WorldWideScience

Sample records for data fusion

  1. Fusion safety data base

    International Nuclear Information System (INIS)

    Laats, E.T.; Hardy, H.A.

    1983-01-01

    The purpose of this Fusion Safety Data Base Program is to provide a repository of data for the design and development of safe commercial fusion reactors. The program is sponsored by the United States Department of Energy (DOE), Office of Fusion Energy. The function of the program is to collect, examine, permanently store, and make available the safety data to the entire US magnetic-fusion energy community. The sources of data will include domestic and foreign fusion reactor safety-related research programs. Any participant in the DOE Program may use the Data Base Program from his terminal through user friendly dialog and can view the contents in the form of text, tables, graphs, or system diagrams

  2. Sensor Data Fusion

    DEFF Research Database (Denmark)

    Plascencia, Alfredo; Stepán, Petr

    2006-01-01

    The main contribution of this paper is to present a sensor fusion approach to scene environment mapping as part of a Sensor Data Fusion (SDF) architecture. This approach involves combined sonar array with stereo vision readings.  Sonar readings are interpreted using probability density functions...

  3. Atomic data for fusion

    Energy Technology Data Exchange (ETDEWEB)

    Hunter, H.T.; Kirkpatrick, M.I.; Alvarez, I.; Cisneros, C.; Phaneuf, R.A. (eds.); Barnett, C.F.

    1990-07-01

    This report provides a handbook of recommended cross-section and rate-coefficient data for inelastic collisions between hydrogen, helium and lithium atoms, molecules and ions, and encompasses more than 400 different reactions of primary interest in fusion research. Published experimental and theoretical data have been collected and evaluated, and the recommended data are presented in tabular, graphical and parametrized form. Processes include excitation and spectral line emission, charge exchange, ionization, stripping, dissociation and particle interchange reactions. The range of collision energies is appropriate to applications in fusion-energy research.

  4. Atomic data for fusion

    International Nuclear Information System (INIS)

    Hunter, H.T.; Kirkpatrick, M.I.; Alvarez, I.; Cisneros, C.; Phaneuf, R.A.; Barnett, C.F.

    1990-07-01

    This report provides a handbook of recommended cross-section and rate-coefficient data for inelastic collisions between hydrogen, helium and lithium atoms, molecules and ions, and encompasses more than 400 different reactions of primary interest in fusion research. Published experimental and theoretical data have been collected and evaluated, and the recommended data are presented in tabular, graphical and parametrized form. Processes include excitation and spectral line emission, charge exchange, ionization, stripping, dissociation and particle interchange reactions. The range of collision energies is appropriate to applications in fusion-energy research

  5. Multisensor data fusion algorithm development

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, D.A.; Chadwick, M.D.; Goudy, S.P.; Johnson, D.K.

    1995-12-01

    This report presents a two-year LDRD research effort into multisensor data fusion. We approached the problem by addressing the available types of data, preprocessing that data, and developing fusion algorithms using that data. The report reflects these three distinct areas. First, the possible data sets for fusion are identified. Second, automated registration techniques for imagery data are analyzed. Third, two fusion techniques are presented. The first fusion algorithm is based on the two-dimensional discrete wavelet transform. Using test images, the wavelet algorithm is compared against intensity modulation and intensity-hue-saturation image fusion algorithms that are available in commercial software. The wavelet approach outperforms the other two fusion techniques by preserving spectral/spatial information more precisely. The wavelet fusion algorithm was also applied to Landsat Thematic Mapper and SPOT panchromatic imagery data. The second algorithm is based on a linear-regression technique. We analyzed the technique using the same Landsat and SPOT data.

  6. Data fusion qualitative sensitivity analysis

    International Nuclear Information System (INIS)

    Clayton, E.A.; Lewis, R.E.

    1995-09-01

    Pacific Northwest Laboratory was tasked with testing, debugging, and refining the Hanford Site data fusion workstation (DFW), with the assistance of Coleman Research Corporation (CRC), before delivering the DFW to the environmental restoration client at the Hanford Site. Data fusion is the mathematical combination (or fusion) of disparate data sets into a single interpretation. The data fusion software used in this study was developed by CRC. The data fusion software developed by CRC was initially demonstrated on a data set collected at the Hanford Site where three types of data were combined. These data were (1) seismic reflection, (2) seismic refraction, and (3) depth to geologic horizons. The fused results included a contour map of the top of a low-permeability horizon. This report discusses the results of a sensitivity analysis of data fusion software to variations in its input parameters. The data fusion software developed by CRC has a large number of input parameters that can be varied by the user and that influence the results of data fusion. Many of these parameters are defined as part of the earth model. The earth model is a series of 3-dimensional polynomials with horizontal spatial coordinates as the independent variables and either subsurface layer depth or values of various properties within these layers (e.g., compression wave velocity, resistivity) as the dependent variables

  7. Data Fusion in Information Retrieval

    CERN Document Server

    Wu, Shengli

    2012-01-01

    The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others: -          What are the key factors that affect the performance of data fusion algorithms significantly? -          What conditions are favorable to data fusion algorithms? -          CombSum and CombMNZ, which one is better? and why? -          What is the rationale of using the linear combination method? -          How can the best fusion option be found under any given circumstances?

