribution of coherent noise can be obtained by numerical reconstruction. Then, based on the phase distributions, the lateral and longitudinal correlation properties of coherent noise are analyzed by a discrete correlation algorithm. Furthermore, a method for reducing phase noise is proposed by use of multiple holograms. Firstly, a series of holograms are recorded by shifting the camera longitudinally with the step more than longitudinal correlation length of coherent noise field. Secondly, the reconstruction of the holograms leads to a series of phase images of object, in which the coherent noise has different patterns. Consequently, by averaging the phase images, the reductions of phase noise are achieved. The applicability of the method is demonstrated by imaging of the resolution targets and the grating.

Pan, Feng; Xiao, Wen; Liu, Shuo; Rong, Lu



Modeling spatial price transmission in the grain markets of Ethiopia with an application of ARDL approach to white teff  

Microsoft Academic Search

Following the agricultural market liberalization policy, there is an emerging grain market structure in Ethiopia in which the central wholesale market exhibits concentration of power and spatial integration with the local markets. Due to this, it is hypothesized that the central wholesale market influences the long-run price movements in the local markets. The relationship can be modeled as spatial price

Kindie Getnet; Wim Verbeke; Jacques Viaene



XD(xanthene dyes)-DC-PVA (dichromated polyvinyl alcohol) for holographic recording: measurement of the spatial resolution and applications  

Microsoft Academic Search

We report on the characterization of some photopolymer recording materials based on DC-PVA films sensitized or non- sensitized by some xanthene dyes. The limit of the spatial resolution was determined for different sample preparation techniques. It is well known that the quality of the recorded hologram depends on the spatial resolution of the recording material. A bad resolution will reduce

Thierry Cornelissen; Christophe de Veuster; Jean J. Couture; Yvon L. Renotte; Yves F. Lion




Microsoft Academic Search

Until now, satellite data are only of limited use to Mid-European forest management. A major limitation is the low spatial reso lution of the commonly available satellite sensors. In this paper, we present a specific data fusion approach (local correlation model ling) which can be used to produce multispectral images with high spatial resolution based on panchromatic reference channels. Such

J. Hill; C. Diemer



Updating bird species distribution at large spatial scales: applications of habitat modelling to data from long-term monitoring programs  

Microsoft Academic Search

Mapping of species distributions at large spatial scales has been often based on the representation of gathered observations in a general grid atlas framework. More recently, subsampling and subsequent interpolation or habitat spatial modelling techniques have been incorporated in these projects to allow more detailed species mapping. Here, we explore the usefulness of data from long-term monitoring (LTM) projects, primarily

Lluís Brotons; Sergi Herrando; Magda Pla



How Students Solve Problems in Spatial Geometry while Using a Software Application for Visualizing 3D Geometric Objects  

ERIC Educational Resources Information Center

In schools, learning spatial geometry is usually dependent upon a student's ability to visualize three dimensional geometric configurations from two dimensional drawings. Such a process, however, often creates visual obstacles which are unique to spatial geometry. Useful software programs which realistically depict three dimensional geometric…

Widder, Mirela; Gorsky, Paul



Deriving Extensional Spatial Composition Tables  

Microsoft Academic Search

Spatial composition tables are fundamental tools for the realisation of qualitative spatial reasoning techniques. Studying the properties of these tables in relation to the spatial calculi they are based on is essential for understanding the applicability of these calculi and how they can be extended and generalised. An extensional interpretation of a spatial composition table is an important property that

Baher K. El-Geresy; Alia I. Abdelmoty; Andrew J. Ware



Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration  

Microsoft Academic Search

A new approach based on pulsed photoacoustic spectroscopy for non-invasively quantifying tissue chromophore concentrations with high spatial resolution has been developed. The technique is applicable to the quantification of tissue chromophores such as oxyhaemoglobin (HbO2) and deoxyhaemoglobin (HHb) for the measurement of physiological parameters such as blood oxygen saturation (SO2) and total haemoglobin concentration. It can also be used to

Jan Laufer; Dave Delpy; Clare Elwell; Paul Beard



Applications of geospatial analysis to surveillance data: a spatial examination of HIV\\/AIDS prevalence in Zambia  

Microsoft Academic Search

Techniques of spatial statistics and GIS are applied to socio-economic, demographic and HIV sentinel data to characterize\\u000a the geographical distribution of HIV prevalence in Zambia and to estimate current prevalence rates. Maps of the 4 years under\\u000a study (i.e. 1994, 1998, 2002 and 2004) reveal a spatial variation in HIV prevalence with urban and provincial districts having\\u000a higher prevalence than rural

Imelda K. Moise; Ezekiel Kalipeni


An algorithm based on spatial filter for infrared small target detection and its application to an all directional IRST system  

NASA Astrophysics Data System (ADS)

For the small targets detection in single frame infrared image, a spatial filter algorithm based on an adaptive smooth filter and the Robinson Guard spatial filter is proposed in the paper. The algorithm can detect the small targets in the undulant background effectively with little target information loss; it is implemented easily by digital processor ADSP-TS201S with high performance and successfully used in an all directional IRST system. The experiments show the effectiveness of the detection performance.

Luo, Jun-hui; Ji, Hong-bing; Liu, Jin



Spatial and temporal synthesized probability gain for middle and long-term earthquake forecast and its preliminary application  

Microsoft Academic Search

The principle of middle and long-term earthquake forecast model of spatial and temporal synthesized probability gain and the\\u000a evaluation of forecast efficiency (R-values) of various forecast methods are introduced in this paper. The R-value method, developed by Xu (1989), is further developed here, and can be applied to more complicated cases. Probability\\u000a gains in spatial and\\/or temporal domains and the

Xiao-Qing Wang; Zheng-Xiang Fu; Li-Ren Zhang; Sheng-Ping Su; Xiang Ding



SpatialBoost: Adding Spatial Reasoning to AdaBoost  

Microsoft Academic Search

SpatialBoost extends AdaBoost to incorporate spatial reasoning. We demonstrate the effective- ness of SpatialBoost on the problem of interactive image segmentation. Our application takes as input a tri-map of the original image, trains SpatialBoost on the pixels of the object and the background and use the trained classifier to classify the unlabeled pixels. The spatial reasoning is introduced in the

Shai Avidan



Analysis of the spatial climate structure from a viticultural perspective. Application to determine viticulture suitability and zonification in Extremadura (Spain)  

NASA Astrophysics Data System (ADS)

The basis for assessing the suitability for viticulture in wine regions is an accurate depiction of the temperature spatial distribution. Thus, using data for a long time internal (1980-2011) and from 117 meteorological stations, four bioclimatic indices were calculated and their spatial distribution patterns were mapped using a multivariate method, the regression-kriging technique. It was obtained that the spatial variability of climate within Extremaduran natural regions (NRs) is significant. Although the warmer conditions predominate in Extremadura, some NRs have part of their territory by up to eight climate classes; this information enables a better understanding of the viticulture suitability within each NR and delineating homogeneous zones. Finally, comparisons of Extremaduran NRs with others worlwide were conducted, which should be taken into account to select varieties and assess the possibilities of producing new wines.

Rebollo, Francisco J.; Moral, Francisco J.; Paniagua, Luís L.; García, Abelardo



Alphatome: Enhancing Spatial Reasoning  

NSDL National Science Digital Library

This article from Elizabeth E. LeClair highlights a spatial reasoning exercise and the importance of spatial reasoning ability in many scientific disciplines. The author touches on her own pedagogical experience and how she witnessed her students struggle with spatial reasoning. The article goes on to include details on a 90-minute lab session which is intended to improve spatial reasoning skills and may be applicable in a number of different science and technical classes. Useful graphics are included. This document may be downloaded in PDF file format.

Leclair, Elizabeth E.



Shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement  

Microsoft Academic Search

In the recent years, denoising based on the spatially adaptive algorithms that employ anisotropic adaption have been developed. These methods are able to match to the local statistics, preserve the edges and truly remove the noise from the texture of the images. On the other hand, a huge proportion of image enhancement methods are implemented in the sparse domains (e.g.,

Hossein Rabbani



PHD filter with diffuse spatial prior on the birth process with applications to GM-PHD filter  

Microsoft Academic Search

This paper presents a simple and efficient way to set the birth process of the Probability Hypothesis Density filter that enhances the performance of this approach when tracking multiple targets in clutter with no a priori spatial information on where targets can appear. The novelty introduced concerns the intensity of the birth Random Finite Set that models new appearing targets.

J. Houssineau; D. Laneuville



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

Microsoft Academic Search

Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as th e 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

H. J. Foster; M. J. Lees; H. S. Wheater; C. Neal; B. Reynolds



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

NASA Astrophysics Data System (ADS)

Although for large area detectors it is crucial to find an alternative to detect thermal neutrons because of the 3He 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 3He-based detectors for high flux applications. We developed a high spatial resolution prototype suitable for neutron reflectometry instruments. It exploits solid 10B-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.

Piscitelli, F.; Buffet, J. C.; Clergeau, J. F.; Cuccaro, S.; Guérard, B.; Khaplanov, A.; La Manna, Q.; Rigal, J. M.; Van Esch, P.



Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.  


This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations. PMID:21879851

Hassan, M Manzurul; Atkins, Peter J



Spatial Databases - Accomplishments and Research Needs  

Microsoft Academic Search

Spatial databases, addressing the growing data management and analysis needs of spatial applications such as geographic information systems, have been an active area of research for more than two decades. This research has produced a taxonomy of models for space, spatial data types and operators, spatial query languages and processing strategies, as well as spatial indexes and clustering techniques. However,

Shashi Shekhar; Sanjay Chawla; Sivakumar Ravada; Andrew Fetterer; Xuan Liu; Chang-tien Lu



Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data  

NASA Technical Reports Server (NTRS)

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Hood, Kenneth Brown (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor); Johnson, James William (Inventor)



Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data  

NASA Technical Reports Server (NTRS)

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Hood, Kenneth Brown (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor); Johnson, James William (Inventor)



On the application of a spatial chaotic model for detecting landcover changes in synthetic aperture radar images  

NASA Astrophysics Data System (ADS)

We present a change detection method for terrain covers from multi-temporal SAR images based on a spatial chaotic model which is known to adequately characterize the coherent process of SAR imaging. The major problem of SAR change detection rises from both the presence of speckle noise and the pixel mis-registration that are commonly seen in the remote sensing image. By means of chaotic model, we first transform the images to fractal domain and then perform the CFAR detection. Simulated tests are conducted to quantitatively evaluate the impacts of these two major error sources on detection rate. Results from satellite SAR for landcover change detection clearly show that the proposed algorithm not only the speckle noise can be effectively suppressed without scarifying the spatial resolution; the excruciating mis-registration error was taken into account and removed.

Chou, Nien-Shiang; Tzeng, Yu-Chang; Chen, Kun Shan; Wang, Chih-Tien; Fan, Kuo-Chin



A web-based, component-oriented application for spatial modelling of habitat suitability of mosquito vectors  

Microsoft Academic Search

This paper proposes a web-enabled computational environment for the spatial modelling of habitat suitability of mosquito vectors. Under a component-based architecture and implemented using an object-oriented data model, we integrate database interfaces, Web feature services (WFS) based on the open GIS consortium (OGC) protocols, and the data-mining tool WEKA, coupled through Java servlet scripts (JSP). The prototype, based exclusively on

P. Zeilhofer; P. S. Arraes Neto; W. Y. Maja; D. A. Vecchiato



Modeling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica  

Microsoft Academic Search

The objective of this paper is to simulate the location of land-use change, specifically forest disturbance, in Costa Rica over several decades. This paper presents a GIS-based model, GEOMOD2, which quantifies factors associated with land-use, and simulates the spatial pattern of land-use forward and backward in time. GEOMOD2 reads rasterized maps of land-use and other biogeophysical attributes to determine empirically

R. Gil Pontius Jr; Joseph D. Cornell; Charles A. S. Hall



Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs and InP substrates  

Microsoft Academic Search

The fabrication and characterization of an optically addressable deformable mirror for spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5-mum thick grid of patterned photoresist supports the 2-mum thick aluminized Mylar membrane. A conductive ZnO layer is placed on the backside of the

B. Haji-Saeed; R. Kolluru; Dana Pyburn; R. Leon; S. K. Sengupta; Markus E. Testorf; W. D. Goodhue; Jed Khoury; Alvin J. Drehman; Charles L. Woods; John Kierstead



Regional Variation in the Severity of Pesticide Exposure Outcomes: Applications of Geographic Information Systems and Spatial Scan Statistics  

PubMed Central

Introduction In a previous study, Geographic Information Systems (GIS) and spatial scan statistics were utilized to assess regional clustering of symptomatic pesticide exposure incidents that were reported to a state Poison Control Center (PCC) during a single year. In the current study, we analyzed five subsequent years of PCC data to test whether there are significant geographic differences in pesticide exposure incidents resulting in serious (moderate, major, and fatal) medical outcomes. Methods A Poison Control Center provided data on unintentional pesticide exposure incidents for the time period 2001?2005. Data were abstracted to identify the geographic location of the caller, the location where the exposure occurred, the exposure route, and the medical outcome. Results The results yielded 273 incidents resulting in moderate (n=261), major effects (n=10), or fatalities (n=2). Analysis of these data using spatial scan statistics resulted in the identification of a geographic area consisting of 2 adjacent counties (one urban, one rural) where statistically significant clustering of serious outcomes was observed. The relative risk of moderate, major, and fatal outcomes was 2.0 in this spatial cluster (p=0.0005). Conclusions Poison Control Center data, GIS, and spatial scan statistics can be effectively utilized to identify clustering of serious incidents involving human exposure to pesticides. These analyses may be useful for public health officials to target preventive interventions. Further investigation is warranted to better understand the potential explanations for geographical clustering, and to assess whether preventive interventions have an impact on reducing pesticide exposure incidents resulting in serious medical outcomes.

Sudakin, Daniel L.



Combined application of social network and cluster detection analyses for temporal-spatial characterization of animal movements in Salamanca, Spain.  


Social network analysis was used in combination with techniques for detection of temporal-spatial clusters to identify operations at high risk of receiving or dispatching pigs, from January through December 2005, in the Spanish province of Salamanca. The temporal-spatial structure of the network was explicitly analyzed to estimate the statistical significance of observed clusters. Significant (P<0.01) temporal-spatial clusters identified were grouped into two compartments based on the nature and extent of the contacts among operations within the clusters. One of the compartments was identified from January through April, included a high proportion of extensive farms (0.39), and was likely to be related with the production and trade of Iberian pigs. The other compartment encompassed a smaller proportion of extensive farms (0.11: P<0.01), took place from May through December, and was probably related to intensive production systems. Analysis of a sub-section of the network, which was selected based on the administrative division of Spain, yielded to the identification of a different set of clusters, showing that results of social network analysis may be sensitive to the extension of the information used in the analysis. The approach presented here will be useful for the implementation of differential surveillance, prevention, and control strategies at specific times and locations, which will aid in the optimization of human and financial resources. PMID:19500865

Martínez-López, B; Perez, A M; Sánchez-Vizcaíno, J M



A methodology to infer gene networks from spatial patterns of expression - An application to fluorescence in situ hybridization images  

PubMed Central

The proper functional development of a multicellular organism depends on an intricate network of interacting genes that are expressed in accurate temporal and spatial patterns across different tissues. Complex inhibitory and excitatory interactions among genes control the territorial differences that explain specialized cell fates, embryo polarization and tissues architecture in metazoan. Given the nature of the regulatory gene networks, similarity of expression patterns can identify genes and with similar roles. The inference and analysis of the gene interaction networks through complex networks tools can reveal important aspects of the biological system modeled. Here we suggest an image analysis pipeline to quantify co-localization patterns in in situ hybridization images of Drosophila embryos and, based on these patterns, infer gene networks. We analyze the spatial dispersion of the gene expression and show the gene interaction networks for different developmental stages. Our results suggest that the inference of developmental networks based on spatial expression data are biologically relevant and represents a potential tool for the understanding of animal development.

Campiteli, Monica Guimaraes; Comin, Cesar Henrique; Costa, Luciano da Fontoura; Babu, M Madan; Cesar, Roberto Marcondes



Privacy Preserving Spatial Outlier Detection  

Microsoft Academic Search

Spatial outlier detection can be applied in the finding of terrorist activities and the forecast of abnormal climate activity etc. For protecting privacy information and mining spatial outliers, we presented privacy preserving spatial outlier mining algorithm. By the definition and application of secure multiparty computation protocols based on semi-honest model, we realized the preserving of the privacy information. We utilized

Anrong Xue; Xiqiang Duan; Handa Ma; Weihe Chen; Shiguang Ju



Fusion of Fuzzy Spatial Relations  

NASA Astrophysics Data System (ADS)

Spatial relations are essential for understanding the image configuration and modeling common sense knowledge. In most of existing methods, topological, directional and distance spatial relations are computed separately as they have separate application domains. Introduction of Temporal Geographic Information System (TGIS), spatio-temporal reasoning and study of spatio-temporal relations required the computation of topological and metric spatial relations together.