  8. Data fusion mathematics theory and practice

    CERN Document Server

    Raol, Jitendra R

    2015-01-01

    Fills the Existing Gap of Mathematics for Data FusionData fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in various applications that include the monitoring of vehicles, aerospace systems, large-scale structures, and large industrial automation plants. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion, and provides a

  9. The fusion engineering data base

    International Nuclear Information System (INIS)

    Musicki, Z.; Maynard, C.W.; Watanabe, Y.; Bennethum, A.; Gruetzmacher, K.

    1986-01-01

    A computerized data base, called FUSEDATA, has been conceived in order to systematically present the performance parameters of components and systems used in fusion plants and experiments. By putting together a framework where data could be systematically input, the authors made it substantially easier to install the proper data when it becomes available (at first from the experimental facilities now operating). The data base consists of different tables that contain information which defines the system, its operating and environmental conditions as well as the necessary performance data (reliability, maintenance, economics, etc.)

  10. A Review of Data Fusion Techniques

    Science.gov (United States)

    2013-01-01

    The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. We first enumerate and explain different classification schemes for data fusion. Then, the most common algorithms are reviewed. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion. PMID:24288502

  11. Nuclear data requirements for fusion reactor nucleonics

    International Nuclear Information System (INIS)

    Bhat, M.R.; Abdou, M.A.

    1980-01-01

    Nuclear data requirements for fusion reactor nucleonics are reviewed and the present status of data are assessed. The discussion is divided into broad categories dealing with data for Fusion Materials Irradiation Test Facility (FMIT), D-T Fusion Reactors, Alternate Fuel Cycles and the Evaluated Data Files that are available or would be available in the near future

  12. Data security on the national fusion grid

    International Nuclear Information System (INIS)

    Burruss, Justine R.; Fredian, Tom W.; Thompson, Mary R.

    2005-01-01

    The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER

  13. Data security on the national fusion grid

    Energy Technology Data Exchange (ETDEWEB)

    Burruss, Justine R.; Fredian, Tom W.; Thompson, Mary R.

    2005-06-01

    The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER.

  14. Categorical Data Fusion Using Auxiliary Information

    OpenAIRE

    Fosdick, Bailey K.; DeYoreo, Maria; Reiter, Jerome P.

    2015-01-01

    In data fusion, analysts seek to combine information from two databases comprised of disjoint sets of individuals, in which some variables appear in both databases and other variables appear in only one database. Most data fusion techniques rely on variants of conditional independence assumptions. When inappropriate, these assumptions can result in unreliable inferences. We propose a data fusion technique that allows analysts to easily incorporate auxiliary information on the dependence struc...

  15. Space-Time Data Fusion

    Science.gov (United States)

    Braverman, Amy; Nguyen, Hai; Olsen, Edward; Cressie, Noel

    2011-01-01

    Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.

  16. Spatial Statistical Data Fusion (SSDF)

    Science.gov (United States)

    Braverman, Amy J.; Nguyen, Hai M.; Cressie, Noel

    2013-01-01

    fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

  17. Forecasting Chronic Diseases Using Data Fusion.

    Science.gov (United States)

    Acar, Evrim; Gürdeniz, Gözde; Savorani, Francesco; Hansen, Louise; Olsen, Anja; Tjønneland, Anne; Dragsted, Lars Ove; Bro, Rasmus

    2017-07-07

    Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC-MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC-MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer.

  18. Nuclear data for fusion reactor technology

    International Nuclear Information System (INIS)

    1988-06-01

    The meeting was organized in four sessions and four working groups devoted to the following topics: Requirements of nuclear data for fusion reactor technology (6 papers); Status of experimental and theoretical investigations of microscopic nuclear data (10 papers); Status of existing libraries for fusion neutronic calculations (5 papers); and Status of integral experiments and benchmark tests (6 papers). A separate abstract was prepared for each of these papers

  19. Ontology-aided Data Fusion (Invited)

    Science.gov (United States)

    Raskin, R.

    2009-12-01

    An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

  20. Information Fusion of Conflicting Input Data

    Directory of Open Access Journals (Sweden)

    Uwe Mönks

    2016-10-01

    Full Text Available Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large amounts of data, further challenges towards the fusion algorithms arise from epistemic uncertainties (incomplete knowledge in the input signals as well as conflicts between them. These aspects must be considered during information processing to obtain reliable results, which are in accordance with the real world. The analysis of the scientific state of the art shows that current solutions fulfil said requirements at most only partly. This article proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation employing the μBalTLCS (fuzzified balanced two-layer conflict solving fusion algorithm to reduce the impact of conflicts on the fusion result. The performance of the contribution is shown by its evaluation in the scope of a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The utilised data is published and freely accessible.

  1. Information Fusion of Conflicting Input Data.

    Science.gov (United States)

    Mönks, Uwe; Dörksen, Helene; Lohweg, Volker; Hübner, Michael

    2016-10-29

    Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large amounts of data, further challenges towards the fusion algorithms arise from epistemic uncertainties (incomplete knowledge) in the input signals as well as conflicts between them. These aspects must be considered during information processing to obtain reliable results, which are in accordance with the real world. The analysis of the scientific state of the art shows that current solutions fulfil said requirements at most only partly. This article proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) employing the μ BalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. The performance of the contribution is shown by its evaluation in the scope of a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The utilised data is published and freely accessible.