Salamat, Nadeem; Zahzah, El-Hadi


Spatial and temporal distribution of solute leaching in heterogeneous soils: analysis and application to multisampler lysimeter data  

NASA Astrophysics Data System (ADS)

Accurate assessment of the fate of salts, nutrients, and pollutants in natural, heterogeneous soils requires a proper quantification of both spatial and temporal solute spreading during solute movement. The number of experiments with multisampler devices that measure solute leaching as a function of space and time is increasing. The breakthrough curve (BTC) can characterize the temporal aspect of solute leaching, and recently the spatial solute distribution curve (SSDC) was introduced to describe the spatial solute distribution. We combined and extended both concepts to develop a tool for the comprehensive analysis of the full spatio-temporal behavior of solute leaching. The sampling locations are ranked in order of descending amount of total leaching (defined as the cumulative leaching from an individual compartment at the end of the experiment), thus collapsing both spatial axes of the sampling plane into one. The leaching process can then be described by a curved surface that is a function of the single spatial coordinate and time. This leaching surface is scaled to integrate to unity, and termed S can efficiently represent data from multisampler solute transport experiments or simulation results from multidimensional solute transport models. The mathematical relationships between the scaled leaching surface S, the BTC, and the SSDC are established. Any desired characteristic of the leaching process can be derived from S. The analysis was applied to a chloride leaching experiment on a lysimeter with 300 drainage compartments of 25 cm 2 each. The sandy soil monolith in the lysimeter exhibited fingered flow in the water-repellent top layer. The observed S demonstrated the absence of a sharp separation between fingers and dry areas, owing to diverging flow in the wettable soil below the fingers. Times-to-peak, maximum solute fluxes, and total leaching varied more in high-leaching than in low-leaching compartments. This suggests a stochastic-convective transport process in the high-flow streamtubes, while convection-dispersion is predominant in the low-flow areas. S can be viewed as a bivariate probability density function. Its marginal distributions are the BTC of all sampling locations combined, and the SSDC of cumulative solute leaching at the end of the experiment. The observed S cannot be represented by assuming complete independence between its marginal distributions, indicating that S contains information about the leaching process that cannot be derived from the combination of the BTC and the SSDC.

de Rooij, Gerrit H.; Stagnitti, Frank



Development of Knowledge Intensive Applications for Hospital  

NASA Astrophysics Data System (ADS)

Most studies of medical intelligence system have focused on the development of backend data repositories rather than frontend user applications. Also, they tend to lack systematic development models which demonstrate how user requirements inform system design and implementation. For these reasons, it is highly desirable to show the process of eliciting knowledge requirements in addition to the development process for knowledge-intensive applications. This research covers the implementation of a medical intelligence system based on analysis of knowledge requirements such as OLAP (On-line Analytical Processing) fundamental functionalities and knowledge types. The proposed medical intelligence system provides health care providers and their supporters with the ability to draw meaningful insights from very large, complex data sets. A real life case is presented to illustrate the system’s practical usage. Six application packages are defined, namely: explorer, analyzer, reporter, statistician, visualizer, and meta administrator. Finally, the study concludes with an evaluation of the developed system and future research directions.

Kim, Jongho; Hong, Han-Kuk; Jang, Gil-Sang; Kim, Joung Yeon; Kim, Taehun


Exploring new methods to exploit the relationship between cloud spatial structure and their spectral radiative signature in remote sensing and energy budget applications  

NASA Astrophysics Data System (ADS)

In this work, we use 3-dimensional (3-D) radiative transfer modeling to investigate the effects of inhomogeneous cloud spatial structure on spectral signatures of radiative quantities of a cloud field such as irradiance, heating rate and cloud radiative effect. The investigation covers different spectral regions, whose radiative properties are dominated by different effects (e.g., molecular scattering, aerosol scattering and absorption, gas absorption and cloud absorption). We define a number of metrics to describe the 3-D cloud spatial structure, which includes cloud optical thickness, cloud size, cloud-to-cloud distance and spatial pattern of the cloud field. Then we use four inhomogeneous cloud cases, three idealized and one observed, with increasing complexity to access the sensitivities of the spectral radiative signatures in each spectral region on each metric. Thus we are able to discuss how each aspect of the 3-D cloud spatial structure gives rise to the spectral radiative signatures in these different spectral regions. Specifically, we explore the spectral signature of the net horizontal photon transport for each spectral region and its dependence on each of the metrics. The results suggest that a limited number of metrics may be sufficient to explain the behavior of the net horizontal photon transport for a range of cloud structure. Thus we propose a preliminary parameterization for simplifying the 3-D cloud effects in cloud-aerosol remote sensing applications. Secondly, we investigate the spatial distribution of heating rates when inhomogeneous clouds are present for all these spectral regions. We discuss how the 3-D cloud heating rate differs from the 1-D plane-parallel counterpart and how this difference can be understood in the framework of the previously defined metrics. The results provide insights into how the presence of clouds could change the distribution of energy within the atmosphere and thus influences atmospheric dynamics. Finally, we investigate the cloud radiative effects for realistic cloud scenes and introduce a new spectral parameterization for cloud heterogeneity effect that is applicable for both remote sensing and energy budget studies.

Song, Shi; Schmidt, K. Sebastian; Pilewskie, Peter; Coddington, Odele



Spatial intelligence with spatial statistics  

Microsoft Academic Search

With the advent of Web 2.0, new technologies for spatial data service, and demanding needs in spatial data sharing, and advanced analysis, both geographic information system and spatial statistics are facing challenges from different disciplines never met before. Due to their mutual beneficial roles in highlevel decision making, it's quite essential to make research on the integration of Web 2.0

Xu Zhang; Shuming Bao; Xinyan Zhu; Kehua Su



Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications  

PubMed Central

Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.

Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.



Continuous-time Monte Carlo and spatial ordering in driven lattice gases: Application to driven vortices in periodic superconducting networks  

NASA Astrophysics Data System (ADS)

We consider the two-dimensional (2D) classical lattice Coulomb gas as a model for magnetic field induced vortices in 2D superconducting networks. Two different dynamical rules are introduced to investigate driven diffusive steady states far from equilibrium as a function of temperature and driving force. The resulting steady states differ dramatically depending on which dynamical rule is used. We show that the commonly used driven diffusive Metropolis Monte Carlo dynamics contains unphysical intrinsic randomness that destroys the spatial ordering present in equilibrium (the vortex lattice) over most of the driven phase diagram. A continuous time Monte Carlo (CTMC) method is then developed, which results in spatially ordered driven states at low temperature in finite sized systems. We show that CTMC is the natural discretization of continuum Langevin dynamics, and argue that it gives the correct physical behavior when the discrete grid represents the minima of a periodic potential. We use detailed finite size scaling methods to analyze the spatial structure of the steady states. We find that finite size effects can be subtle and that very long simulation times can be needed to arrive at the correct steady state. For particles moving on a triangular grid, we find that the ordered moving state is a transversely pinned smectic that becomes unstable to an anisotropic liquid on sufficiently large length scales. For particles moving on a square grid, the moving state is a similar smectic at large drives, but we find evidence for a possible moving solid at lower drives. We find that the driven liquid on the square grid has long range hexatic order, and we explain this as a specifically nonequilibrium effect. We show that, in the liquid, fluctuations about the average center of mass motion are diffusive in both the transverse and longitudinal directions.

Gotcheva, Violeta; Wang, Yanting; Wang, Albert T. J.; Teitel, S.



Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs and InP substrates  

NASA Astrophysics Data System (ADS)

The fabrication and characterization of an optically addressable deformable mirror for spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5-?m thick grid of patterned photoresist supports the 2-?m thick aluminized Mylar membrane. A conductive ZnO layer is placed on the backside of the GaAs wafer. Similar devices were also fabricated with InP. A standard Michelson interferometer is used to measure mirror deformation data as a function of illumination, applied voltage and frequency. A simplified analysis of device operation is also presented.

Haji-Saeed, B.; Kolluru, R.; Pyburn, Dana; Leon, R.; Sengupta, S. K.; Testorf, Markus E.; Goodhue, W. D.; Khoury, Jed; Drehman, Alvin J.; Woods, Charles L.; Kierstead, John



Applications of the normal-incidence rotating-sample ellipsometer to high- and low-spatial-frequency gratings  

NASA Astrophysics Data System (ADS)

The normal-incidence rotating-sample ellipsometer is an instrument that can be used to characterize grating surfaces from the measured ratio rho of complex reflection coefficients ry/r x of light polarized perpendicular and parallel to the grating groove direction. Experimental results at different wavelengths for different gratings with spatial frequencies from 150 to 5880 grooves/mm are presented. The groove depth of the 5880-grooves/mm gold-coated grating can be estimated from the measured rho and rigorous grating theory.

Cui, Y.; Azzam, R. M. A.



A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment  

NASA Technical Reports Server (NTRS)

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; Eck, T. F.; Holben, B. N.; Kahn, R. A.



A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications  

PubMed Central

Forest surveys provide critical information for many diverse interests. Data are often collected from samples, and from these samples, maps of resources and estimates of aerial totals or averages are required. In this paper, two approaches for mapping and estimating totals; the spatial linear model (SLM) and k-NN (k-Nearest Neighbor) are compared, theoretically, through simulations, and as applied to real forestry data. While both methods have desirable properties, a review shows that the SLM has prediction optimality properties, and can be quite robust. Simulations of artificial populations and resamplings of real forestry data show that the SLM has smaller empirical root-mean-squared prediction errors (RMSPE) for a wide variety of data types, with generally less bias and better interval coverage than k-NN. These patterns held for both point predictions and for population totals or averages, with the SLM reducing RMSPE from 9% to 67% over some popular k-NN methods, with SLM also more robust to spatially imbalanced sampling. Estimating prediction standard errors remains a problem for k-NN predictors, despite recent attempts using model-based methods. Our conclusions are that the SLM should generally be used rather than k-NN if the goal is accurate mapping or estimation of population totals or averages.

Ver Hoef, Jay M.; Temesgen, Hailemariam



Texture-based measurement of spatial frequency response using the dead leaves target: extensions, and application to real camera systems  

NASA Astrophysics Data System (ADS)

The dead leaves model was recently introduced as a method for measuring the spatial frequency response (SFR) of camera systems. The target consists of a series of overlapping opaque circles with a uniform gray level distribution and radii distributed as r-3. Unlike the traditional knife-edge target, the SFR derived from the dead leaves target will be penalized for systems that employ aggressive noise reduction. Initial studies have shown that the dead leaves SFR correlates well with sharpness/texture blur preference, and thus the target can potentially be used as a surrogate for more expensive subjective image quality evaluations. In this paper, the dead leaves target is analyzed for measurement of camera system spatial frequency response. It was determined that the power spectral density (PSD) of the ideal dead leaves target does not exhibit simple power law dependence, and scale invariance is only loosely obeyed. An extension to the ideal dead leaves PSD model is proposed, including a correction term to account for system noise. With this extended model, the SFR of several camera systems with a variety of formats was measured, ranging from 3 to 10 megapixels; the effects of handshake motion blur are also analyzed via the dead leaves target.

McElvain, Jon; Campbell, Scott P.; Miller, Jonathan; Jin, Elaine W.



The influence of spatial pulsed magnetic field application on neuropathic pain after tibial nerve transection in rat.  


The purpose of the study was to examine the influence of the spatial variable magnetic field (induction: 150-300?µT, 80-150?µT, 20-80?µT; frequency 40?Hz) on neuropathic pain after tibial nerve transection. The experiments were carried out on 64 male Wistar C rats. The exposure of animals to magnetic field was performed 1?d/20?min., 5?d/week, for 28?d. Behavioural tests assessing the intensity of allodynia and sensitivity to mechanical and thermal stimuli were conducted 1?d prior to surgery and 3, 7, 14, 21 and 28?d after the surgery. The extent of autotomy was examined. Histological and immunohistochemical analysis was performed. The use of extremely low-frequency magnetic fields of minimal induction values (20-80?µT/40?Hz) decreased pain in rats after nerve transection. The nociceptive sensitivity of healthy rats was not changed following the exposition to the spatial magnetic field of the low frequency. The results of histological and immunohistochemical investigations confirm those findings. Our results indicate that extremely low-frequency magnetic field may be useful in the neuropathic pain therapy. PMID:23781991

Szajkowski, Sebastian; Marcol, Wies?aw; W?aszczuk, Adam; Cie?lar, Grzegorz; Pietrucha-Dutczak, Marita; Siero?, Aleksander; Lewin-Kowalik, Joanna



Spatial cognition  

NASA Technical Reports Server (NTRS)

Spatial cognition is the ability to reason about geometric relationships in the real (or a metaphorical) world based on one or more internal representations of those relationships. The study of spatial cognition is concerned with the representation of spatial knowledge, and our ability to manipulate these representations to solve spatial problems. Spatial cognition is utilized most critically when direct perceptual cues are absent or impoverished. Examples are provided of how human spatial cognitive abilities impact on three areas of space station operator performance: orientation, path planning, and data base management. A videotape provides demonstrations of relevant phenomena (e.g., the importance of orientation for recognition of complex, configural forms). The presentation is represented by abstract and overhead visuals only.

Kaiser, Mary Kister; Remington, Roger



Spatial and temporal flushing time approach in estuaries influenced by river and tide. An application in Suances Estuary (Northern Spain)  

NASA Astrophysics Data System (ADS)

Since Water Policies around the world establish the need to manage the aquatic systems through the use of water bodies, a hydromorphological descriptor such as the flushing time may be utilized as a good homogeneity and water quality criterion to distinguish between different types of water bodies. In order to achieve this task, a methodological procedure has been proposed involving a hydrodynamic forcing analysis, an approach to calculate flushing time and a sensitivity analysis of the results applied to the Suances Estuary. This method allows taking into account the different spatial regions on an estuary and the temporal variations of the main forcing. Consequently, the role of bathymetry, freshwater river inflows and oceanic tides on the flushing time is investigated using a two-dimensional numerical model. The hydrodynamic module integrates the depth-averaged mass and momentum equations in the time and space domains as well the transport module solves the depth-averaged advection-diffusion equation. Both modules were calibrated and validated using field data collected during spring and neap tidal cycles. Water levels and current velocities were used in the hydrodynamic module while salinities were compared in the transport module. In order to characterize the spatial variation in water renewal conditions, several boxes were selected along the estuary to evaluate the flushing time. The mass reduction is monitored in time and the flushing time at each part of the estuary was computed for several scenarios and analyzed with a multi-sensitivity analysis. Most of the river estuary basins in Northern Spain are characterized by their small surface area, short length and steepness, leading to a rapid hydrological response to rainfall and, consequently, a high variability in the river flow. During extensive dry periods during which the river flow is very small, pollutants could remain for long periods in the estuary posing an environmental risk.

Bárcena, Javier F.; García, Andrés; Gómez, Aina G.; Álvarez, César; Juanes, José A.; Revilla, José A.



The Impacts of Map-Oriented Internet Applications on Internet Clients, Map Servers and Spatial Database Systems  

Microsoft Academic Search

The presentation of simple maps on Internet web sites has become very popular in the lastfew years. With an increasing complexity of the Internet applications, also the demands onthe presentation of the maps are growing: a sophisticated interaction, an extensiveadaptability, and the support of dynamically changing maps are typical examples. Anarchitecture, which is able to fulfil such requirements, consists of

Thomas Brinkhoff



Spatial Displays and Spatial Instruments  

NASA Technical Reports Server (NTRS)

The conference proceedings topics are divided into two main areas: (1) issues of spatial and picture perception raised by graphical electronic displays of spatial information; and (2) design questions raised by the practical experience of designers actually defining new spatial instruments for use in new aircraft and spacecraft. Each topic is considered from both a theoretical and an applied direction. Emphasis is placed on discussion of phenomena and determination of design principles.

Ellis, Stephen R. (editor); Kaiser, Mary K. (editor); Grunwald, Arthur J. (editor)



Multifractality in Seismicity Spatial Distributions: Significance and Possible Precursory Applications as Found for Two Cases in Different Tectonic Environments  

NASA Astrophysics Data System (ADS)

We explore fractal properties of two observed seismicity distributions prior to the 2003 M w 7.4 Colima, Mexico and 1992 M w 7.3 Landers, USA earthquakes, together with several mathematical fractal distributions and two non-fractal ones, in order to estimate minimum reliable sample sizes, determine whether fractality for observed seismicity is essentially different from random uniform distributions, and explore the possibility of extracting premonitory information from fractal characteristics of seismicity before large earthquakes. Sample sizes above 800 events for whole catalogs appear to be sufficient to maintain ordered multifractality and to yield dimension estimates that vary smoothly and reliably. Fractal estimates appear to be best for whole catalogs that include aftershocks. The fractal characteristics of spatial distributions of seismicity are essentially different from those of the uniform random distribution, which is the null hypothesis of a non-fractal distribution with minimum information. The fractal dimensions and afractality measures of seismicity distributions change with time and show distinctive behaviors associated with foreshocks and main events, although these behaviors are different for each example. Results suggest the possibility of a priori identification of foreshocks to large earthquakes. A combination of fractal dimension and afractality measures over time may be helpful in large earthquake premonitory studies.

Márquez-Rámirez, Víctor Hugo; Nava Pichardo, F. Alejandro; Reyes-Dávila, Gabriel



The spatial-temporal variations in optical properties of atmosphere aerosols over China and its application in remote sensing  

NASA Astrophysics Data System (ADS)

The atmospheric and climate response to the aerosol forcing are assessed by climate models regionally and globally under the past, present and future conditions. However, large uncertainties exist because of incomplete knowledge concerning the distribution and the physical and chemical properties of aerosols as well as aerosol-cloud interactions. Reduction in these uncertainties requires long-term monitoring of detailed properties of different aerosol types. China is one of the heavily polluted areas with high concentration of aerosols in the world. The complex source, composition of China aerosol led to the worse accuracy of aerosol radiative forcing assessment in the world, which urgently calls for improvements on the understanding of China regional aerosol properties. The spatial-temporal properties of aerosol types over China are studied using the radiance measurements and inversions data at 4 Aerosol Robotic Network (AERONET) stations. Five aerosol classes were identified including a coarse-size dominated aerosol type (presumably dust) and four fine-sized dominated aerosol types ranging from non-absorbing to highly absorbing fine aerosols. The mean optical properties of different aerosol types in China and their seasonal variations were also investigated. Based on the cluster analysis, the improved ground-based aerosol model is applied to the MODIS dark target inversion algorithm. Validation with MODIS official product and CE318 is also included.

Chen, H.; Cheng, T.




SciTech Connect

We present a new method for the determination of the two-dimensional (2D) projected spatial distribution of globular clusters (GCs) in external galaxies. This method is based on the K-Nearest Neighbor density estimator of Dressler, complemented by Monte-Carlo simulations to establish the statistical significance of the results. We apply this method to NGC 4261, a ''test galaxy'' where significant 2D anisotropy in the GC distribution has been reported. We confirm that the 2D distribution of GC is not azimuthally isotropic. Moreover, we demonstrate that the 2D distribution departures from the average GC radial distribution results in highly significant spiral-like or broken shell features. Overall, the same perturbations are found in ''red'' and ''blue'' GCs, but with some differences. In particular, we observe a central feature, roughly aligned with the minor axis of NGC 4261, composed of red and most luminous GCs. Blue and fainter GCs are more frequent at large radial distances and follow the spiral-like features of the overall density structure. These results suggest a complex merging history for NGC 4261.

D'Abrusco, R.; Fabbiano, G.; Zezas, A.; Mineo, S.; Fragos, T.; Kim, D.-W. [Harvard-Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, MA 02138 (United States); Strader, J. [Department of Astronomy, Michigan State University, 567 Wilson Road, East Lansing, MI 48824-2320 (United States); Bonfini, P. [Physics Department and Institute of Theoretical and Computational Physics, University of Crete, 71003 Heraklion, Crete (Greece); Luo, B. [Department of Astronomy and Astrophysics, 525 Davey Lab, The Pennsylvania State University, University Park, PA 16802 (United States); King, A. [Department of Physics and Astronomy, University of Leicester, Leicester (United Kingdom)



Multivariate analysis of spatially heterogeneous phase synchronisation in complex systems: application to self-organised control of material flows in networks  

NASA Astrophysics Data System (ADS)

Networks of interacting components are a class of complex systems that has attracted considerable interest over the last decades. In particular, if the dynamics of the autonomous components is characterised by an oscillatory behaviour, different types of synchronisation can be observed in dependence on the type and strength of interactions. In this contribution, we study the transition from non-synchronised to synchronised phase dynamics in complex networks. The most common approach to quantify the degree of phase synchronisation in such systems is the consideration of measures of phase coherence which are averaged over all pairs of interacting components. However, this approach implicitly assumes a spatially homogeneous synchronisation process, which is typically not present in complex networks. As a potential alternative, two novel methods of multivariate phase synchronisation analysis are considered: synchronisation cluster analysis (SCA) and the linear variance decay (LVD) dimension method. The strengths and weaknesses of the traditional as well as both new approaches are briefly illustrated for a Kuramoto model with long-range coupling. As a practical application, we study how spatial heterogeneity influences the transition to phase synchronisation in traffic networks where intersecting material flows are subjected to a self-organised decentralised control. We find that the network performance and the degree of phase synchronisation are closely related to each other and decrease significantly in the case of structural heterogeneities. The influences of the different parameters of our control approach on the synchronisation process are systematically studied, yielding a sequence of Arnold tongues which correspond to different locking modes.

Donner, R.



Development of high-spatial and high-mass resolution mass spectrometric imaging (MSI) and its application to the study of small metabolites and endogenous molecules of plants  

SciTech Connect

High-spatial and high-mass resolution laser desorption ionization (LDI) mass spectrometric (MS) imaging technology was developed for the attainment of MS images of higher quality containing more information on the relevant cellular and molecular biology in unprecedented depth. The distribution of plant metabolites is asymmetric throughout the cells and tissues, and therefore the increase in the spatial resolution was pursued to reveal the localization of plant metabolites at the cellular level by MS imaging. For achieving high-spatial resolution, the laser beam size was reduced by utilizing an optical fiber with small core diameter (25 ?m) in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer. Matrix application was greatly improved using oscillating capillary nebulizer. As a result, single cell level spatial resolution of ~ 12 ?m was achieved. MS imaging at this high spatial resolution was directly applied to a whole Arabidopsis flower and the substructures of an anther and single pollen grains at the stigma and anther were successfully visualized. MS imaging of high spatial resolution was also demonstrated to the secondary roots of Arabidopsis thaliana and a high degree of localization of detected metabolites was successfully unveiled. This was the first MS imaging on the root for molecular species. MS imaging with high mass resolution was also achieved by utilizing the LTQ-Orbitrap mass spectrometer for the direct identification of the surface metabolites on the Arabidopsis stem and root and differentiation of isobaric ions having the same nominal mass with no need of tandem mass spectrometry (MS/MS). MS imaging at high-spatial and high-mass resolution was also applied to cer1 mutant of the model system Arabidopsis thaliana to demonstrate its usefulness in biological studies and reveal associated metabolite changes in terms of spatial distribution and/or abundances compared to those of wild-type. The spatial distribution of targeted metabolites, mainly waxes and flavonoids, was systematically explored on various organs, including flowers, leaves, stems, and roots at high spatial resolution of ~ 12-50 ?m and the changes in the abundance level of these metabolites were monitored on the cer1 mutant with respect to the wild-type. This study revealed the metabolic biology of CER1 gene on each individual organ level with very detailed high spatial resolution. The separate MS images of isobaric metabolites, i.e. C29 alkane vs. C28 aldehyde could be constructed on both genotypes from MS imaging at high mass resolution. This allows tracking of abundance changes for those compounds along with the genetic mutation, which is not achievable with low mass resolution mass spectrometry. This study supported previous hypothesis of molecular function of CER1 gene as aldehyde decarbonylase, especially by displaying hyper accumulation of aldehydes and C30 fatty acid and decrease in abundance of alkanes and ketones in several plant organs of cer1 mutant. The scope of analytes was further directed toward internal cell metabolites from the surface metabolites of the plant. MS profiling and imaging of internal cell metabolites were performed on the vibratome section of Arabidopsis leaf. Vibratome sectioning of the leaf was first conducted to remove the surface cuticle layer and it was followed by enzymatic treatment of the section to induce the digestion of primary cell walls, middle lamella, and expose the internal cells underneath to the surface for detection with the laser by LDI-MS. The subsequent MS imaging onto the enzymatically treated vibratome section allowed us to map the distribution of the metabolites in the internal cell layers, linolenic acid (C18:3 FA) and linoleic acid (C18:2 FA). The development of an assay for relative quantification of analytes at the single subcellular/organelle level by LDI-MS imaging was attempted and both plausibility and significant obstacles were seen. As a test system, native plant organelle, chloroplasts isolated from the spinach leaves were used

Jun, Ji Hyun



Effect of spatial confinement on magnetic hyperthermia via dipolar interactions in Fe3O4 nanoparticles for biomedical applications.  


In this work, the effect of nanoparticle confinement on the magnetic relaxation of iron oxide (Fe3O4) nanoparticles (NP) was investigated by measuring the hyperthermia heating behavior in high frequency alternating magnetic field. Three different Fe3O4 nanoparticle systems having distinct nanoparticle configurations were studied in terms of magnetic hyperthermia heating rate and DC magnetization. All magnetic nanoparticle (MNP) systems were constructed using equivalent ~10nm diameter NP that were structured differently in terms of configuration, physical confinement, and interparticle spacing. The spatial confinement was achieved by embedding the Fe3O4 nanoparticles in the matrices of the polystyrene spheres of 100nm, while the unconfined was the free Fe3O4 nanoparticles well-dispersed in the liquid via PAA surface coating. Assuming the identical core MNPs in each system, the heating behavior was analyzed in terms of particle freedom (or confinement), interparticle spacing, and magnetic coupling (or dipole-dipole interaction). DC magnetization data were correlated to the heating behavior with different material properties. Analysis of DC magnetization measurements showed deviation from classical Langevin behavior near saturation due to dipole interaction modification of the MNPs resulting in a high magnetic anisotropy. It was found that the Specific Absorption Rate (SAR) of the unconfined nanoparticle systems were significantly higher than those of confined (the MNPs embedded in the polystyrene matrix). This increase of SAR was found to be attributable to high Néel relaxation rate and hysteresis loss of the unconfined MNPs. It was also found that the dipole-dipole interactions can significantly reduce the global magnetic response of the MNPs and thereby decrease the SAR of the nanoparticle systems. PMID:25063092

Sadat, M E; Patel, Ronak; Sookoor, Jason; Bud'ko, Sergey L; Ewing, Rodney C; Zhang, Jiaming; Xu, Hong; Wang, Yilong; Pauletti, Giovanni M; Mast, David B; Shi, Donglu



A bottom up approach to on-road CO2 emissions estimates: improved spatial accuracy and applications for regional planning.  


On-road transportation is responsible for 28% of all U.S. fossil-fuel CO2 emissions. Mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories use spatial proxies such as population and road density to downscale national or state-level data. Such procedures introduce errors where the proxy variables and actual emissions are weakly correlated, and limit analysis of the relationship between emissions and demographic trends at local scales. We develop an on-road emission inventory product for Massachusetts-based on roadway-level traffic data obtained from the Highway Performance Monitoring System (HPMS). We provide annual estimates of on-road CO2 emissions at a 1 × 1 km grid scale for the years 1980 through 2008. We compared our results with on-road emissions estimates from the Emissions Database for Global Atmospheric Research (EDGAR), with the Vulcan Product, and with estimates derived from state fuel consumption statistics reported by the Federal Highway Administration (FHWA). Our model differs from FHWA estimates by less than 8.5% on average, and is within 5% of Vulcan estimates. We found that EDGAR estimates systematically exceed FHWA by an average of 22.8%. Panel regression analysis of per-mile CO2 emissions on population density at the town scale shows a statistically significant correlation that varies systematically in sign and magnitude as population density increases. Population density has a positive correlation with per-mile CO2 emissions for densities below 2000 persons km(-2), above which increasing density correlates negatively with per-mile emissions. PMID:23343173

Gately, Conor K; Hutyra, Lucy R; Wing, Ian Sue; Brondfield, Max N



Retrieval techniques for airborne imaging of methane concentrations using high spatial and moderate spectral resolution: application to AVIRIS  

NASA Astrophysics Data System (ADS)

Two quantitative retrieval techniques were evaluated to estimate methane (CH4) enhancement in concentrated plumes using high spatial and moderate spectral resolution data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). An Iterative Maximum a Posteriori Differential Optical Absorption Spectroscopy (IMAP-DOAS) algorithm performed well for an ocean scene containing natural CH4 emissions from the Coal Oil Point (COP) seep field near Santa Barbara, California. IMAP-DOAS retrieval precision errors are expected to equal between 0.31 to 0.61 ppm CH4 over the lowest atmospheric layer (height up to 1.04 km), corresponding to about a 30 to 60 ppm error for a 10 m thick plume. However, IMAP-DOAS results for a terrestrial scene were adveresly influenced by the underlying landcover. A hybrid approach using Singular Value Decomposition (SVD) was particularly effective for terrestrial surfaces because it could better account for spectral variability in surface reflectance. Using this approach, a CH4 plume was observed immediately downwind of two hydrocarbon storage tanks at the Inglewood Oil Field in Los Angeles, California, with a maximum near surface enhancement of 8.45 ppm above background. At COP, the distinct plume had a maximum enhancement of 2.85 ppm CH4 above background and was consistent with known seep locations and local wind direction. A sensitivity analysis also indicates CH4 sensitivity should be more than doubled for the next generation AVIRIS sensor (AVIRISng) due to improved spectral resolution and sampling. AVIRIS-like sensors offer the potential to better constrain emissions on local and regional scales, including sources of increasing concern like industrial point source emissions and fugitive CH4 from the oil and gas industry.

Thorpe, A. K.; Frankenberg, C.; Roberts, D. A.



Modelling ecosystem functions and properties at different time and spatial scales in shallow coastal lagoons: An application of the LOICZ biogeochemical model  

NASA Astrophysics Data System (ADS)

The Land-Ocean Interactions in the Coastal Zone (LOICZ) biogeochemical model (LBM) was applied at different temporal and spatial scales in 17 Italian lagoons of the LaguNet network ( A series of alternative assumptions taking into account benthic vegetation and sedimentary fluxes were introduced and compared with the classical LBM approach at various time scales. The reliability of the LBM application to the seventeen Italian lagoons was tested by comparison to a pool of shallow coastal systems from the global LOICZ database with comparable depths and sizes. The nutrient loads of the Italian sites can be considered relatively low, particularly for dissolved inorganic phosphorus (DIP). Although the median values of estimated internal transformations (source-sink) of both dissolved inorganic phosphorous and nitrogen at the LaguNet sites were comparable with the selected LOICZ sites, the positive and negative extreme values were one order of magnitude lower. Overall, the LBM applications to the Italian sites gave good quality budgets for shallow systems subjected to relatively low nutrient inputs and with a wide range of primary producer communities, including seagrass, macroalgae and phytoplankton. Furthermore, stoichiometry of Carbon:Nitrogen:Phosphorous for the different primary producer groups allowed the integration of previous studies by identifying a series of relationships between nutrient loads and ecosystem functions. To some extent, the LBM application at monthly and seasonal time scales, as shown for the Sacca di Goro lagoon, can simulate the internal variability affected by the life cycle of the dominant primary producers. Therefore, the LBM not only allows the assessment of net ecological metabolism but seems, also, capable of representing the wide range of trophic conditions associated with shallow coastal systems. Overall, the application of alternative assumptions supports the robustness of the classical LBM, although some of the simplifications that enable the LBM to function in a wide range of systems and with incomplete data sets must be considered with caution for shallow environments.

Giordani, Gianmarco; Austoni, Martina; Zaldívar, José M.; Swaney, Dennis P.; Viaroli, Pierluigi



Fusion and clustering algorithms for spatial data  

Microsoft Academic Search

Spatial clustering is an approach for discovering groups of related data points in spatial data. Spatial clustering has attracted a lot of research attention due to various applications where it is needed. It holds practical importance in application domains such as geographic knowledge discovery, sensors, rare disease discovery, astronomy, remote sensing, and so on. The motivation for this work stems

Pavani Kuntala



Application of knowledge-driven spatial modelling approaches and uncertainty management to a study of Rift Valley fever in Africa  

PubMed Central

Background There are few studies that have investigated uncertainties surrounding the scientific community's knowledge of the geographical distribution of major animal diseases. This is particularly relevant to Rift Valley fever (RVF), a zoonotic disease causing destructive outbreaks in livestock and man, as the geographical range of the disease is widening to involve previously unaffected regions. In the current study we investigate the application of methods developed in the decision sciences: multiple criteria decision making using weighted linear combination and ordered weighted averages, and Dempster-Shafer theory, implemented within the geographical information system IDRISI, to obtain a greater understanding of uncertainty related to the geographical distribution of RVF. The focus is on presenting alternate methods where extensive field data are not available and traditional, model-based approaches to disease mapping are impossible to conduct. Results Using a compensatory multiple criteria decision making model based on weighted linear combination, most of sub-Saharan Africa was suitable for endemic circulation of RVF. In contrast, areas where rivers and lakes traversed semi-arid regions, such as those bordering the Sahara, were highly suitable for RVF epidemics and wet, tropical areas of central Africa had low suitability. Using a moderately non-compensatory model based on ordered weighted averages, the areas considered suitable for endemic and epidemic RVF were more restricted. Varying the relative weights of the different factors in the models did not affect suitability estimates to a large degree, but variations in model structure had a large impact on our suitability estimates. Our Dempster-Shafer analysis supported the belief that a range of semi-arid areas were suitable for RVF epidemics and the plausibility that many other areas of the continent were suitable. Areas where high levels of uncertainty were highlighted included the Ethiopian Highlands, southwest Kenya and parts of West Africa. Conclusion We have demonstrated the potential of methods developed in the decision sciences to improve our understanding of uncertainties surrounding the geographical distribution of animal diseases, particularly where information is sparse, and encourage wider application of the decision science methodology in the field of animal health.

Clements, Archie CA; Pfeiffer, Dirk U; Martin, Vincent



A Plea for Spatial Literacy  

NSDL National Science Digital Library

This report from Nora Newcombe, which originally appeared in the Chronicle of Higher Education, looks at the importance of spatial reasoning. The author makes the argument that education in the United States should focus more heavily on improving student spatial skills, as these skills are widely applicable, particularly in respect to the STEM disciplines. She also discusses sex and socioeconomic differences in respect to spatial reasoning ability. This document may be downloaded in PDF file format.

Newcombe, Nora



An Automated Land Analysis System (ALAS) for applications at a range of spatial scales: Watershed to global  

SciTech Connect

Recent advances in Digital Elevation Model (DEM) data availability and topographic analysis have enabled us to develop an Automated Land Analysis System (ALAS). ALAS is based on a series of codes which determine topographic and hydrologic characteristics at each pixel, watershed, and each large scale cell. The input requirements are a DEM from any location in the world, it`s resolution, and array size. A Motif accessed script reads in these inputs and generates a series of data sets which further describe the watershed properties such as flow directions, hydrologic characteristic probability density functions, etc.). Postscript files and arrays indicating the fme river networks and each subcatchment, as well as numerous other properties, are produced and catalogued. The motivation behind the development of ALAS is a direct response to the conceptualization of convergent scales between hydrologic and atmospheric models as defined by the World Climate Research Programme. The remainder of this paper highlights ALAS components, capabilities, and provides some discussion on its applications.

Miller, N.L.