  2. The Terra Data Fusion Project: An Update

    Science.gov (United States)

    Di Girolamo, L.; Bansal, S.; Butler, M.; Fu, D.; Gao, Y.; Lee, H. J.; Liu, Y.; Lo, Y. L.; Raila, D.; Turner, K.; Towns, J.; Wang, S. W.; Yang, K.; Zhao, G.

    2017-12-01

    Terra is the flagship of NASA's Earth Observing System. Launched in 1999, Terra's five instruments continue to gather data that enable scientists to address fundamental Earth science questions. By design, the strength of the Terra mission has always been rooted in its five instruments and the ability to fuse the instrument data together for obtaining greater quality of information for Earth Science compared to individual instruments alone. As the data volume grows and the central Earth Science questions move towards problems requiring decadal-scale data records, the need for data fusion and the ability for scientists to perform large-scale analytics with long records have never been greater. The challenge is particularly acute for Terra, given its growing volume of data (> 1 petabyte), the storage of different instrument data at different archive centers, the different file formats and projection systems employed for different instrument data, and the inadequate cyberinfrastructure for scientists to access and process whole-mission fusion data (including Level 1 data). Sharing newly derived Terra products with the rest of the world also poses challenges. As such, the Terra Data Fusion Project aims to resolve two long-standing problems: 1) How do we efficiently generate and deliver Terra data fusion products? 2) How do we facilitate the use of Terra data fusion products by the community in generating new products and knowledge through national computing facilities, and disseminate these new products and knowledge through national data sharing services? Here, we will provide an update on significant progress made in addressing these problems by working with NASA and leveraging national facilities managed by the National Center for Supercomputing Applications (NCSA). The problems that we faced in deriving and delivering Terra L1B2 basic, reprojected and cloud-element fusion products, such as data transfer, data fusion, processing on different computer architectures

  3. Pragmatic data fusion uncertainty concerns: Tribute to Dave L. Hall

    CSIR Research Space (South Africa)

    Blasch, E

    2016-07-01

    Full Text Available Over the course of Dave Hall's career, he highlighted various concerns associated with the implementation of data fusion methods. Many of the issues included the role of uncertainty in data fusion, practical implementation of sensor fusion systems...

  4. The ORNL Controlled Fusion Atomic Data Center

    International Nuclear Information System (INIS)

    Schultz, D.R.; Krstic, P.S.; Ownby, F.M.; Meyer, F.W.; Havener, C.C.; Bannister, M.E.; Liu, W.; Jeffery, D.J.; Stancil, P.C.

    1997-01-01

    The principal mission of the Controlled Fusion Atomic Data Center is the collection evaluation, and dissemination of atomic collision data relevant to fusion energy development. With the advent of the widespread use of the World Wide Web, the data center's resources are being placed on-line to facilitate their use by end-users (cf. http://www-cfadc.phy.ornl.gov/). As this development continues, initially disparate, individually compiled resources will be transformed into integrated tools for retrieving recommended data, or displaying and manipulating the information available. The data center's present capabilities, recent data production/evaluation efforts, and goals for future development are highlighted here

  5. Fusion Nuclear Data activities at FNL, IPR

    OpenAIRE

    P. M. Prajapati; B. Pandey; S. Jakhar; C.V. S. Rao; T. K. Basu; B. K. Nayak; S. V. Suryanarayana; A. Saxena

    2015-01-01

    This paper briefly describes the current fusion nuclear data activities at Fusion Neutronics Laboratory, Institute for Plasma Research. It consist of infrastructure development for the cross-section measurements of structural materials with an accelerator based 14 MeV neutron generator and theoretical study of the cross-section using advanced nuclear reaction modular codes EMPIRE and TALYS. It will also cover the proposed surrogate experiment to measure 55Fe (n, p) 55Mn using BARC-TIFR Pel...

  6. General software design for multisensor data fusion

    Science.gov (United States)

    Zhang, Junliang; Zhao, Yuming

    1999-03-01

    In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programing and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

  7. Data management on the fusion computational pipeline

    International Nuclear Information System (INIS)

    Klasky, S; Beck, M; Bhat, V; Feibush, E; Ludaescher, B; Parashar, M; Shoshani, A; Silver, D; Vouk, M

    2005-01-01

    Fusion energy science, like other science areas in DOE, is becoming increasingly data intensive and network distributed. We discuss data management techniques that are essential for scientists making discoveries from their simulations and experiments, with special focus on the techniques and support that Fusion Simulation Project (FSP) scientists may need. However, the discussion applies to a broader audience since most of the fusion SciDAC's, and FSP proposals include a strong data management component. Simulations on ultra scale computing platforms imply an ability to efficiently integrate and network heterogeneous components (computational, storage, networks, codes, etc), and to move large amounts of data over large distances. We discuss the workflow categories needed to support such research as well as the automation and other aspects that can allow an FSP scientist to focus on the science and spend less time tending information technology

  8. Nuclear data needs for fusion reactors

    International Nuclear Information System (INIS)

    Gohar, Y.

    1986-01-01

    The nuclear design of fusion components (e.g., first wall, blanket, shield, magnet, limiter, divertor, etc.) requires an accurate prediction of the radiation field, the radiation damage parameters, and the activation analysis. The fusion nucleonics for these tasks are reviewed with special attention to point out nuclear data needs and deficiencies which effect the design process. The main areas included in this review are tritium breeding analyses, nuclear heating calculations, radiation damage in reactor components, shield designs, and results of uncertainty analyses as applied to fusion reactor studies. Design choices and reactor parameters that impact the neutronics performance of the blanket are discussed with emphasis on the tritium breeding ratio. Nuclear data required for kerma factors, shielding analysis, and radiation damage are discussed. Improvements in the evaluated data libraries are described to overcome the existing problems. 84 refs., 11 figs., 9 tabs

  9. Data-Acquisition Systems for Fusion Devices

    NARCIS (Netherlands)

    van Haren, P. C.; Oomens, N. A.