A spatial analysis of cultural ecosystem service valuation by regional stakeholders in Florida: a coastal application of the social values for ecosystem services (SolVES) tool  

USGS Publications Warehouse

Livelihoods and lifestyles of people throughout the world depend on essential goods and services provided by marine and coastal ecosystems. However, as societal demand increases and available ocean and coastal space diminish, better methods are needed to spatially and temporally allocate ocean and coastal activities such as shipping, energy production, tourism, and fishing. While economic valuation is an important mechanism for doing so, cultural ecosystem services often do not lend themselves to this method. Researchers from the U.S. Geological Survey are working collaboratively with the Florida Sea Grant College Program to map nonmonetary values of cultural ecosystem services for a pilot area (Sarasota Bay) in the Gulf of Mexico. The research seeks to close knowledge gaps about the attitudes and perceptions, or nonmonetary values, held by coastal residents toward cultural ecosystem services, and to adapt related, terrestrial-based research methods to a coastal setting. A critical goal is to integrate research results with coastal and marine spatial planning applications, thus making them relevant to coastal planners and managers in their daily efforts to sustainably manage coastal resources. Using information about the attitudes and preferences of people toward places and uses in the landscape, collected from value and preference surveys, the USGS SolVES 2.0 tool will provide quantitative models to relate social values, or perceived nonmonetary values, assigned to locations by survey respondents with the underlying environmental characteristics of those same locations. Project results will increase scientific and geographic knowledge of how Sarasota Bay residents value their area’s cultural ecosystem services.

Coffin, Alisa W.; Swett, Robert A.; Cole, Zachary D.



Study and application of data mining and data warehouse in CIMS  

NASA Astrophysics Data System (ADS)

The interest in analyzing data has grown tremendously in recent years. To analyze data, a multitude of technologies is need, namely technologies from the fields of Data Warehouse, Data Mining, On-line Analytical Processing (OLAP). This paper gives a new architecture of data warehouse in CIMS according to CRGC-CIMS application engineering. The data source of this architecture comes from database of CRGC-CIMS system. The data is put in global data set by extracting, filtrating and integrating, and then the data is translated to data warehouse according information request. We have addressed two advantages of the new model in CRGC-CIMS application. In addition, a Data Warehouse contains lots of materialized views over the data provided by the distributed heterogeneous databases for the purpose of efficiently implementing decision-support, OLAP queries or data mining. It is important to select the right view to materialize that answer a given set of queries. In this paper, we also have designed algorithms for selecting a set of views to be materialized in a data warehouse in order to answer the most queries under the constraint of given space. First, we give a cost model for selecting materialized views. Then we give the algorithms that adopt gradually recursive method from bottom to top. We give description and realization of algorithms. Finally, we discuss the advantage and shortcoming of our approach and future work.

Zhou, Lijuan; Liu, Chi; Liu, Daxin



Planetary Spatial Analyst  

NASA Technical Reports Server (NTRS)

This is a status report for the project entitled Planetary Spatial Analyst (PSA). This report covers activities from the project inception on October 1, 2007 to June 1, 2008. Originally a three year proposal, PSA was awarded funding for one year and required a revised work statement and budget. At the time of this writing the project is well on track both for completion of work as well as budget. The revised project focused on two objectives: build a solid connection with the target community and implement a prototype software application that provides 3D visualization and spatial analysis technologies for that community. Progress has been made for both of these objectives.

Keely, Leslie



Spatially 2D-selective RF excitations using the PROPELLER trajectory: basic principles and application to MR spectroscopy of irregularly shaped single voxel.  


Spatially two-dimensional selective radio frequency (2DRF) excitations are able to excite arbitrarily-shaped profiles in their excitation plane and, hence, can be used to minimize partial volume effects in single-voxel magnetic resonance spectroscopy. In this study, 2DRF excitations based on the PROPELLER trajectory which consists of blades of parallel lines that are rotated against each other, are presented. Because the k-space center is covered with each segment, the trajectory yields a high signal efficiency which, e.g., is considerably improved compared to a segmented blipped-planar approach. It is shown that a sampling density correction based on the PROPELLER trajectory's Voronoi diagram suppresses unwanted side excitations. Off-resonance effects like chemical-shift displacement artifacts, can be minimized by applying nonselective refocusing radio frequency pulses between the lines of a blade. With half-Fourier segments, the 2DRF's echo time contribution can be shortened considerably. Thus, robust 2DRF excitations capable of exciting high-resolution profiles at short echo times with high signal efficiency are obtained. Their applicability to MR spectroscopy of an arbitrarily-shaped single voxel is demonstrated in a two-bottle phantom and in the human brain in vivo on a 3 T whole-body MR system. PMID:21465546

Busch, Martin G; Finsterbusch, Jürgen



Spatial data interoperability for multi-platform GIS based on Oracle Spatial  

Microsoft Academic Search

Spatial data sharing among multiple GIS (Geographic Information System) platforms is a fundamental requirement of many GIS applications, yet conventional methods of spatial data interoperability don't adequately consider practical application circumstance, which now becomes a primary barrier to more efficient spatial data sharing among multiple GIS platforms. In this paper, after analyzing the disadvantages of conventional methods and the causation

Yu Xia; Xinyan Zhu



Efficiently Mining Regional Outliers in Spatial Data  

Microsoft Academic Search

With the increasing availability of spatial data in many applications, spatial clustering and outlier detection has received a lot of attention in the database and data mining community. As a very prominent method, the spatial scan statistic finds a region that deviates (most) significantly from the entire dataset. In this paper, we introduce the novel problem of mining regional outliers

Richard Frank; Wen Jin; Martin Ester




Microsoft Academic Search

Geographic information systems manage a large volume of spatial data. We often use it to solve some problems such as urban planning and land use management. Interoperability of GIS is the ability to access spatial data and associated services in a distributed and heterogeneous processing environment. There are many existing spatial databases and GIS applications that are built on those

Jianya Gong; Hanjiang Xiong; Yandong Wang; Lite Shi


Indexing in Spatial Databases  

Microsoft Academic Search

Spatial information processing has been a focus of research in the past decade. In spatial databases, data are associated with spatial coordinates and extents, and are retrieved based on spatial proximity. A formidable number of spatial indexes have been proposed to facilitate spatial data retrieval. In this paper, we examine various spatial indexes proposed in the literature and present a

Beng Chin Ooi; Ron Sacks-Davis Jiawei


Elevational spatial compounding.  


Spatial compounding has long been explored to reduce coherent speckle noise in medical ultrasound. By laterally translating a one-dimensional array, partially correlated measurements made at different look directions can be obtained and incoherently averaged. The lateral resolution, however, is limited by the sub-array length used for each independent measurement. To reduce speckle contrast without compromising lateral resolution, a new spatial compounding technique using two-dimensional, anisotropic arrays is proposed. This technique obtains partially correlated measurements by steering the image plane elevationally with small inclinations. Incoherent averaging is then performed by adding image magnitudes. Therefore, contrast resolution is improved only at the price of a slightly wider elevational beam. Note that although anisotropic arrays have limited steering capability in elevation, grating lobes are not considered influential since only small inclinations are needed between measurements. Simulations have been performed to show both the change in spatial resolution and the improvement in contrast resolution. Results indicated minimal increase in the correlation length both laterally and axially. It was also shown that detectability can be significantly enhanced by increasing the number of measurements or increasing the differential inclination between measurements. This technique is therefore effective for reducing speckle noise while maintaining in-plane spatial resolution. Furthermore, it demonstrates a new application of two-dimensional anisotropic arrays in spite of their limited elevational steering capability. PMID:7839557

Li, P C; O'Donnell, M



Visualizations in Spatial Algorithm Development  

NASA Astrophysics Data System (ADS)

Spatial algorithms as used in Geographic Information Systems (GIS) can be difficult to understand and use, both for the developers and users. Knowledge transfer between developers and GIS enabled application users is often inadequate, incomprehensible or non-existent. Novel approaches for spatially indexing and searching data involve trade-offs; all have their limitations and advantages. Effectively communicating these trade-offs is a challenge. Both the limitations and strong points of any algorithms used in scientific applications must be explained to end-users in an easily understood and digestible manner. Written documentation is only one way of describing an algorithm. Images, animations, and interactive demos have long been used to aid in understanding spatial algorithms but their adoption and use could be increased. This session demonstrates how to include interactive visualizations from a project's inception and outlines the possibility of using these visualizations not only as eventual documentation, but also as verification criteria for spatial algorithm development. Interactive tools, such as Google Earth, can be used to create and visualize inputs to spatial algorithms and validate results. During development, a developer can benefit from constant feedback and the ability to quickly test changes and new code. This session will also demonstrate methods of documenting spatial algorithms for end users. The use of literate programming tools such as docco, http://, and spatial visualizations document the code and aid in producing documentation for scientists and developers.

Gilman, J.; Pilone, D.; Mitchell, A. E.; Baynes, K.



SMART: a spatially explicit bio-economic model for assessing and managing demersal fisheries, with an application to italian trawlers in the strait of sicily.  


Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species. PMID:24465971

Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio



On the Applicability of Taylor's ``Frozen-Flow'' Hypothesis to Spatial and Temporal Observations of Atmosphere Path Delay From InSAR and GPS  

NASA Astrophysics Data System (ADS)

Turbulent mixing of water vapor in the lower troposphere produces fluctuations of the spatio-temporal distribution of neutral atmosphere refractive index at microwave frequencies. These variations cause phase shifts in Interferometric Synthetic Aperture Radar (InSAR) images and Global Positioning System (GPS) signals. Here, we compare spatial observations of atmospheric phase shifts from a radar interferogram of Southern California with temporal measurements of atmospheric delay obtained from a network of continuous GPS receivers operating in the imaged area. We translate temporal observations to equivalent spatial samples of delay through Taylor's ``frozen-flow'' hypothesis. We use the ``frozen-flow'' hypothesis in conjuction with Kolmogorov turbulence theory to derive theoretical expressions for temporal and spatial power spectra and structure functions of atmosphere delay. We show that temporal and spatial power spectra and structure functions have similar theoretical forms and parameters. Further, the theoretical expressions for temporal power spectra and structure functions require knowledge of the magnitude and direction of wind about each GPS receiver, which we estimate from the timeseries of delays at each site. These wind estimates and the theoretical expressions are fit to computed power spectra and structure functions of delay derived from the GPS and InSAR data. The parameters derived from the least-squares fitting of temporal power spectra and structure functions from GPS are used to infer spatial models of power spectra and structure functions of interferometric phase. Comparison of these inferred models with computed spatial power spectra and structure functions from the InSAR phase residuals demonstrate the validity of applying Taylor's hypothesis to GPS and InSAR atmospheric delay measurements. This correspondence between measurements of atmosphere delay from the two datasets suggests that full timeseries of atmosphere path delay from GPS, as opposed to delay observations taken at the radar acquisition times only, can be used to mitigate atmospheric effects in radar interferograms.

Onn, F.; Zebker, H. A.



Application of the micro-genetic algorithm to the design of spatial filters with frequency-selective surfaces embedded in dielectric media  

Microsoft Academic Search

We present an efficient method of optimizing spatial filters comprising of single and multiple frequency-selective surface (FSS) screens embedded in multilayered dielectric media. Two such filter designs are optimized via the micro-genetic algorithm (MGA) and their frequency responses are validated by alternate methods

Sourav Chakravarty; Raj Mittra



Control of spatial polarization by use of a liquid crystal with an optically treated alignment layer and its application to beam apodization  

Microsoft Academic Search

We have investigated the alignment of a liquid crystal whose orientation is controlled by photoisomerization reaction for use in developing optical devices to improve beam quality. A glass window of a liquid-crystal cell that is coated with poly(vinyl alcohol) doped with azo dye was illuminated with a Hg lamp. We confirmed the dependence of the spatially controlled alignment direction of

Keiichi Sueda; Kouji Tsubakimoto; Noriaki Miyanaga; Masahiro Nakatsuka



Evaluation of the spatial impacts of improved connectivity from urban transport investments. A GIS (Geographic Information System) application of the ICON indicator for urban areas  

Microsoft Academic Search

A well-designed urban public transport policy provides significant benefits: reduces congestion and costs, and decreases the number of accidents and environment impacts. Accessibility indicators are used by planners to assess the spatial effects of their proposals and to identify those areas requiring actions to ensure minimum conditions of service. They are also used in decision making on the implementation of

Hector Tapia



Multi-beam second-harmonic generation in beta barium borate with a spatial light modulator and application to internal structuring in poly(methyl methacrylate)  

NASA Astrophysics Data System (ADS)

Parallel beam frequency doubling of 170 fs, NIR pulses is demonstrated by placing a thin beta barium borate (BBO) nonlinear crystal after a spatial light modulator. Computer-generated holograms applied to the spatial light modulator create 18 parallel diffracted beams at the fundamental wavelength ?=775 nm, then frequency doubled to ?=387 nm and focussed inside the poly(methyl methacrylate) (PMMA) substrate for refractive index structuring. This procedure, demonstrated for the first time in PMMA, requires careful attention to phase matching of multiple beams and opens up dynamic parallel processing at UV wavelengths where nematic liquid crystal devices are more sensitive to optical damage. By overlapping filamentary modifications, an efficient, stable volume phase grating with dimensions 5×5×2.0 mm3 and pitch ?=15 ?m was fabricated in 18 minutes and reached a first-order diffraction efficiency of 70 % at the Bragg angle.

Liu, D.; Perrie, W.; Kuang, Z.; Scully, P. J.; Baum, A.; Liang, S.; Edwardson, S. P.; Fearon, E.; Dearden, G.; Watkins, K. G.



Cause of Spatial Disorientation.  

National Technical Information Service (NTIS)

We here present a model including visual-vestibular interactions describing the basic properties of the human spatial orientation system. It hence also explains and describes spatial disorientation. The model indicates that spatial orientation should at l...

E. L. Groen J. E. Bos R. J. Hosman W. Bles



Novel solid-state spatial light modulator on integrated circuits for high-speed application with electro-optic thin film  

Microsoft Academic Search

Novel solid-state spatial light modulator (SLM) is developed by using an electro-optic thin film technology. The use of sol-gel technique makes it possible to fabricate optically smooth 800nm-thick lead zirconate titanate (PZT) films. It shows large electro-optic effects Deltan=0.02 with the fastest switching response of 12ns that have ever been reported. The prototype 180times180 SLM array on 5mmtimes5mm-size chip demonstrates

Y. Fujimori; T. Fujii; T. Suzuki; H. Kimura; T. Fuchikami; T. Nakamura; H. Takasu



A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis  

NASA Astrophysics Data System (ADS)

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this "single-valued" space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent "line-like objects" and "point-like objects" are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.

Liu, Yu; Guo, Qinghua; Kelly, Maggi


The design of a heterocellular 3D architecture and its application to monitoring the behavior of cancer cells in response to the spatial distribution of endothelial cells.  


The spatial cell distribution is one of the critical features for governing cellular interactions and their consequent behaviors. Here we suggest a novel method of building a hierarchical cellular structure by stacking cell-attached microplate structures with specific configurations within hydrogel layers. This method is applied to the reconstruction of the 3D architecture of a liver lobule and the development of an experimental model of the various phases of cancer angiogenesis. PMID:22927197

Lee, Wonjae; Park, Jon



Spatial-Operator Algebra For Robotic Manipulators  

NASA Technical Reports Server (NTRS)

Report discusses spatial-operator algebra developed in recent studies of mathematical modeling, control, and design of trajectories of robotic manipulators. Provides succinct representation of mathematically complicated interactions among multiple joints and links of manipulator, thereby relieving analyst of most of tedium of detailed algebraic manipulations. Presents analytical formulation of spatial-operator algebra, describes some specific applications, summarizes current research, and discusses implementation of spatial-operator algebra in the Ada programming language.

Rodriguez, Guillermo; Kreutz, Kenneth K.; Milman, Mark H.




Microsoft Academic Search

Abstract The present work deals with the first application of Support Vector Regression (SVR) for the spatial data mapping. SVR is a ,recent development ,of the ,Statistical Learning Theory (VapnikChervonenkis,theory). It is based on Structural Risk Minimisation and seems ,to be ,promising approach for the spatial data analysis and processing. There are several attractive properties of the SVR: robustness of

Mikhail Kanevski; Stephane Canu



GIS and spatial data analysis: Converging perspectives  

Microsoft Academic Search

This article identifies some of the important developments in GIS and spatial data analysis since the early 1950s. Although GIS and spatial data analysis started out as two more or less separate areas of research and application, they have grown closer together over time. We argue that the two areas meet in the field of geographic information science, with each

Michael F. Goodchild; Robert P. Haining



Transverse spatial transport in field-effect transistors based on heterostructures with selective doping and the limits of applicability of quasi-hydrodynamic models  

SciTech Connect

For field-effect transistors based on heterostructures with selective doping, the results of calculations for the output characteristics of devices on the basis of the hydrodynamic model are compared with those based on the quasi-hydrodynamic (temperature-related) model. It is shown that the transverse spatial transport and heavy dependences of relaxation times on energy lead to the situation where the results of calculations based on the above models differ appreciably from one another at the gate lengths that much exceed the length of electron relaxation by momentum.

Klimova, A. V. [Federal State Unitary Corporation Istok (Russian Federation)], E-mail:; Lukashin, M. V. [Research Institute MEIIT MIEM (Russian Federation); Pashkovskii, A. B. [Federal State Unitary Corporation Istok (Russian Federation)



Approximate spatial reasoning  

NASA Technical Reports Server (NTRS)

A model for approximate spatial reasoning using fuzzy logic to represent the uncertainty in the environment is presented. Algorithms are developed which can be used to reason about spatial information expressed in the form of approximate linguistic descriptions similar to the kind of spatial information processed by humans. Particular attention is given to static spatial reasoning.