    1993-01-01

    During the last two decades, computerized data acquisition systems (DASs) have been applied at magnetic confinement fusion devices. Present-day data acquisition is done by means of distributed computer systems and transient recorders in CAMAC systems. The development of DASs has been technology

  10. Common and distinct components in data fusion

    DEFF Research Database (Denmark)

    Smilde, Age Klaas; Mage, Ingrid; Næs, Tormod

    2016-01-01

    and understanding their relative merits. This paper provides a unifying framework for this subfield of data fusion by using rigorous arguments from linear algebra. The most frequently used methods for distinguishing common and distinct components are explained in this framework and some practical examples are given...

  11. Statistical data fusion for cross-tabulation

    NARCIS (Netherlands)

    Kamakura, W.A.; Wedel, M.

    The authors address the situation in which a researcher wants to cross-tabulate two sets of discrete variables collected in independent samples, but a subset of the variables is common to both samples. The authors propose a statistical data-fusion model that allows for statistical tests of

  12. Data Fusion for Decision Support

    Science.gov (United States)

    2014-03-27

    that the location information for some commercial roads is copyrighted. However, there is no limit to the reproduction and use of the data provided...NFDRS identifies six basic fuel models (lichens and mosses; marsh grasses and reeds; grasses and forbs; brush, shrubs, and tree reproduction ; trees...dangerous except immediately after ignition. Fires that develop headway in heavy slash or in conifer stands may be unmanageable while the extreme

  13. Multisource data fusion for documenting archaeological sites

    Science.gov (United States)

    Knyaz, Vladimir; Chibunichev, Alexander; Zhuravlev, Denis

    2017-10-01

    The quality of archaeological sites documenting is of great importance for cultural heritage preserving and investigating. The progress in developing new techniques and systems for data acquisition and processing creates an excellent basis for achieving a new quality of archaeological sites documenting and visualization. archaeological data has some specific features which have to be taken into account when acquiring, processing and managing. First of all, it is a needed to gather as full as possible information about findings providing no loss of information and no damage to artifacts. Remote sensing technologies are the most adequate and powerful means which satisfy this requirement. An approach to archaeological data acquiring and fusion based on remote sensing is proposed. It combines a set of photogrammetric techniques for obtaining geometrical and visual information at different scales and detailing and a pipeline for archaeological data documenting, structuring, fusion, and analysis. The proposed approach is applied for documenting of Bosporus archaeological expedition of Russian State Historical Museum.

  14. Nuclear data requirements for fusion reactor shielding

    International Nuclear Information System (INIS)

    Abdou, M.A.

    1979-01-01

    The nuclear data requirements for experimental, demonstration and commercial fusion reactors are reviewed. Particular emphasis is given to the shield as well as major reactor components of concern to the nuclear performance. The nuclear data requirements are defined as a result of analyzing four key areas. These are the most likely candidate materials, energy range, types of needed nuclear data, and the required accuracy in the data. Deducing the latter from the target goals for the accuracy in prediction is also discussed. A specific proposal of measurements is recommended. Priorities for acquisition of data are also assigned. (author)

  15. Classification Accuracy Increase Using Multisensor Data Fusion

    Science.gov (United States)

    Makarau, A.; Palubinskas, G.; Reinartz, P.

    2011-09-01

    The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use of classification products. Employment of hyperspectral data is another solution, but their low spatial resolution (comparing to multispectral data) restrict their usage for many applications. Another improvement can be achieved by fusion approaches of multisensory data since this may increase the quality of scene classification. Integration of Synthetic Aperture Radar (SAR) and optical data is widely performed for automatic classification, interpretation, and change detection. In this paper we present an approach for very high resolution SAR and multispectral data fusion for automatic classification in urban areas. Single polarization TerraSAR-X (SpotLight mode) and multispectral data are integrated using the INFOFUSE framework, consisting of feature extraction (information fission), unsupervised clustering (data representation on a finite domain and dimensionality reduction), and data aggregation (Bayesian or neural network). This framework allows a relevant way of multisource data combination following consensus theory. The classification is not influenced by the limitations of dimensionality, and the calculation complexity primarily depends on the step of dimensionality reduction. Fusion of single polarization TerraSAR-X, WorldView-2 (VNIR or full set), and Digital Surface Model (DSM) data allow for different types of urban objects to be classified into predefined classes of interest with increased accuracy. The comparison to classification results of WorldView-2 multispectral data (8 spectral bands) is provided and the numerical evaluation of the method in comparison to

  16. Materials design data for fusion reactors

    International Nuclear Information System (INIS)

    Tavassoli, A.A.F.

    1998-01-01

    Design data needed for fusion reactors are characterized by the diversity of materials and the complexity of loading situations found in these reactors. In addition, advanced fabrication techniques, such as hot isostatic pressing, envisaged for fabrication of single and multilayered in-vessel components, could significantly change the original materials properties for which the current design rules are written. As a result, additional materials properties have had to be generated for fusion reactors and new structural design rules formulated. This paper recalls some of the materials properties data generated for ITER and DEMO, and gives examples of how these are converted into design criteria. In particular, it gives specific examples for the properties of 316LN-IG and modified 9Cr-1Mo steels, and CuCrZr alloy. These include, determination of tension, creep, isochronous, fatigue, and creep-fatigue curves and their analysis and conversion into design limits. (orig.)

  17. Materials design data for fusion reactors

    Energy Technology Data Exchange (ETDEWEB)

    Tavassoli, A.A.F. [CEA Commissariat a l`Energie Atomique, Gif sur Yvette (France). CEREM

    1998-10-01

    Design data needed for fusion reactors are characterized by the diversity of materials and the complexity of loading situations found in these reactors. In addition, advanced fabrication techniques, such as hot isostatic pressing, envisaged for fabrication of single and multilayered in-vessel components, could significantly change the original materials properties for which the current design rules are written. As a result, additional materials properties have had to be generated for fusion reactors and new structural design rules formulated. This paper recalls some of the materials properties data generated for ITER and DEMO, and gives examples of how these are converted into design criteria. In particular, it gives specific examples for the properties of 316LN-IG and modified 9Cr-1Mo steels, and CuCrZr alloy. These include, determination of tension, creep, isochronous, fatigue, and creep-fatigue curves and their analysis and conversion into design limits. (orig.) 19 refs.

  18. Performance evaluation of multi-sensor data fusion technique for ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Multi-sensor data fusion; Test Range application; trajectory .... Kalman filtering technique utilizes the noise statistics of the underlying system under con- ..... Hall D L 1992 Mathematical techniques in multi-sensor data fusion (Boston, MA: ...

  19. ORNL's Controlled Fusion Atomic Data Center

    International Nuclear Information System (INIS)

    Barnett, C.F.; Gregory, D.C.

    1983-01-01

    The Data Center maintains a detailed bibliography of atomic data measurements and calculations for processes of interest to the fusion community. One hundred nineteen journals are regularly searched for papers of interest, including back issues to 1950. Entries are categorized by author, process, reactants, energy range, and theory/experiment. Complete bibliographies have been published since 1978 and a computerized data retrieval system is available. In addition, an updated and extended multi-volume critical compilation of cross sections (the ORNL Redbooks) is under way

  20. Geophysical data fusion for subsurface imaging

    International Nuclear Information System (INIS)

    Hoekstra, P.; Vandergraft, J.; Blohm, M.; Porter, D.

    1993-08-01

    A geophysical data fusion methodology is under development to combine data from complementary geophysical sensors and incorporate geophysical understanding to obtain three dimensional images of the subsurface. The research reported here is the first phase of a three phase project. The project focuses on the characterization of thin clay lenses (aquitards) in a highly stratified sand and clay coastal geology to depths of up to 300 feet. The sensor suite used in this work includes time-domain electromagnetic induction (TDEM) and near surface seismic techniques. During this first phase of the project, enhancements to the acquisition and processing of TDEM data were studied, by use of simulated data, to assess improvements for the detection of thin clay layers. Secondly, studies were made of the use of compressional wave and shear wave seismic reflection data by using state-of-the-art high frequency vibrator technology. Finally, a newly developed processing technique, called ''data fusion,'' was implemented to process the geophysical data, and to incorporate a mathematical model of the subsurface strata. Examples are given of the results when applied to real seismic data collected at Hanford, WA, and for simulated data based on the geology of the Savannah River Site

  1. Research on an Agricultural Knowledge Fusion Method for Big Data

    Directory of Open Access Journals (Sweden)

    Nengfu Xie

    2015-05-01

    Full Text Available The object of our research is to develop an ontology-based agricultural knowledge fusion method that can be used as a comprehensive basis on which to solve agricultural information inconsistencies, analyze data, and discover new knowledge. A recent survey has provided a detailed comparison of various fusion methods used with Deep Web data (Li, 2013. In this paper, we propose an effective agricultural ontology-based knowledge fusion method by leveraging recent advances in data fusion, such as the semantic web and big data technologies, that will enhance the identification and fusion of new and existing data sets to make big data analytics more possible. We provide a detailed fusion method that includes agricultural ontology building, fusion rule construction, an evaluation module, etc. Empirical results show that this knowledge fusion method is useful for knowledge discovery.

  2. Biases in cold fusion data; and reply

    International Nuclear Information System (INIS)

    Freedman, Stuart; Krakauer, Daniel; Jones, S.E.; Decker, D.L.; Tolley, H.D.