Dutta, Soumitra



Application of Composite Water Quality Identification Index on the water quality evaluation in spatial and temporal variations: a case study in Honghu Lake, China.  


Composite Water Quality Identification Index (CWQII) and multivariate statistical techniques were used to investigate the temporal and spatial variations of water quality in Honghu Lake. The aims are to explore the characteristics of water quality trends in annual, monthly, and site spatial distribution and to identify the main pollution factors. The results showed that the values of CWQII increased from 2.0 to 4.0 from the years 2001 to 2005, then decreased from 2006 and kept a balance between 2.0 and 3.0 from 2006 to 2011, indicating that the water quality of Honghu Lake deteriorated from 2001 to 2005 and has gradually improved since 2006, which were likely achieved after water protection measurements taken since 2004. The monthly change rules of water quality were influenced by a superposition of natural processes and human activities. In samples numbered 1-9 from upstream to downstream, the maximum values of CWQII often occurred in sample site 9 while the minimum ones often occurred in sample site 2, indicating that the water quality near the upstream tributary was the poorest and that in the core zone was the best. Incoming water from the trunk canal of the Sihu area upstream was the largest pollution source. The sensitive pollution nutrients were mainly caused by the total nitrogen, followed by the total phosphorus. PMID:24615690

Ban, Xuan; Wu, Qiuzhen; Pan, Baozhu; Du, Yun; Feng, Qi



Control of Spatially Inhomogeneous Shear Flows.  

National Technical Information Service (NTIS)

Model-based feedback control of the instabilities arising in a spatially inhomogeneous boundary layer flow is studied. To build a reduced- order model of the problem, where the application of standard tools from control theory become computationally feasi...

D. S. Henningson E. Akervik L. Brandt O. Semeraro S. Bagheri



Spatial Modulation in the Underwater Acoustic Channel.  

National Technical Information Service (NTIS)

Multiple-input multiple-output (MIMO) communication channels are an active area of research for terrestrial wireless applications. The natural bandwidth limitations of the underwater acoustic channel (UAC) combined with the potential for a rich spatial pr...

D. Kilfoyle L. Freitag




EPA Science Inventory

Pesticides found in homes may result from indoor applications to control household pests or by translocation from outdoor sources. Pesticides disperse according to their physical properties and other factors such as human activity, air exchange, temperature and humidity. Insect...


TeachSpatial Annotations  

NSDL National Science Digital Library

The TeachSpatial collection assembles digital teaching resources relevant to spatial cognition, spatial learning, and spatial literacy across multiple STEM disciplines for middle school, high school, and undergraduate learners. Common topics include physical geography, GIS (Geographic Information Systems), and map reading skills (population demographics, geographic coordinates, etc.). Resources are indexed by the core spatial concepts and principles found in the 1996 National Science Education Standards and contain comments and ratings from a community of users. TeachSpatial is a project of the Center for Spatial Studies at the University of California, Santa Barbara.




Microsoft Academic Search

Spatial regression models incorporating non-stationarity in the regression coefficients are popular. In this paper we propose a family of spatial Smooth Transition AutoRegressive (STAR) models inspired by analogous nonlinear approaches developed in the time series literature. Spatial STAR models constitute a parsimonious, easy-to-estimate approach to modeling nonlinear spatial parameter variation and endogenous detection of spatial regimes. A distinct advantage of

Raymond J. G. M. Florax; Valerien O. Pede; Matthew T. Holt


Spatial Standard Observer  

NASA Technical Reports Server (NTRS)

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image, or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image. Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer, SSO. Some embodiments include masking functions, window functions, special treatment for images lying on or near borders and pre-processing of test images.

Watson, Andrew B. (Inventor)



Spatial Standard Observer  

NASA Technical Reports Server (NTRS)

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image. or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image . Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer. SSO. Some embodiments include masking functions. window functions. special treatment for images lying on or near border and pre-processing of test images.

Watson, Andrw B. (Inventor)



Independent spatial intensity, phase and polarization distributions.  


Independent control of the spatial intensity, phase and polarization distribution has numerous applications in direct laser writing, microscopy and optical trapping. Especially, it is well known that the inversion of the Debye-Wolf diffraction integral usually leads to spatially varying intensity, phase and polarization maps. Here, we present a prism and grating free setup built around a single phase-only spatial-light-modulator for full control of spatial intensity, phase and polarization distributions. These distributions are not limited to non-diffractive beams and do not require any change of setup. We verify the versatility of the proposed method with wavefront and intensity measurements. PMID:24514328

Waller, Erik H; von Freymann, Georg



A high-spatial-resolution fiber-optic-coupled CMOS imager with novel scintillator for high-energy x-ray applications  

NASA Astrophysics Data System (ADS)

A fast, high-spatial-resolution detector for high-energy microscopy work is presented. The detector uses a 2160 × 2560 CMOS chip for fast framing (up to 100 Hz in full-frame mode), coupled by a fiber optic taper to a scintillating Terbium-doped fiber optic plate for excellent stopping power even at high energies. The field of view is 7mm × 8.6mm with a resolution of 9 microns. The sensitivity is 1 e-/x-ray at 35 keV, with a read noise of 2.5 e-/pixel. Standard characterization metrics including dark current, sensitivity, modulation transfer function, and detective quantum efficiency are presented, along with preliminary experimental results.

Baur, Robin M.; Tate, Mark W.; Dale, Darren S.; Gruner, Sol M.



Center for Advanced Spatial Technologies  

NSDL National Science Digital Library

The Center for Advanced Spatial Technologies (CAST) at the University of Arkansas is dedicated to applications in Geographic Information Systems (GIS), remote sensing, digital photogrammetry and interoperability, and Global Positioning Systems (GPS). This enormous site contains a wide range of research activities in spatial technologies as applied to the disciplines of environmental studies, archaeology, historical preservation, landscape architecture, urban and rural planning, spatial statistics, and data development. Within the Reports and Publications section, the Arkansas Gap Analysis Program (GAP) final report is available (in HTML and .pdf formats) and, though the work itself was completed in 1998, the report provides excellent information on biodiversity assessment and land-cover mapping (For the national Gap Analysis Program Website, see the September 17, 1997 Scout Report for Science & Engineering). Each of the research areas of the site contains documentation of projects and links to related sites.



Spatial and temporal heterogeneity explain disease dynamics in a spatially explicit network model.  


There is an increasing recognition that individual-level spatial and temporal heterogeneity may play an important role in metapopulation dynamics and persistence. In particular, the patterns of contact within and between aggregates (e.g., demes) at different spatial and temporal scales may reveal important mechanisms governing metapopulation dynamics. Using 7 years of data on the interaction between the anther smut fungus (Microbotryum violaceum) and fire pink (Silene virginica), we show how the application of spatially explicit and implicit network models can be used to make accurate predictions of infection dynamics in spatially structured populations. Explicit consideration of both spatial and temporal organization reveals the role of each in spreading risk for both the host and the pathogen. This work suggests that the application of spatially explicit network models can yield important insights into how heterogeneous structure can promote the persistence of species in natural landscapes. PMID:18662121

Brooks, Christopher P; Antonovics, Janis; Keitt, Timothy H



Development of atomic radical monitoring probe and its application to spatial distribution measurements of H and O atomic radical densities in radical-based plasma processing  

SciTech Connect

Atomic radicals such as hydrogen (H) and oxygen (O) play important roles in process plasmas. In a previous study, we developed a system for measuring the absolute density of H, O, nitrogen, and carbon atoms in plasmas using vacuum ultraviolet absorption spectroscopy (VUVAS) with a compact light source using an atmospheric pressure microplasma [microdischarge hollow cathode lamp (MHCL)]. In this study, we developed a monitoring probe for atomic radicals employing the VUVAS with the MHCL. The probe size was 2.7 mm in diameter. Using this probe, only a single port needs to be accessed for radical density measurements. We successfully measured the spatial distribution of the absolute densities of H and O atomic radicals in a radical-based plasma processing system by moving the probe along the radial direction of the chamber. This probe allows convenient analysis of atomic radical densities to be carried out for any type of process plasma at any time. We refer to this probe as a ubiquitous monitoring probe for atomic radicals.

Takahashi, Shunji [Department of Electrical Engineering and Computer Science, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Katagiri Engineering Co., Ltd., 3-5-34 Shitte Tsurumi-ku, Yokohama 230-0003 (Japan); Takashima, Seigo [Plasma Center for Industrial Applications, Nagoya Urban Industries Promotion Corporation, 2268-1 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003 (Japan); Yamakawa, Koji; Den, Shoji [Katagiri Engineering Co., Ltd., 3-5-34 Shitte Tsurumi-ku, Yokohama 230-0003 (Japan); Kano, Hiroyuki [NU-EcoEngineering Co., Ltd., 1237-87 Aza Umazutsumi, Ooaza Kurozasa, Miyoshi-cho, Nishikamo-gun, Aichi 470-0201 (Japan); Takeda, Keigo [Department of Electrical Engineering and Computer Science, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Hori, Masaru [Department of Electrical Engineering and Computer Science, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Plasma Nanotechnology Research Center, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); JST, CREST, 4-1-8 Hon-chou, Kawaguchi, Saitama 332-0012 (Japan)



An application of remotely derived climatological fields for risk assessment of vector-borne diseases : a spatial study of filariasis prevalence in the Nile Delta, Egypt.  

SciTech Connect

This paper applies a relatively straightforward remote sensing method that is commonly used to derive climatological variables. Measurements of surface reflectance and surface radiant temperature derived from Landsat Thematic Mapper data were used to create maps of fractional vegetation and surface soil moisture availability for the southern Nile delta in Egypt. These climatological variables were subsequently used to investigate the spatial distribution of the vector borne disease Bancroftian filariasis in the Nile delta where it is focally endemic and a growing problem. Averaged surface soil moisture values, computed for a 5-km border area around affected villages, were compared to filariasis prevalence rates. Prevalence rates were found to be negligible below a critical soil moisture value of 0.2, presumably because of a lack of appropriate breeding sites for the Culex Pipiens mosquito species. With appropriate modifications to account for local conditions and vector species, this approach should be useful as a means to map, predict, and control insect vector-borne diseases that critically depend on wet areas for propagation. This type of analysis may help governments and health agencies that are involved in filariasis control to better focus limited resources to identifiable high-risk areas.

Crombie, M. K.; Gillies, R. R.; Arvidson, R. E.; Brookmeyer, P.; Weil, G. J.; Sultan, M.; Harb, M.; Environmental Research; Washington Univ.; Utah State Univ.; Egyptian Ministry of Health



Visual acuity measurements by swept spatial frequency visual-evoked-cortical potentials (VECPs): clinical application in children with various visual disorders.  


Previous studies have indicated that visual acuities of normal infants can be estimated with good accuracy using swept spatial frequency visual-evoked-potentials (VECPs). In this report we describe acuity measurements obtained with this technique from 304 examinations performed on 135 children having various visual disorders. When possible, two or more different stimulation frequencies (8, 12, 15 or 24 contrast reversals/sec) were used in each patient, and three to eight sweep VECPs were obtained from each patient under each simulation and recording condition. High correlation coefficients (0.94 - 0.96) between the acuity estimated on each patient from either the single sweep giving the best visual acuity (BSS) or from vector averages (VeA) of the EEG data obtained from several sweeps confirmed previous findings in normal infants. We also found high correlation coefficients among BSS recorded at different temporal frequencies (0.79-0.97) and among comparisons of BSS or VeA acuity to optotype visual acuity (0.6-0.89). Children with clinically undetectable optokinetic responses showed lower visual acuity estimated by BSS than those who demonstrated optokinetic nystagmus. We conclude that the sweep VECP is a valid method, giving estimates of acuity which correlate well with optotype acuity and correspond well to other clinical findings, and that it can be useful in the clinical management of nonverbal patients. PMID:2324917

Gottlob, I; Fendick, M G; Guo, S; Zubcov, A A; Odom, J V; Reinecke, R D



Multiband Multislice GE-EPI at 7 Tesla, With 16-Fold Acceleration Using Partial Parallel Imaging With Application to High Spatial and Temporal Whole-Brain FMRI  

PubMed Central

Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k-space coverage in the phase-encode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4-fold phase-encoding undersampling, resulting in 16-fold acceleration and up to 16-fold maximal aliasing, was investigated. Task/stimulus-induced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single-band excitation and longer pulse repetition times. Robust, whole-brain functional mapping at 7 T, with 2 × 2 × 2mm3 (pulse repetition time 1.25 sec) and 1 × 1 × 2mm3 (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 × 256 × 176mm3 and 192 × 172 × 176mm3, respectively, was demonstrated with current gradient performance.

Moeller, Steen; Yacoub, Essa; Olman, Cheryl A.; Auerbach, Edward; Strupp, John; Harel, Noam; Ugurbil, Kamil



Comparing the applicability of some geostatistical methods to predict the spatial distribution of topsoil Calcium Carbonate in part of farmland of Zanjan Province  

NASA Astrophysics Data System (ADS)

Most of soils in iran, were located in the arid and semi-arid regions and have high pH (more than 7) and high amount of calcium carbonate and this problem cause to their calcification.In calcareous soils, plant growing and production is difficult. Most part of this problem, in relation to high pH and high concentration of calcium ion that cause to fixation and unavailability of elements which were dependent to pH, especially Phosphorous and some micro nutrients such as Fe, Zn, Mn and Cu. Prediction of soil calcium carbonate in non-sampled areas and mapping the calcium carbonate variability in order to sustainable management of soil fertility is very important.So, this research was done with the aim of evaluation and analyzing spatial variability of topsoil calcium carbonate as an aspect of soil fertility and plant nutrition, comparing geostatistical methods such as kriging and co-kriging and mapping topsoil calcium carbonate. For geostatistical analyzing, sampling was done with stratified random method and soil samples from 0 to 15 cm depth were collected with auger within 23 locations.In co-kriging method, salinity data was used as auxiliary variable. For comparing and evaluation of geostatistical methods, cross validation were used by statistical parameters of RMSE. The results showed that co-kriging method has the highest correlation coefficient and less RMSE and has the higher accuracy than kriging method to prediction of calcium carbonate content in non-sampled areas.

Sarmadian, Fereydoon; Keshavarzi, Ali



Analysing urban resilience through alternative stormwater management options: application of the conceptual Spatial Decision Support System model at the neighbourhood scale.  


Recent changes in cities and their environments, caused by rapid urbanisation and climate change, have increased both flood probability and the severity of flooding. Consequently, there is a need for all cities to adapt to climate and socio-economic changes by developing new strategies for flood risk management. Following a risk paradigm shift from traditional to more integrated approaches, and considering the uncertainties of future urban development, one of the main emerging tasks for city managers becomes the development of resilient cities. However, the meaning of the resilience concept and its operability is still not clear. The goal of this research is to study how urban engineering and design disciplines can improve resilience to floods in urban neighbourhoods. This paper presents the conceptual Spatial Decision Support System (DS3) model which we consider a relevant tool to analyse and then implement resilience into neighbourhood design. Using this model, we analyse and discuss alternative stormwater management options at the neighbourhood scale in two specific areas: Rotterdam and New Orleans. The results obtained demonstrate that the DS3 model confirmed in its framework analysis that stormwater management systems can positively contribute to the improved flood resilience of a neighbourhood. PMID:24334895

Balsells, M; Barroca, B; Amdal, J R; Diab, Y; Becue, V; Serre, D



Kinetic theory of spatially homogeneous systems with long-range interactions: III. Application to power law potentials, plasmas, stellar systems, and to the HMF model  

NASA Astrophysics Data System (ADS)

We apply the general results of the kinetic theory of systems with long-range interactions to particular systems of physical interest. We consider repulsive and attractive power law potentials of interaction with in a space of dimension d . For , strong collisions must be taken into account and the evolution of the system is governed by the Boltzmann equation or by a modified Landau equation; for , strong collisions are negligible and the evolution of the system is governed by the Lenard-Balescu equation. In the marginal case , we can use the Landau equation (with appropriately justified cut-offs) as a relevant approximation of the Boltzmann and Lenard-Balescu equations. The divergence at small scales that appears in the original Landau equation is regularized by the effect of strong collisions. In the case of repulsive interactions with a neutralizing background ( e.g. plasmas), the divergence at large scales that appears in the original Landau equation is regularized by collective effects accounting for Debye shielding. In the case of attractive interactions ( e.g. gravity), it is regularized by the spatial inhomogeneity of the system and its finite extent. We provide explicit analytical expressions of the diffusion and friction coefficients, and of the relaxation time, depending on the value of the exponent and on the dimension of space d . We treat in a unified framework the case of Coulombian plasmas and stellar systems in various dimensions of space, and the case of the attractive and repulsive HMF models.

Chavanis, Pierre-Henri



Components of Spatial Ability.  

National Technical Information Service (NTIS)

The goal of this project was to identify information processing components of spatial ability. A summary paper is presented that reviews major psychometric analyses of spatial ability as they relate to theories of information processing. The primary empha...