    1990-01-01

    These two letters represent a criticism of a claim to have observed ''cold'' nuclear fusion and the original scientists' rebuttal of the claims against them. The first authors suggest that data presented has a peculiar characteristic, which, they claim, indicates a systematic bias in the data collection process, and thus calls the claimed observation into dispute. In reply, the original workers list a huge range of checks they made, before and after receiving the criticism, making allowances for all sorts of external parameters capable of affecting their results. (UK)

  3. Review of 3d GIS Data Fusion Methods and Progress

    Science.gov (United States)

    Hua, Wei; Hou, Miaole; Hu, Yungang

    2018-04-01

    3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

  4. REVIEW OF 3D GIS DATA FUSION METHODS AND PROGRESS

    Directory of Open Access Journals (Sweden)

    W. Hua

    2018-04-01

    Full Text Available 3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

  5. Feasibility study on sensor data fusion for the CP-140 aircraft: fusion architecture analyses

    Science.gov (United States)

    Shahbazian, Elisa

    1995-09-01

    Loral Canada completed (May 1995) a Department of National Defense (DND) Chief of Research and Development (CRAD) contract, to study the feasibility of implementing a multi- sensor data fusion (MSDF) system onboard the CP-140 Aurora aircraft. This system is expected to fuse data from: (a) attributed measurement oriented sensors (ESM, IFF, etc.); (b) imaging sensors (FLIR, SAR, etc.); (c) tracking sensors (radar, acoustics, etc.); (d) data from remote platforms (data links); and (e) non-sensor data (intelligence reports, environmental data, visual sightings, encyclopedic data, etc.). Based on purely theoretical considerations a central-level fusion architecture will lead to a higher performance fusion system. However, there are a number of systems and fusion architecture issues involving fusion of such dissimilar data: (1) the currently existing sensors are not designed to provide the type of data required by a fusion system; (2) the different types (attribute, imaging, tracking, etc.) of data may require different degree of processing, before they can be used within a fusion system efficiently; (3) the data quality from different sensors, and more importantly from remote platforms via the data links must be taken into account before fusing; and (4) the non-sensor data may impose specific requirements on the fusion architecture (e.g. variable weight/priority for the data from different sensors). This paper presents the analyses performed for the selection of the fusion architecture for the enhanced sensor suite planned for the CP-140 aircraft in the context of the mission requirements and environmental conditions.

  6. Highway travel time estimation with data fusion

    CERN Document Server

    Soriguera Martí, Francesc

    2016-01-01

    This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-toll highways with the existing surveillance equipment, suggesting that highway operators might provide...

  7. Distributed video data fusion and mining

    Science.gov (United States)

    Chang, Edward Y.; Wang, Yuan-Fang; Rodoplu, Volkan

    2004-09-01

    This paper presents an event sensing paradigm for intelligent event-analysis in a wireless, ad hoc, multi-camera, video surveillance system. In particilar, we present statistical methods that we have developed to support three aspects of event sensing: 1) energy-efficient, resource-conserving, and robust sensor data fusion and analysis, 2) intelligent event modeling and recognition, and 3) rapid deployment, dynamic configuration, and continuous operation of the camera networks. We outline our preliminary results, and discuss future directions that research might take.

  8. Data Mining and Data Fusion for Enhanced Decision Support

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona

    2008-01-01

    The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

  9. Failure rate data for fusion safety and risk assessment

    International Nuclear Information System (INIS)

    Cadwallader, L.C.

    1993-01-01

    The Fusion Safety Program (FSP) at the Idaho National Engineering Laboratory (INEL) conducts safety research in materials, chemical reactions, safety analysis, risk assessment, and in component research and development to support existing magnetic fusion experiments and also to promote safety in the design of future experiments. One of the areas of safety research is applying probabilistic risk assessment (PRA) methods to fusion experiments. To apply PRA, we need a fusion-relevant radiological dose code and a component failure rate data base. This paper describes the FSP effort to develop a failure rate data base for fusion-specific components

  10. Data acquisition systems for fusion devices

    International Nuclear Information System (INIS)

    Van Haren, P.C.; Oomens, N.A.

    1993-01-01

    During the last two decades, computerized data acquisition systems (DASs) have been applied at magnetic confinement fusion devices. Present-day data acquisition is done by means of distributed computer systems and transient recorders in CAMAC systems. The development of DASs has been technology driven; the emphasis has been on the development of computer hardware and system software. For future DASs, challenging problems are to be solved: The DASs have to be better optimized with respect to the needs of the users. Existing bottlenecks, such as CAMAC-computer coupling or pulse file merging, need to be eliminated. Continuous or long-pulse operation will require the introduction of event abstraction in DAS design. 59 refs., 4 figs., 1 tab

  11. Data fusion and sensor management for nuclear power plant safety

    Energy Technology Data Exchange (ETDEWEB)

    Ciftcioglu, O [Istanbul Technical Univ., Istanbul (Turkey). Nuclear Power Dept.; Turkcan, E [Netherlands Energy Research Foundation (ECN), Petten (Netherlands)

    1997-12-31

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. The organization of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 fits, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. 12 refs, 6 figs.

  12. Data fusion and sensor management for nuclear power plant safety

    International Nuclear Information System (INIS)

    Ciftcioglu, O.

    1996-01-01

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. The organization of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 fits, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. 12 refs, 6 figs

  13. Modeling Cyber Situational Awareness Through Data Fusion

    Science.gov (United States)

    2013-03-01

    following table: Table 3.10: Example Vulnerable Hosts for Criticality Assessment Experiment Example Id OS Applications/Services Version 1 Mac OS X VLC ...linux.org/. [4] Blasch, E., I. Kadar, J. Salerno, M. Kokar, S. Das, G. Powell, D. Corkill, and E. Ruspini. “Issues and challenges of knowledge representation...Holsopple. “Issues and challenges in higher level fusion: Threat/impact assessment and intent modeling (a panel summary)”. Information Fusion (FUSION

  14. Data triggered data processing at the Mirror Fusion Test Facility

    International Nuclear Information System (INIS)

    Jackson, R.J.; Balch, T.R.; Preckshot, G.G.