J. W. Pellegrino D. L. Alderton J. W. Regian



Probabilistic Spatial Database Operations  

Microsoft Academic Search

Spatial databases typically assume that the positional at- tributes of spatial objects are precisely known. In practice, however, they are known only approximately, with the error depending on the nature of the measurement and the source of data. In this paper, we address the problem how to perform spatial database operations in the presence of uncertainty. We first discuss a

Jinfeng Ni; Chinya V. Ravishankar; Bir Bhanu



Application of a two-dimensional model to describe the CO2 exchange between a spatially non-uniform forest stand and the atmosphere  

NASA Astrophysics Data System (ADS)

Within the framework of the study a two dimensional hydrodynamic high-resolution model of the energy, H2O, CO2 turbulent exchange was developed and applied to describe effect of the horizontal and vertical heterogeneity of a forest canopy on CO2exchange between soil surface, forest stand and the atmosphere under different weather conditions. Most attention in the study was paid to analyze the influence of forest clearing, windthrow of different sizes, forest edges, etc. on turbulent exchange rate and CO2 flux partitioning between forest overstorey, understorey and soil surface. The modeling experiments were provided under different wind conditions, thermal stratification of the atmospheric boundary layer, incoming solar radiation, etc. To quantify effect of spatial heterogeneity on total ecosystem fluxes the modeling results were compared with CO2 fluxes modeled for a spatially uniform forest canopy under similar ambient conditions. The averaged system of hydrodynamic equations is used for calculating the components of the mean velocity ?V = {V1, V2}: ( ( ) ) ?Vi+ V ?Vi= - 1-??P- - -?- ? E - K ?Vi-+ ?Vj- + F, ?Vi = 0, ?t j?xj ?0 ?xi ?xj ij ?xj ?xi i ?xi where E is the turbulent kinetic energy (TKE), K is the turbulent diffusivity, ?P is the deviation of pressure from the hydrostatic distribution and ?0?F is the averaged force of air flow interaction with vegetation. F? was parameterized as ?F = -cd ·LAD ·| | ||V?||·?V, where cd is the drag coefficient and LAD is the leaf area density. The turbulent diffusivity K can be expressed by means of TKE and the velocity of TKE dissipation ? as follows: K = C?E2?-1, where C? is the proportionality coefficient. One of the ways to obtain E and ? is to solve the additional system of two differential equations of diffusion-transport type: ( ) ( ) ?E- -?E- -?- -K-?E- ?-? ??- -?- K-?? -? ( 1 2 ) ?t +Vj?xj = ?xi ?E ?xi +PE - ?, ?t +Vj ?xj = ?xi ???xi +E C ?PE - C?? - ? ?, where ?E and ?? are the Prandtl numbers, PE is the TKE production by shear, C?1 and C?2 are the model constants. The term ?? = ?- E(C ?1 - C?2) · 12C?1/2c dLAD||? || |V |E describes the increase of TKE dissipation due to the interaction with vegetation elements. The function ? can be any of the following variables: ?, ?/ E, or El, where l is the mixing length. Detailed analysis of these equations performed by Sogachev (Sogachev, Panferov, 2006) showed that for ? = ?/ E the model is less sensible to the errors of the input data. Transfer equation for CO2 within and above a plant canopy can be written as: ( ) ?C- -?C- -?- -K-?C- ?t + Vj?xj = ?xi ?C ?xi + FC, where C is CO2 concentration, ?C is the Prandtl number, and the term FC describes the sources/sinks of CO2 in the vegetation and soil. For parameterization of the photosynthesis rate in the forest canopy the Monsi and Saeki approach (Monsi M., Saeki T., 1953) was applied. Stem respiration was ignored in the study. The CO2 emission from the soil surface into the atmosphere was assumed to be constant for entire forest area. This study was supported by grants of the Russian Foundation for Basic Research (RFBR 14-04-01568-a).

Mukhartova, Yulia; Olchev, Alexander; Shapkina, Natalia



Application of a spatially distributed water balance model for assessing surface water and groundwater resources in the Geba basin, Tigray, Ethiopia  

NASA Astrophysics Data System (ADS)

The Geba basin is one of the most water-stressed areas of Ethiopia, with only a short rainy period from mid-June to mid-September. Because rainfall in this region has been consistently erratic in the last decades, both in time and space, rain-fed agriculture has become problematic. Hence, in order to supplement rain-fed agriculture by irrigation, a detailed understanding of local and regional surface water and groundwater resources is important. The main objective of this study is to assess the available water resources in the Geba basin using a spatially distributed water balance model (WetSpass). Relevant input data for the model is prepared in the form of digital maps using remote sensing images, GIS tools, FAO and NASA databases, field reconnaissance and processing of meteorological and hydrological observations. The model produces digital maps of long-term average, seasonal and annual surface runoff, evapotranspiration and groundwater recharge. Results of the model show that 76% of the precipitation in the basin is lost through evapotranspiration, 18% becomes surface runoff and only 6% recharges the groundwater system. Model predictions are verified against river flow observations and are shown to be reliable. Additional maps are derived of accumulated surface runoff, safe yield for groundwater abstraction and water deficit for crop growth. Comparison of existing reservoirs with the accumulated runoff map shows that many reservoirs have failed because their design capacity is much higher than the actual inflow. Comparison of the safe yield map with the crop water deficit map shows that in most areas groundwater can be safely abstracted to supplement the water deficit for crop growth during the wet summer season. However, in the dry winter season the crop water deficit is too high to be supplemented by groundwater abstraction in a sustainable way.

Gebreyohannes, Tesfamichael; De Smedt, Florimond; Walraevens, Kristine; Gebresilassie, Solomon; Hussien, Abdelwasie; Hagos, Miruts; Amare, Kasa; Deckers, Jozef; Gebrehiwot, Kindeya



Spatial soil variability as a guiding principle in nitrogen management  

Microsoft Academic Search

This thesis focuses on the optimisation of N fertiliser application, taking into account spatially variable soil conditions. Spatial soil variability effects both cropproduction and nitrate leaching. Site specific management tries to address spatially variable conditions. Research on site specific management was done for a field on the experimental farm \\

A. Verhagen



Spatial Modulation in the Underwater Acoustic Channel  

Microsoft Academic Search

Multiple-input \\/ multiple-output (MIMO) communication channels are an active area of research for terrestrial wireless applications. The natural bandwidth limitations of the underwater acoustic channel (UAC) combined with the potential for a rich spatial propagation structure suggests the ocean is another useful application area for MIMO techniques. An underwater acoustic communications experiment was conducted in the waters surrounding Elba, Italy,

Daniel Kilfoyle; Lee Freitag



Effects of disturbance by Siberian marmots ( Marmota sibirica ) on spatial heterogeneity of vegetation at multiple spatial scales  

Microsoft Academic Search

An understanding of the relationship between vegetation spatial heterogeneity and disturbance and its application to the management are important for maintaining biodiversity and functions of ecosystems. We examined the effects of disturbance by Siberian marmots on the spatial heterogeneity of vegetation at three spatial scales (fine, intermediate and coarse) in a Mongolian grassland. We established a 50 m × 50

Yu Yoshihara; Toshiya Ohkuro; Buuveibaatar Bayarbaatar; Kazuhiko Takeuchi



Spatial profiling using a Time of Flight Diagnostic and applications of deuterim-deuterium fusion in Inertial Electrostatic Confinement fusion devices  

NASA Astrophysics Data System (ADS)

The Inertial Electrostatic Confinement (IEC) Fusion Research Group at the University of Wisconsin-Madison utilizes IEC devices as small-scale neutron generators using D-D fusion to create 2.45 MeV neutrons for the purpose of detecting clandestine material. Detection of explosives in particular can be accomplished using thermal neutron capture methods to identify characteristic nitrogen signatures in explosive material. Research has been conducted to increase reliability of detection, decrease interrogation time, and increase the steady-state operational time. Efforts have also been made to increase the neutron production rate of the device. Optimization studies have varied the configuration and design of the electrodes and have resulted in system configurations with up to 50 percent higher neutron production rates than have previously been utilized. A new feedthrough design has been constructed that is intended to increase the maximum operating voltage from 175 kV with the previous feedthrough to 300 kV. Neutron production rates scale almost linearly with both current and voltage, so the IEC device will be capable of operation at higher neutron producing regimes than have ever before been achieved. The optimization efforts involve the use of several new diagnostic tools developed at UW, which are the Fusion Ion Doppler (FIDO) Diagnostic and the Time of Flight (TOF) Diagnostic. FIDO provides the energy spectra of the charged fusion products and reactants created in the IEC device. The FIDO Diagnostic was originally only capable of studying D-D fusion, but with recent advancements is now able to study both D-D and D-3He fusion. The TOF Diagnostic provides spatial information along with the energy resolution of where the fusion reactions are occurring in the IEC device. Development of the diagnostics has involved the implementation of timing electronics, alignment systems, data acquisition software, computational post-processing, and upgrades to the experimental facility. A significant rise in the concentration of fusion events was found outside of the anode, believed to be due in part from negative ions. The FIDO and TOF Diagnostics have proven to be valuable additions to the study of IEC devices and have greatly advanced IEC operation and theory.

Donovan, David C.


Spatially-Heterodyned Holography  


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

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



Association Rule Mining using Fuzzy Spatial Data Cubes  

Microsoft Academic Search

The popularity of spatial databases increases since the amount of the spatial data that need to be handled has increased by\\u000a the use of digital maps, images from satellites, video cameras, medical equipment, sensor networks, etc. Spatial data are\\u000a difficult to examine and extract interesting knowledge; hence, applications that assist decision-making about spatial data\\u000a like weather forecasting, traffic supervision, mobile

Narin Isik; Adnan Yazici


Detecting of transient vibration signatures using an improved fast spatial-spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery  

NASA Astrophysics Data System (ADS)

Detecting transient vibration signatures is of vital importance for vibration-based condition monitoring and fault detection of the rotating machinery. However, raw mechanical signals collected by vibration sensors are generally mixtures of physical vibrations of the multiple mechanical components installed in the examined machinery. Fault-generated incipient vibration signatures masked by interfering contents are difficult to be identified. The fast kurtogram (FK) is a concise and smart gadget for characterizing these vibration features. The multi-rate filter-bank (MRFB) and the spectral kurtosis (SK) indicator of the FK are less powerful when strong interfering vibration contents exist, especially when the FK are applied to vibration signals of short duration. It is encountered that the impulsive interfering contents not authentically induced by mechanical faults complicate the optimal analyzing process and lead to incorrect choosing of the optimal analysis subband, therefore the original FK may leave out the essential fault signatures. To enhance the analyzing performance of FK for industrial applications, an improved version of fast kurtogram, named as "fast spatial-spectral ensemble kurtosis kurtogram", is presented. In the proposed technique, discrete quasi-analytic wavelet tight frame (QAWTF) expansion methods are incorporated as the detection filters. The QAWTF, constructed based on dual tree complex wavelet transform, possesses better vibration transient signature extracting ability and enhanced time-frequency localizability compared with conventional wavelet packet transforms (WPTs). Moreover, in the constructed QAWTF, a non-dyadic ensemble wavelet subband generating strategy is put forward to produce extra wavelet subbands that are capable of identifying fault features located in transition-band of WPT. On the other hand, an enhanced signal impulsiveness evaluating indicator, named "spatial-spectral ensemble kurtosis" (SSEK), is put forward and utilized as the quantitative measure to select optimal analyzing parameters. The SSEK indicator is robuster in evaluating the impulsiveness intensity of vibration signals due to its better suppressing ability of Gaussian noise, harmonics and sporadic impulsive shocks. Numerical validations, an experimental test and two engineering applications were used to verify the effectiveness of the proposed technique. The analyzing results of the numerical validations, experimental tests and engineering applications demonstrate that the proposed technique possesses robuster transient vibration content detecting performance in comparison with the original FK and the WPT-based FK method, especially when they are applied to the processing of vibration signals of relative limited duration.

Chen, BinQiang; Zhang, ZhouSuo; Zi, YanYang; He, ZhengJia; Sun, Chuang



Distance browsing in spatial databases  

SciTech Connect

The authors compare two different techniques for browsing through a collection of spatial objects stored in an R-tree spatial data structure on the basis of their distances from an arbitrary spatial query object. The conventional approach is one that makes use of a k-nearest neighbor algorithm where k is known prior to the invocation of the algorithm. Thus if m {gt} k neighbors are needed, the k-nearest neighbor algorithm has to be reinvoked for m neighbors, thereby possibly performing some redundant computations. The second approach is incremental in the sense that having obtained the k nearest neighbors, the k + 1{sup st} neighbor can be obtained without having to calculate the k + 1 nearest neighbors from scratch. The incremental approach is useful when processing complex queries where one of the conditions involves spatial proximity (e.g., the nearest city to Chicago with population greater than a million), in which case a query engine can make use of a pipelined strategy. The authors present a general incremental nearest neighbor algorithm that is applicable to a large class of hierarchical spatial data structures. This algorithm is adapted to the R-tree and its performance is compared to an existing k-nearest neighbor algorithm for R-trees. Experiments show that the incremental nearest neighbor algorithm significantly outperforms the k-nearest neighbor algorithm for distance browsing queries in a spatial database that uses the R-tree as a spatial index. Moreover, the incremental nearest neighbor algorithm usually outperforms the k-nearest neighbor algorithm when applied to the k-nearest neighbor problem for the R-tree, although the improvement is not nearly as large as for distance browsing queries. In fact, they prove informally that at any step in its execution the incremental nearest neighbor algorithm is optimal with respect to the spatial data structure that is employed. Furthermore, based on some simplifying assumptions, they prove that in two dimensions the number of distance computations and leaf nodes accesses made by the algorithm for finding k neighbors is O (k + k).

Hjaltason, G.R.; Samet, H.



SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics  

PubMed Central

Summary: SPREAD is a user-friendly, cross-platform application to analyze and visualize Bayesian phylogeographic reconstructions incorporating spatial–temporal diffusion. The software maps phylogenies annotated with both discrete and continuous spatial information and can export high-dimensional posterior summaries to keyhole markup language (KML) for animation of the spatial diffusion through time in virtual globe software. In addition, SPREAD implements Bayes factor calculation to evaluate the support for hypotheses of historical diffusion among pairs of discrete locations based on Bayesian stochastic search variable selection estimates. SPREAD takes advantage of multicore architectures to process large joint posterior distributions of phylogenies and their spatial diffusion and produces visualizations as compelling and interpretable statistical summaries for the different spatial projections. Availability: SPREAD is licensed under the GNU Lesser GPL and its source code is freely available as a GitHub repository: Contact:

Bielejec, Filip; Rambaut, Andrew; Suchard, Marc A.; Lemey, Philippe



Modularizing Spatial Ontologies for Assisted Living Systems  

NASA Astrophysics Data System (ADS)

Assisted living systems are intended to support daily-life activities in user homes by automatizing and monitoring behavior of the environment while interacting with the user in a non-intrusive way. The knowledge base of such systems therefore has to define thematically different aspects of the environment mostly related to space, such as basic spatial floor plan information, pieces of technical equipment in the environment and their functions and spatial ranges, activities users can perform, entities that occur in the environment, etc. In this paper, we present thematically different ontologies, each of which describing environmental aspects from a particular perspective. The resulting modular structure allows the selection of application-specific ontologies as necessary. This hides information and reduces complexity in terms of the represented spatial knowledge and reasoning practicability. We motivate and present the different spatial ontologies applied to an ambient assisted living application.

Hois, Joana


Spatial ontologies for tactical behaviors  

NASA Astrophysics Data System (ADS)

We address spatial ontologies for the areas of operations of tactical behaviors carried out by unmanned ground vehicles (UGVs). An ontology is a conceptualization of a domain and provides a common vocabulary for automated applications in the domain of interest. Ontological concepts are typically qualitative yet are rigorously defined. An ontology should provide abstract concepts that allow meaningful generalizations. The work reported here is the first known attempt to apply spatial ontologies to tactical behaviors. Some research on spatial ontologies is based on point set topology, although many find points to be unnatural primitives. Alternatives include relations defined in terms of the primitive binary relation "connected_to" on regions; the "part_of" relation is also important. This paper includes a focused survey driven by examples in which we evaluate the strengths and weaknesses of the different approaches for the domain in question. We also develop new concepts and techniques especially applicable to representing and reasoning about areas of operation in which UGVs perform missions.

BouSaba, Chafic W.; Esterline, Albert C., Jr.; Homaifar, Abdollah; Fatehi, Fereshteh



Virtual-memory tiling for spatial data handling in GIS  

Microsoft Academic Search

Virtual-memory tiling enables applications efficiently to handle much larger arrays of raster spatial data more efficiently than is otherwise possible, without requiring specialist computing resources. It has particular application to geographical information systems (GIS) given the wide availability of large sets of digital raster spatial data from remote sensing and other sources. The size of these data sets often greatly

J. E. McCormack; J. Hogg



Modal Logics for Qualitative Spatial Reasoning  

Microsoft Academic Search

Spatial reasoning is essential for many AI applications. In most existing systems the representationis primarily numerical, so the information that can be handled is limited to precise quantitative data.However, for many purposes the ability to manipulate high-level qualitative spatial information ina flexible way would be extremely useful. Such capabilities can be proveded by logical calculi; andindeed 1st-order theories of certain

Brandon Bennett



Part I: Temporal and spatial distribution of multiclass pesticide residues in lake waters of Northern Greece: application of an optimized SPE-UPLC-MS/MS pretreatment and analytical method.  