    1986-01-01

    A primary characteristic of most batch systems is that the input data files must exist before jobs are scheduled. On the Mirror Fusion Test Facility (MFTF-B) at Lawrence Livermore National Laboratory the authors schedule jobs to process experimental data to be collected during a five minute shot cycle. The data driven processing system emulates a coarsely granular data flow architecture. Processing jobs are scheduled before the experimental data is collected. Processing jobs ''fire'', or execute, as input data becomes available. Similar to UNIX ''pipes'', data produced by upstream processing nodes may be used as inputs by following nodes. Users, working on the networked SUN workstations, specify data processing templates which define processes and their data dependencies. Data specifications indicate the source of data; actual associations with specific data instantiations are made when the jobs are scheduled. The authors report here on details of diagnostic data processing and their experiences

  15. Data fusion using dynamic associative memory

    Science.gov (United States)

    Lo, Titus K. Y.; Leung, Henry; Chan, Keith C. C.

    1997-07-01

    An associative memory, unlike an addressed memory used in conventional computers, is content addressable. That is, storing and retrieving information are not based on the location of the memory cell but on the content of the information. There are a number of approaches to implement an associative memory, one of which is to use a neural dynamical system where objects being memorized or recognized correspond to its basic attractors. The work presented in this paper is the investigation of applying a particular type of neural dynamical associative memory, namely the projection network, to pattern recognition and data fusion. Three types of attractors, which are fixed-point, limit- cycle, and chaotic, have been studied, evaluated and compared.

  16. Use of data fusion to optimize contaminant transport predictions

    International Nuclear Information System (INIS)

    Eeckhout, E. van

    1997-10-01

    The original data fusion workstation, as envisioned by Coleman Research Corp., was constructed under funding from DOE (EM-50) in the early 1990s. The intent was to demonstrate the viability of fusion and analysis of data from various types of sensors for waste site characterization, but primarily geophysical. This overall concept changed over time and evolved more towards hydrogeological (groundwater) data fusion after some initial geophysical fusion work focused at Coleman. This initial geophysical fusion platform was tested at Hanford and Fernald, and the later hydrogeological fusion work has been demonstrated at Pantex, Savannah River, the US Army Letterkenny Depot, a DoD Massachusetts site and a DoD California site. The hydrogeologic data fusion package has been spun off to a company named Fusion and Control Technology, Inc. This package is called the Hydrological Fusion And Control Tool (Hydro-FACT) and is being sold as a product that links with the software package, MS-VMS (MODFLOW-SURFACT Visual Modeling System), sold by HydroGeoLogic, Inc. MODFLOW is a USGS development, and is in the public domain. Since the government paid for the data fusion development at Coleman, the government and their contractors have access to the data fusion technology in this hydrogeologic package for certain computer platforms, but would probably have to hire FACT (Fusion and Control Technology, Inc.,) and/or HydroGeoLogic for some level of software and services. Further discussion in this report will concentrate on the hydrogeologic fusion module that is being sold as Hydro-FACT, which can be linked with MS-VMS

  17. PERSON AUTHENTICATION USING MULTIPLE SENSOR DATA FUSION

    Directory of Open Access Journals (Sweden)

    S. Vasuhi

    2011-04-01

    Full Text Available This paper proposes a real-time system for face authentication, obtained through fusion of Infra Red (IR and visible images. In order to identify the unknown person authentication in highly secured areas, multiple algorithms are needed. The four well known algorithms for face recognition, Block Independent Component Analysis(BICA, Kalman Filtering(KF method, Discrete Cosine Transform(DCT and Orthogonal Locality Preserving Projections (OLPP are used to extract the features. If the data base size is very large and the features are not distinct then ambiguity will exists in face recognition. Hence more than one sensor is needed for critical and/or highly secured areas. This paper deals with multiple fusion methodology using weighted average and Fuzzy Logic. The visible sensor output depends on the environmental condition namely lighting conditions, illumination etc., to overcome this problem use histogram technique to choose appropriate algorithm. DCT and Kalman filtering are holistic approaches, BICA follows feature based approach and OLPP preserves the Euclidean structure of face space. These recognizers are capable of considering the problem of dimensionality reduction by eliminating redundant features and reducing the feature space. The system can handle variations like illumination, pose, orientation, occlusion, etc. up to a significant level. The integrated system overcomes the drawbacks of individual recognizers. The proposed system is aimed at increasing the accuracy of the person authentication system and at the same time reducing the limitations of individual algorithms. It is tested on real time database and the results are found to be 96% accurate.

  18. Decentralized data fusion with inverse covariance intersection

    NARCIS (Netherlands)

    Noack, B.; Sijs, J.; Reinhardt, M.; Hanebeck, U.D.

    2017-01-01

    In distributed and decentralized state estimation systems, fusion methods are employed to systematically combine multiple estimates of the state into a single, more accurate estimate. An often encountered problem in the fusion process relates to unknown common information that is shared by the

  19. Data fusion according to the principle of polyrepresentation

    DEFF Research Database (Denmark)

    Larsen, Birger; Ingwersen, Peter; Lund, Berit

    2009-01-01

    logical data fusion combinations compared to the performance of the four individual models and their intermediate fusions when following the principle of polyrepresentation. This principle is based on cognitive IR perspective (Ingwersen & Järvelin, 2005) and implies that each retrieval model is regarded...... that only the inner disjoint overlap documents between fused models are ranked. The second set of experiments was based on traditional data fusion methods. The experiments involved the 30 TREC 5 topics that contain more than 44 relevant documents. In all tests, the Borda and CombSUM scoring methods were...... the individual models at DCV100. At DCV15, however, the results of polyrepresentative fusion were less predictable.The traditional fusion method based on polyrepresentation principles demonstrates a clear picture of performance at both DCV levels and verifies the polyrepresentation predictions for data fusion...