The present work describes the application of an analytical procedure, utilizing ultra performance liquid chromatography (UPLC) coupled with mass spectrometry instrumentation, for the determination of 253 multiclass pesticides, classified in six different groups. Solid phase extraction was applied for the isolation and pre-concentration of target compounds in water samples. Surface waters of the lakes located in Northern Greece (Volvi, Doirani, and Kerkini), were collected in two time periods (fall/winter 2010 and spring/summer 2011) and analyzed, applying the developed analytical methods. Spatial distribution of detected pesticides was visualized using interpolation methods and geographical information systems (GIS). Pesticides with maximum concentrations were amitrole, propoxur, simazine, chlorpyrifos, carbendazim, triazophos, disulfoton-sulfone, pyridaben, sebuthylazine, terbuthylazine, atrazine, atrazine-desethyl, bensulfuron-methyl, metobromuron, metribuzin, rotenone, pyriproxyfen, and rimsulfuron. In Lake Kerkini, mainly carbamates and triazines were determined at elevated concentrations, near the coastal point of the NW side of the lake. Seasonal variations were strong among the applied pesticide classes and determined concentrations, indicating the contribution of pesticide application patterns and rainfall. Lake Doirani exhibited organophosphate pesticides at higher concentrations mainly at coastal points, while triazines emerged as the main pollutant during spring sampling. Lake Volvi exhibited the highest pesticide concentrations, mostly triazines and ureas at the central part of the lake. The occurrence of extreme values and nonconstant seasonal variations indicated that the concentrations were increased disproportionately during the second sampling, as a result of the varying contribution of pollution sources right after the application period. In all cases, the total concentration of pesticides increased during the second sampling period. PMID:24696214

Kalogridi, Eleni-Chrysoula; Christophoridis, Christophoros; Bizani, Erasmia; Drimaropoulou, Garyfallia; Fytianos, Konstantinos




NASA Astrophysics Data System (ADS)

Welding, brazing, and soldering are thermal processes used to join material. Laser technology has been applied for these processes for many years. The main principle of all laser-supported joining technologies is the absorption of laser radiation near to the contact area of the joining partners and — if used — also at the filler material, the transformation of the radiation energy into heat and the transition of part of the irradiated material into the molten (metals) or plasticized (polymers) state. This phase transformation allows the creation of a solid joint by resolidification of the molten or plasticized volume and bridging the gap between the joining partners. This happens spatially behind the interaction zone being moved along the joint track or simply temporally after the laser is switched off.

Petring, D.; Polzin, R.; Becker, M.


Spatial cointegration and heteroscedasticity  

NASA Astrophysics Data System (ADS)

A two-step Lagrange Multiplier test strategy has recently been suggested as a tool to reveal spatial cointegration. The present paper generalises the test procedure by incorporating control for unobserved heteroscedasticity. Using Monte Carlo simulation, the behaviour of several relevant tests for spatial cointegration and/or heteroscedasticity is investigated. The two-step test for spatial cointegration appears to be robust towards heteroscedasticity. While several tests for heteroscedasticity prove to be inconclusive under certain circumstances, a Lagrange Multiplier test for heteroscedasticity based on spatially differenced variables is shown to serve well as an indication of heteroscedasticity irrespective of cointegration status.

Lauridsen, Jørgen; Kosfeld, Reinhold



Individual differences in spatial text processing: High spatial ability can compensate for spatial working memory interference  

Microsoft Academic Search

The present study investigates the relation between spatial ability and visuo-spatial and verbal working memory in spatial text processing. In two experiments, participants listened to a spatial text (Experiments 1 and 2) and a non-spatial text (Experiment 1), at the same time performing a spatial or a verbal concurrent task, or no secondary task. To understand how individuals who differ

Chiara Meneghetti; Valérie Gyselinck; Francesca Pazzaglia; Rossana De Beni



Individual Differences in Spatial Text Processing: High Spatial Ability Can Compensate for Spatial Working Memory Interference  

ERIC Educational Resources Information Center

The present study investigates the relation between spatial ability and visuo-spatial and verbal working memory in spatial text processing. In two experiments, participants listened to a spatial text (Experiments 1 and 2) and a non-spatial text (Experiment 1), at the same time performing a spatial or a verbal concurrent task, or no secondary task.…

Meneghetti, Chiara; Gyselinck, Valerie; Pazzaglia, Francesca; De Beni, Rossana



Querying spatial patterns  

Microsoft Academic Search

Spatial data are common in many scientific and commercial domains such as geographical information systems and gene\\/protein expression profiles. Querying for distribution patterns on such data can discover underlying spatial relationships and suggest avenues for further scientific exploration. Supporting such pattern retrieval requires not only the formulation of an appropriate scoring function for defining relevant connected subregions, but also the

Vishwakarma Singh; Arnab Bhattacharya; Ambuj K. Singh



Spatial Join Indices  

Microsoft Academic Search

Algorithms based on grid files as the underlying spatial index are presented for spatial joins in databases which store images, pictures, maps and drawings. For typical data distributions, it is shown that the size of the index and its maintenance cost are relatively small. The effect of diagonal distributions and different densities of the two grid files on the size

Doron Rotem



Discriminative spatial pyramid  

Microsoft Academic Search

Spatial Pyramid Representation (SPR) is a widely used method for embedding both global and local spatial information into a feature, and it shows good performance in terms of generic image recognition. In SPR, the image is divided into a sequence of increasingly finer grids on each pyramid level. Features are extracted from all of the grid cells and are concatenated

Tatsuya Harada; Yoshitaka Ushiku; Yuya Yamashita; Yasuo Kuniyoshi



Neurophysiology of Spatial Cognition.  


Understanding of the neurophysiology of cognition is advancing through the study of how animals navigate and understand space. Manipulating various classes of spatial information and recording from hippocampal neurons provides a robust model for understanding how the brain stores and constructs the spatial memories that are critical for organizing daily experience. PMID:11390917

Bures, Jan; Fenton, André A.



Spatial attention in vision  

Microsoft Academic Search

Human observers can selectively allocate processing resources to different areas of the visual field within a single fixation. This spatial attention system may affect either the quality of information extraction or the decisions and responses based on this information. This paper reviews evidence from behavioral, single-unit, and event-related potential paradigms; the evidence suggests a relatively “early” locus of spatial attention.

James E. Hoffman



Statistical analysis of pair-wise compatibility of spatially nearest neighbor and adjacent residues in alpha-helix and beta-strands: application to a minimal model for secondary structure prediction.  


Secondary structural elements like alpha-helix and beta-strands possess distinctly different structural features and thus the relative positioning of the nearest neighbor residues, and also the sequence-wise adjacent residues is important in determining the structural preference. In the present work we have statistically examined the pair-wise compatibility pattern of physically nearest neighbors and separately the adjacent residue pairs along the sequence in between the nearest neighbor partners in alpha-helices and beta-strands. It has been demonstrated that the patterns and hence, the physical basis of the compatibility of adjacent residue pairs and the spatially nearest neighbors are significantly different in most cases. The influence of tertiary contacts on the pair-wise compatibility is shown to be significant for beta-strands while it is small for alpha-helices. Based on the compatibility of physically nearest neighbors and the sequence-wise adjacent residue pairs, a minimal model has been constructed to predict the alpha-helices, beta-strands and coils of a protein from its sequence. Application of this method to 100 sequences shows that it has a predictive capability comparable to that of other more sophisticated statistical methods. PMID:12504253

Sen, Srikanta



SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data  

NASA Astrophysics Data System (ADS)

To support their analytical processes, today's organizations deploy data warehouses and client tools such as OLAP (On-Line Analytical Processing) to access, visualize, and analyze their integrated, aggregated and summarized data. Since a large part of these data have a spatial component, better client tools are required to take full advantage of the geometry of the spatial phenomena or objects being analyzed. With this regard, Spatial OLAP (SOLAP) technology offers promising possibilities. A SOLAP tool can be defined as "a type of software that allows rapid and easy navigation within spatial databases and that offers many levels of information granularity, many themes, many epochs and many display modes synchronized or not: maps, tables and diagrams" [Bédard, Y., Proulx, M.J., Rivest, S., 2005. Enrichissement du OLAP pour l'analyse géographique: exemples de réalisation et différentes possibilités technologiques. In: Bentayeb, F., Boussaid, O., Darmont, J., Rabaseda, S. (Eds.), Entrepôts de Données et Analyse en ligne, RNTI B_1. Paris: Cépaduès, pp. 1-20]. SOLAP tools offer a new user interface and are meant to be client applications sitting on top of multi-scale spatial data warehouses or datacubes. As they are based on the multidimensional paradigm, they facilitate the interactive spatio-temporal exploration of data. The purpose of this paper is to discuss how SOLAP concepts support spatio-temporal exploration of data and then to present the geovisualization, interactivity, and animation features of the SOLAP software developed by our research group. This paper first reviews the general concepts behind OLAP and SOLAP systems. This is followed by a discussion of how these SOLAP concepts support spatio-temporal exploration of data. In the subsequent section, SOLAP software is introduced along with features that enable geovisualization, interactivity and animation.

Rivest, Sonia; Bédard, Yvan; Proulx, Marie-Josée; Nadeau, Martin; Hubert, Frederic; Pastor, Julien


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

ERIC Educational Resources Information Center

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…

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



The spatial rotator.  


This paper presents a new local volume estimator, the spatial rotator, which is based on measurements on a virtual 3D probe, using computer assisted microscopy. The basic design of the probe builds upon the rotator principle which requires only a few manual intersection markings, thus making the spatial rotator fast to use. Since a 3D probe is involved, it is expected that the spatial rotator will be more efficient than the the nucleator and the planar rotator, which are based on measurements in a single plane. An extensive simulation study shows that the spatial rotator may be more efficient than the traditional local volume estimators. Furthermore, the spatial rotator can be seen as a further development of the Cavalieri estimator, which does not require randomization of sectioning or viewing direction. The tissue may thus be sectioned in any arbitrary direction, making it easy to identify the specific tissue region under study. In order to use the spatial rotator in practice, however, it is necessary to be able to identify intersection points between cell boundaries and test rays in a series of parallel focal planes, also at the peripheral parts of the cell boundaries. In cases where over- and underprojection phenomena are not negligible, they should therefore be corrected for if the spatial rotator is to be applied. If such a correction is not possible, it is needed to avoid these phenomena by using microscopy with increased resolution in the focal plane. PMID:23488880

Rasmusson, A; Hahn, U; Larsen, J O; Gundersen, H J G; Jensen, E B Vedel; Nyengaard, J R



Clustering of estimated spatial locations in networked sensors  

NASA Astrophysics Data System (ADS)

Multisensor data fusion combines data from multiple sensors to overcome interferences that may not be possible from a single sensor or source alone. In military application data fusion can be used to integrate the individual sensor data into common operational picture of the battlefield. However, there is still possibility to improve quality of the individual sensor. Improving of accuracy in estimation of spatial location is investigated in this paper. Some novel methods and algorithms for estimation of spatial location are compared such as Discrete Probability Density (DPD) method, fusion of multiple bearing lines and mean-square distance algorithm. These methods for estimation of spatial location use two-step positioning technique (indirect technique) based on estimation of a specified parameter such as angle of arrival (AOA). In the network where is possible to provide multiple spatial locations from the spatially close sources, clustering of estimated spatial location is very important. The estimated spatial locations that correspond to a source are spatially close to one another will have a larger likelihood than those estimated spatial locations that are not correspond to the source. In this paper methods and algorithms for estimation of spatial location are compared where it is multiple spatial locations, for the same sources spatially close. Clustering has been performed based on estimated spatial locations and appropriates the covariance matrix.

Pokrajac, Ivan P.; Okiljevic, Predrag; Vracar, Miodrag



Spatial filters for complex wavefront modulation.  


In this paper we propose a method to generate independent and simultaneous phase and amplitude modulation by a phase-only spatial light modulator and Fourier filtering. The incident light is modulated by a suitable phase pattern containing high spatial frequencies. The modulated light is transmitted through a 4f optical system having an appropriate spatial filter in the Fourier plane in order to synthesize the expected complex modulated wavefront on the output of the system. We propose a simple method to generate spatial filters applicable for the phase-only to complex modulated wavefront conversion. We analyze the quality of the output image related to the ideal wavefront using the proposed filters. We show that more efficient complex modulation can be realized by the proposed method than by the earlier solutions. PMID:23913064

Sarkadi, Tamás; Kettinger, Ádám; Koppa, Pál



Spatial degradation of satellite data  

Microsoft Academic Search

Two aspects of spatial degradation of satellite data are examined. The first describes a technique for spatially degrading high-resolution satellite data to produce comparable data sets over a range of coarser resolutions. In this study seven spatial resolution data sets are produced from Landsat Multispectral Scanner (MSS) data resulting in spatial resolutions ranging from 79 m to 4 km applying a spatial




Spatial decision support system for tobacco enterprise based on spatial data mining  

NASA Astrophysics Data System (ADS)

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong



Geologic spatial analysis  

SciTech Connect

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

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



A Spatial Fourier Analyser.  

National Technical Information Service (NTIS)

A device was constructed which calculates the Fourier coefficients and power spectral densities of spatially periodic signals, picked up from a set of magnetic probes positioned toroidally in a torus, or from a perpendicularly placed plasma to the magneti...

A. Ogata K. Adati



ET Spatial Techniques  

NSDL National Science Digital Library

This site from ET Spatial Techniques profiles reasonably priced, highly functional software for the ArcView/ArcGIS professionals. Links to information and free dowloads can also be found on this site.

Techniques, Et S.


Spatial filter issues  

SciTech Connect

Experiments and calculations indicate that the threshold pressure in spatial filters for distortion of a transmitted pulse scales approximately as I{sup O.2} and (F{number_sign}){sup 2} over the intensity range from 10{sup 14} to 2xlO{sup 15} W/CM{sup 2} . We also demonstrated an interferometric diagnostic that will be used to measure the scaling relationships governing pinhole closure in spatial filters.

Murray, J.E.; Estabrook, K.G.; Milam, D.; Sell, W.D.; Van Wonterghem, R.M.; Feil, M.D.; Rubenchick, A.M.



Spatial occupancy models for large data sets  

USGS Publications Warehouse

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.

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



Dealing with spatial heterogeneity  

NASA Astrophysics Data System (ADS)

Heterogeneity can be dealt with by defining homogeneous equivalent properties, known as averaging, or by trying to describe the spatial variability of the rock properties from geologic observations and local measurements. The techniques available for these descriptions are mostly continuous Geostatistical models, or discontinuous facies models such as the Boolean, Indicator or Gaussian-Threshold models and the Markov chain model. These facies models are better suited to treating issues of rock strata connectivity, e.g. buried high permeability channels or low permeability barriers, which greatly affect flow and, above all, transport in aquifers. Genetic models provide new ways to incorporate more geology into the facies description, an approach that has been well developed in the oil industry, but not enough in hydrogeology. The conclusion is that future work should be focused on improving the facies models, comparing them, and designing new in situ testing procedures (including geophysics) that would help identify the facies geometry and properties. A world-wide catalog of aquifer facies geometry and properties, which could combine site genesis and description with methods used to assess the system, would be of great value for practical applications. On peut aborder le problème de l'hétérogénéité en s'efforçant de définir une perméabilité équivalente homogène, par prise de moyenne, ou au contraire en décrivant la variation dans l'espace des propriétés des roches à partir des observations géologiques et des mesures locales. Les techniques disponibles pour une telle description sont soit continues, comme l'approche Géostatistique, soit discontinues, comme les modèles de faciès, Booléens, ou bien par Indicatrices ou Gaussiennes Seuillées, ou enfin Markoviens. Ces modèles de faciès sont mieux capables de prendre en compte la connectivité des strates géologiques, telles que les chenaux enfouis à forte perméabilité, ou au contraire les faciès fins de barrières de perméabilité, qui ont une influence importante sur les écoulement, et, plus encore, sur le transport. Les modè les génétiques récemment apparus ont la capacité de mieux incorporer dans les modèles de faciès les observations géologiques, chose courante dans l'industrie pétrolière, mais insuffisamment développée en hydrogéologie. On conclut que les travaux de recherche ultérieurs devraient s'attacher à développer les modèles de faciès, à les comparer entre eux, et à mettre au point de nouvelles méthodes d'essais in situ, comprenant les méthodes géophysiques, capables de reconnaître la géométrie et les propriétés des faciès. La constitution d'un catalogue mondial de la géométrie et des propriétés des faciès aquifères, ainsi que des méthodes de reconnaissance utilisées pour arriver à la détermination de ces systèmes, serait d'une grande importance pratique pour les applications. La heterogeneidad se puede manejar por medio de la definición de características homogéneas equivalentes, conocidas como promediar o tratando de describir la variabilidad espacial de las características de las rocas a partir de observaciones geológicas y medidas locales. Las técnicas disponibles para estas descripciones son generalmente modelos geoestadísticos continuos o modelos de facies discontinuos como los modelos Boolean, de Indicador o de umbral de Gaussian y el modelo de cadena de Markow. Estos modelos de facies son mas adecuados para tratar la conectvidad de estratos geológicos (por ejemplo canales de alta permeabilidad enterrados o barreras de baja permeabilidad que tienen efectos importantes sobre el flujo y especialmente sobre el transporte en los acuíferos. Los modelos genéticos ofrecen nuevas formas de incorporar más geología en las descripciones de facies, un enfoque que está bien desarollado en la industria petrolera, pero insuficientemente en la hidrogeología. Se concluye que los trabajos futuros deberían estar más enfocados en mejorar los modelos de facies, en establecer comparaciones y en

Marsily, Gh.; Delay, F.; Gonçalvès, J.; Renard, Ph.; Teles, V.; Violette, S.



Comparative study of different spatial\\/spatial-frequency methods (Gabor filters, wavelets, wavelets packets) for texture segmentation\\/classification  

Microsoft Academic Search

The interest manifested into texture recognition has had a substantial growth since these past few years. Much research is focused on a joint space\\/spatial-frequency representation of images. This paper describes the comparison between different spatial\\/spatial-frequency methods involving Gabor filters and wavelets. Two applications are considered: image segmentation and texture classification\\/recognition. It has been seen that results can depend significantly on

Philippe Vautrot; Noel Bonnet; Michel Herbin



Comparing the Sexes on Spatial Abilities: Map-Use Skills  

Microsoft Academic Search

Studies by psychologists suggest that males are more proficient than females in performing many types of spatial tasks. There is no information, however, as to whether the results of psychological research are relevant and applicable to geography. This paper summarizes psychologists' views of spatial skills, discusses them from a geographical perspective, and reports the results of five map-use experiments that

Patricia P. Gilmartin; Jeffrey C. Patton



Mining geo-spatial temporal patterns from soccer games  

Microsoft Academic Search

In this proposal we design a prototype demonstration of the soccer game analyzer using concepts of spatial databases. The availability of such application can enhance coaching strategies, enhance AI game simulations, and identify trends causing injuries and gather similar observations derived from mining game play spatial data. We propose the relational model, schema and indexing for this database as well

Paul Lesov



Microsoft Academic Search

In the analysis of geocoded statistical data, common practice has been to treat the data in isolation from its locational or spatial characteristics. This results in a potentially critical loss of the spatial information that is contained in the mapped representation of the statisti cal data but not in the application of aspatial statistical techniques such as cross-sectional regression. One

Barry J. Glick; Stephen A. Hirsch


Knowledge Discovery in Spatial Databases Progress and Challenges  

Microsoft Academic Search

Spatial data, i.e., data related to objects that occupyspace, are continuosly being collected forvarious applications ranging from remote sensing,geographical information systems (GIS) to computercartography and environmental assesmentand planing. The volume of data collected is sohuge that it has become humanely impossible todo any intelligent data analysis. Even thoughvery few methods have been proposed and appliedto discover knowledge from spatial data,

Junas Adhikary



An interactive framework for raster data spatial joins  

Microsoft Academic Search

Many Geographic Information System (GIS) applications must handle large geospatial datasets stored in raster rep- resentation. Spatial joins over raster data are important queries in GIS for data analysis and decision support. How- ever, evaluating spatial joins can be very time intensive due to the size of these datasets. In this paper we propose a new interactive framework that allows

Wan D. Bae; Petr Vojtechovský; Shayma Alkobaisi; Scott T. Leutenegger; Seon Ho Kim



Spatial ecology across scales.  


The international conference 'Models in population dynamics and ecology 2010: animal movement, dispersal and spatial ecology' took place at the University of Leicester, UK, on 1-3 September 2010, focusing on mathematical approaches to spatial population dynamics and emphasizing cross-scale issues. Exciting new developments in scaling up from individual level movement to descriptions of this movement at the macroscopic level highlighted the importance of mechanistic approaches, with different descriptions at the microscopic level leading to different ecological outcomes. At higher levels of organization, different macroscopic descriptions of movement also led to different properties at the ecosystem and larger scales. New developments from Levy flight descriptions to the incorporation of new methods from physics and elsewhere are revitalizing research in spatial ecology, which will both increase understanding of fundamental ecological processes and lead to tools for better management. PMID:21068027

Hastings, Alan; Petrovskii, Sergei; Morozov, Andrew



The Spatial Standard Observer  

NASA Technical Reports Server (NTRS)

The spatial standard observer is a computational model that provides a measure of the visibility of a target in a uniform background image or of the visual discriminability of two images. Standard observers have long been used in science and industry to quantify the discriminability of colors. Color standard observers address the spectral characteristics of visual stimuli, while the spatial standard observer (SSO), as its name indicates, addresses spatial characteristics. The SSO is based on a model of human vision. The SSO was developed in a process that included evaluation of a number of earlier mathematical models that address optical, physiological, and psychophysical aspects of spatial characteristics of human visual perception. Elements of the prior models are incorporated into the SSO, which is formulated as a compromise between accuracy and simplicity. The SSO operates on a digitized monochrome still image or on a pair of such images. The SSO consists of three submodels that operate sequentially on the input image(s): 1. A contrast model, which converts an input monochrome image to a luminance contrast image, wherein luminance values are expressed as excursions from, and normalized to, a mean; 2. A contrast-sensitivity-filter model that includes an oblique-effect filter (which accounts for the decline in contrast sensitivity at oblique viewing angles); and 3. A spatial summation model, in which responses are spatially pooled by raising each pixel to the power beta, adding the results, and raising the sum to the 1/b power. In this model, b=2.9 was found to be a suitable value. The net effect of the SSO is to compute a numerical measure of the perceptual strength of the single image, or of the visible difference (denoted the perceptual distance) between two images. The unit of a measure used in the SSO is the just noticeable difference (JND), which is a standard measure of perceptual discriminability. A target that is just visible has a measure of 1 JND.

Watson, Andrew B.; Ahumada, Albert J, Jr.



Fuzzy Spatial Data Types and Predicates: Their Deflnition and Integration into Query Languages  

Microsoft Academic Search

Representing, storing, quering, and manipulating spatial information is im-portant for many non-standard database applications. Specialized systems like geographical information systems (GIS) and spatial database systems to a certain extent provide the needed technology to support these applications. So far, spatial data modeling has implicitly assumed that the extent and hence the borders of spatial phenomena are precisely determined, homoge-neous, and

Markus Schneider


Spatial light modulator microscopy.  


The use of spatial light modulators (SLMs) for two-photon laser microscopy is described. SLM phase modulation can be used to generate nearly any spatiotemporal pattern of light, enabling simultaneous illumination of any number of selected regions of interest. We take advantage of this flexibility to perform fast two-photon imaging or uncaging experiments on dendritic spines and neocortical neurons. By operating in the spatial Fourier plane, an SLM can effectively mimic any arbitrary optical transfer function and thus replace, in software, many of the functions provided by hardware in standard microscopes, such as focusing, magnification, and aberration correction. PMID:24298039

Nikolenko, Volodymyr; Peterka, Darcy S; Araya, Roberto; Woodruff, Alan; Yuste, Rafael



Reconstructing Spatial Distributions from Anonymized Locations  

SciTech Connect

Devices such as mobile phones, tablets, and sensors are often equipped with GPS that accurately report a person's location. Combined with wireless communication, these devices enable a wide range of new social tools and applications. These same qualities, however, leave location-aware applications vulnerable to privacy violations. This paper introduces the Negative Quad Tree, a privacy protection method for location aware applications. The method is broadly applicable to applications that use spatial density information, such as social applications that measure the popularity of social venues. The method employs a simple anonymization algorithm running on mobile devices, and a more complex reconstruction algorithm on a central server. This strategy is well suited to low-powered mobile devices. The paper analyzes the accuracy of the reconstruction method in a variety of simulated and real-world settings and demonstrates that the method is accurate enough to be used in many real-world scenarios.

Horey, James L [ORNL] [ORNL; Forrest, Stephanie [University of New Mexico, Albuquerque] [University of New Mexico, Albuquerque; Groat, Michael [University of New Mexico, Albuquerque] [University of New Mexico, Albuquerque



Effect of Sound Spatialization on Responses to Overlapping Messages.  

National Technical Information Service (NTIS)

The purpose of this research was to determine if a spatialized headphone display would improve users' recognition accuracy when listening to more than two overlapping messages. This type of task has numerous applications in a variety of different military...

J. R. Campbell




EPA Science Inventory

This paper describes the application of aerial photography and GIS technology to develop flexible and transferable methods for multi-spatial scale characterization and analysis of riparian corridors. Relationships between structural attributes of riparian corridors and indicator...


Perceptual categories for spatial layout.  

PubMed Central

The central problems of vision are often divided into object identification and localization. Object identification, at least at fine levels of discrimination, may require the application of top-down knowledge to resolve ambiguous image information. Utilizing top-down knowledge, however, may require the initial rapid access of abstract object categories based on low-level image cues. Does object localization require a different set of operating principles than object identification or is category determination also part of the perception of depth and spatial layout? Three-dimensional graphics movies of objects and their cast shadows are used to argue that identifying perceptual categories is important for determining the relative depths of objects. Processes that can identify the causal class (e.g. the kind of material) that generates the image data can provide information to determine the spatial relationships between surfaces. Changes in the blurriness of an edge may be characteristically associated with shadows caused by relative motion between two surfaces. The early identification of abstract events such as moving object/shadow pairs may also be important for depth from shadows. Knowledge of how correlated motion in the image relates to an object and its shadow may provide a reliable cue to access such event categories.

Kersten, D



Spatial management of data  

Microsoft Academic Search

Spatial data management is a technique for organizing and retrieving information by positioning it in a graphical data space (GDS). This graphical data space is viewed through a color raster-scan display which enables users to traverse the GDS surface or zoom into the image to obtain greater detail. In contrast to conventional database management systems, in which users access data

Christopher F. Herot



Bayesian Spatial Quantile Regression  

PubMed Central

Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997–2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast.

Reich, Brian J.; Fuentes, Montserrat; Dunson, David B.



Handbook of Spatial Cognition  

ERIC Educational Resources Information Center

Spatial cognition is a branch of cognitive psychology that studies how people acquire and use knowledge about their environment to determine where they are, how to obtain resources, and how to find their way home. Researchers from a wide range of disciplines, including neuroscience, cognition, and sociology, have discovered a great deal about how…

Waller, David, Ed.; Nadel, Lynn, Ed.



Spatially Augmented Reality  

Microsoft Academic Search

To create an effective illusion of virtual objects coexisting with the real world, see-through HMD-based Augmented Reality techniques supplement the user's view with images of virtual objects. We introduce here a new paradigm, Spatially Augmented Reality (SAR), where virtual objects are rendered directly within or on the user's physical space. A key benefit of SAR is that the user does

Ramesh Raskar; Greg Welch; Henry Fuchs


Bayesian Spatial Quantile Regression.  


Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997-2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794

Reich, Brian J; Fuentes, Montserrat; Dunson, David B



Cartography: LACIE's spatial processor  

NASA Technical Reports Server (NTRS)

The spatial processing needs of LACIE include the location of agricultural test sites, and the registration of ground truth to LANDSAT imagery. The technological aspects of LACIE cartographic support, the need for cartography in satellite crop surveys, and proposed improvements which would enhance support of future programs are discussed.

Rader, M. L.; Vela, R. R. (principal investigators)




EPA Science Inventory

This spatial database contains boundaries and attributes describing Level III ecoregions in EPA Region 8. The ecoregions shown here have been derived from Omernik (1987) and from refinements of Omernik's framework that have been made for other projects. These ongoing or re...


Spatially Resolved Luminescence Spectroscopy  

NASA Astrophysics Data System (ADS)

Spatially resolved luminescence spectroscopy is a useful tool for the study of semiconductors with inhomogeneities of their properties on submicrometer scale and semiconductor nanostructures. In this chapter, basic operation principles, instrumentation, and advantages and disadvantages of micro-photoluminescence (?-PL), confocal microscopy, scanning near-field optical microscopy (SNOM), and cathodoluminescence (CL) are discussed.

Tamulaitis, Gintautas


Spatial strategies for managing visitor impacts in National Parks  

USGS Publications Warehouse

Resource and social impacts caused by recreationists and tourists have become a management concern in national parks and equivalent protected areas. The need to contain visitor impacts within acceptable limits has prompted park and protected area managers to implement a wide variety of strategies and actions, many of which are spatial in nature. This paper classifies and illustrates the basic spatial strategies for managing visitor impacts in parks and protected areas. A typology of four spatial strategies was proposed based on the recreation and park management literature. Spatial segregation is a common strategy for shielding sensitive resources from visitor impacts or for separating potentially conflicting types of use. Two forms of spatial segregation are zoning and closure. A spatial containment strategy is intended to minimize the aggregate extent of visitor impacts by confining use to limited designated or established Iocations. In contrast, a spatial dispersal strategy seeks to spread visitor use, reducing the frequency of use to levels that avoid or minimize permanent resource impacts or visitor crowding and conflict. Finally, a spatial configuration strategy minimizes impacting visitor behavior though the judicious spatial arrangement of facilities. These four spatial strategics can be implemented separately or in combination at varying spatial scales within a single park. A survey of national park managers provides an empirical example of the diversity of implemented spatial strategies in managing visitor impacts. Spatial segregation is frequently applied in the form of camping restrictions or closures to protect sensitive natural or cultural resources and to separate incompatible visitor activities. Spatial containment is the most widely applied strategy for minimizing the areal extent of resource impacts. Spatial dispersal is commonly applied to reduce visitor crowding or conflicts in popular destination areas but is less frequently applied or 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.

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




Microsoft Academic Search

Increasing application of Geospatial information requires integration , fusion and interoperability of current monolithic GIS, especially more complex and multidisciplinary involved application. Interoperability is base for information integration and fusion. we give five-level GIS interoperability model(InteroModel5). The spatial information infrastructure(SII) provides a sharing spatial information framework , architecture and an interoperability platform for geographical information system. This paper studies architecture

Shanzhen Yi; Qi Li; Jicheng Cheng



Transillumination spatially modulated illumination microscopy  

NASA Astrophysics Data System (ADS)

The diagnostic utility of a conventional transillumination microscope, the most common imaging modality in clinical use today, is limited by the microscope's resolution. It is, however, possible to achieve lateral resolution well beyond the classical limit by using laterally structured illumination in a wide-field, nonconfocal microscope. In this method, the spatially modulated illumination (SMI) makes high-resolution information that is normally inaccessible visible in the observed image. Previously presented SMI microscopy systems operated in epifluorescence mode. We describe the design, construction, and testing of a novel transillumination SMI microscope. As transillumination is necessary for most medical applications, such as histopathologic evaluation of biopsy tissue and chromosomal analysis, such a system should have a significant diagnostic effect.

Pitris, Costas; Eracleous, Peter



The Impact of Spatial Scales and Spatial Smoothing on the Outcome of Bayesian Spatial Model  

PubMed Central

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matérn correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.

Kang, Su Yun; McGree, James; Mengersen, Kerrie



Numerical modeling of spatial coherence using the elementary function method.  


The elementary function method is an approximate method for propagation calculations in spatially, partially coherent light in two dimensions. In this paper, we present the numerical application of this method to a 248 nm UV excimer laser source. We present experimental results of the measurement of the degree of spatial coherence and the beam profile of this source. The elementary function method is then applied to the real beam data and used to simulate the effects of imaging an opaque edge with a source of varying degrees of spatial coherence. The effect of spatial coherence on beam homogenization is also presented. PMID:23669693

Smith, Arlene; Dainty, Christopher



Hierarchical Modeling for Spatial Data Problems  

PubMed Central

This short paper is centered on hierarchical modeling for problems in spatial and spatio-temporal statistics. It draws its motivation from the interdisciplinary research work of the author in terms of applications in the environmental sciences - ecological processes, environmental exposure, and weather modeling. The paper briefly reviews hierarchical modeling specification, adopting a Bayesian perspective with full inference and associated uncertainty within the specification, while achieving exact inference to avoid what may be uncomfortable asymptotics. It focuses on point-referenced (geo-statistical) and point pattern spatial settings. It looks in some detail at problems involving data fusion, species distributions, and large spatial datasets. It also briefly describes four further examples arising from the author's recent research projects.

Gelfand, Alan E.



Spatial and spectral coherent control with frequency combs  

NASA Astrophysics Data System (ADS)

Quantum coherent control is a powerful tool for steering the outcome of quantum processes towards a desired final state by the accurate manipulation of quantum interference between multiple pathways. Although coherent control techniques have found applications in many fields of science, the possibilities for spatial and high-resolution frequency control have remained limited. Here, we show that the use of counter-propagating broadband pulses enables the generation of fully controlled spatial excitation patterns. This spatial control approach also provides decoherence reduction, which allows the use of the high-frequency resolution of an optical frequency comb. We exploit the counter-propagating geometry to perform spatially selective excitation of individual species in a multicomponent gas mixture, as well as frequency determination of hyperfine constants of atomic rubidium with unprecedented accuracy. The combination of spectral and spatial coherent control adds a new dimension to coherent control, with applications in nonlinear spectroscopy, microscopy and high-precision frequency metrology, among others.

Barmes, Itan; Witte, Stefan; Eikema, Kjeld S. E.



Children's spatial thinking: Does talk about the spatial world matter?  

PubMed Central

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 child age 14 to 46 months in a diverse sample of 52 parent-child dyads interacting in their home settings. These same children were given three non-verbal spatial tasks, items from a Spatial Transformation task (Levine et al., 1999), the Block Design subtest from the WPPSI-III (Wechsler, 2002), and items on the Spatial Analogies subtest from Primary Test of Cognitive Skills (Huttenlocher & Levine, 1990) at 54 months of age. We find that parents vary widely in the amount of spatial language they use with their children during everyday interactions. This variability in spatial language input, in turn, predicts the amount of spatial language children produce, controlling for overall parent language input. Furthermore, children who produce more spatial language are more likely to perform better on spatial problem solving tasks at a later age.

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



Spatial symmetry breaking in rapidly rotating convective spherical shells  

NASA Technical Reports Server (NTRS)

Many problems in geophysical and astrophysical convection systems are characterized by fast rotation and spherical shell geometry. The combined effects of Coriolis forces and spherical shell geometry produce a unique spatial symmetry for the convection pattern in a rapidly rotating spherical shell. In this paper, we first discuss the general spatial symmetries for rotating spherical shell convection. A special model, a spherical shell heated from below, is then used to illustrate how and when the spatial symmetries are broken. Symmetry breaking occurs via a sequence of spatial transitions from the primary conducting state to the complex multiple-layered columnar structure. It is argued that, because of the dominant effects of rotation, the sequence of spatial transitions identified from this particular model is likely to be generally valid. Applications of the spatial symmetry breaking to planetary convection problems are also discussed.

Zhang, Keke; Schubert, Gerald



Spatial Modeling of Cell Signaling Networks  

PubMed Central

The shape of a cell, the sizes of subcellular compartments and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic vs, stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling.

Cowan, Ann E.; Moraru, Ion I.; Schaff, James C.; Slepchenko, Boris M.; Loew, Leslie M.