  20. Collection of experimental data for fusion neutronics benchmark

    International Nuclear Information System (INIS)

    Maekawa, Fujio; Yamamoto, Junji; Ichihara, Chihiro; Ueki, Kotaro; Ikeda, Yujiro.

    1994-02-01

    During the recent ten years or more, many benchmark experiments for fusion neutronics have been carried out at two principal D-T neutron sources, FNS at JAERI and OKTAVIAN at Osaka University, and precious experimental data have been accumulated. Under an activity of Fusion Reactor Physics Subcommittee of Reactor Physics Committee, these experimental data are compiled in this report. (author)

  1. Advances in multi-sensor data fusion: algorithms and applications.

    Science.gov (United States)

    Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

    2009-01-01

    With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

  2. Research on Kalman-filter based multisensor data fusion

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc.Various multisensor data fusion methods have been extensively investigated by researchers,of which Klaman filtering is one of the most important.Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown.states of a dynamic system,which has found widespread application in many areas.The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods.then a new method of state fusion is proposed.Finally the simulation results demonstrate the effectiveness of the introduced method.

  3. Graphs of neutron cross section data for fusion reactor development

    International Nuclear Information System (INIS)

    Asami, Tetsuo; Tanaka, Shigeya

    1979-03-01

    Graphs of neutron cross section data relevant to fusion reactor development are presented. Nuclides and reaction types in the present compilation are based on a WRENDA request list from Japan for fusion reactor development. The compilation contains various partial cross sections for 55 nuclides from 6 Li to 237 Np in the energy range up to 20 MeV. (author)

  4. Nuclear data for fusion technology – the European approach

    Directory of Open Access Journals (Sweden)

    Fischer Ulrich

    2017-01-01

    Full Text Available The European approach for the development of nuclear data for fusion technology applications is presented. Related R&D activities are conducted by the Consortium on Nuclear Data Development and Analysis for Fusion to satisfy the nuclear data needs of the major projects including ITER, the Early Neutron Source (ENS and DEMO. Recent achievements are presented in the area of nuclear data evaluations, benchmarking and validation, nuclear model improvements, and uncertainty assessments.

  5. Gene Fusion Markup Language: a prototype for exchanging gene fusion data.

    Science.gov (United States)

    Kalyana-Sundaram, Shanker; Shanmugam, Achiraman; Chinnaiyan, Arul M

    2012-10-16

    An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/. The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses.

  6. Tracking and sensor data fusion methodological framework and selected applications

    CERN Document Server

    Koch, Wolfgang

    2013-01-01

    Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing th

  7. Nuclear data for structural materials of fission and fusion reactors

    International Nuclear Information System (INIS)

    Goulo, V.

    1989-06-01

    The document presents the status of nuclear reaction theory concerning optical model development, level density models and pre-equilibrium and direct processes used in calculation of neutron nuclear data for structural materials of fission and fusion reactors. 6 refs

  8. Fusion of Inertial Navigation and Imagery Data, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The innovations of the Fusion of Inertial Navigation and Imagery Data are the application of the concept to the dynamic entry-interface through near-landing phases,...

  9. Cluster-based centralized data fusion for tracking maneuvering ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    In this scheme, measurements are sent to the data fusion centre where the mea- ... using 'clusters' (a cluster by definition is a type of parallel or distributed processing ... working together as a single, integrated computing resource) is proposed.

  10. Data fusion and sensor management for nuclear power plant safety

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-05-01

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. By means of accident management the appropriate prompt actions to be taken to avoid nuclear accident (SA) scenarios subjected to study. By means of accident management the appropriate prompt actions to be taken to avoid nuclear accidents are meant, while such accidents are deemed to somehow be imminent during plant operation. The organisation of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 first, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by the examples of deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. (orig./WL)

  11. Revised graphs of activation data for fusion reactor applications

    International Nuclear Information System (INIS)

    Seki, Yasushi; Kawasaki, Hiromitsu; Yamamuro, Nobuhiro; Iijima, Shungo.

    1991-06-01

    Activation data are required for calculation of induced activity in a fusion reactor. This report gives in graphical form, the activation data which have been evaluated based on recent measurements and calculations, for use in the activation calculation code system THIDA-2. It shows transmutation and decay chain data, activation cross sections and decay gamma-ray emission data for 152 nuclides of interest in terms of fusion reactor design. This report is an updated and enlarged version of a similar report compiled in 1982 for the activation data of 116 nuclides, which had been shown to be extremely effective in referring the activation data and in locating and correcting inappropriate data. (author)

  12. Remote Sensing Data Visualization, Fusion and Analysis via Giovanni

    Science.gov (United States)

    Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.

    2007-01-01

    We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.

  13. Fusion of imaging and nonimaging data for surveillance aircraft

    Science.gov (United States)

    Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

    1997-06-01

    This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).

  14. Nuclear Power Plants Fault Diagnosis Method Based on Data Fusion

    International Nuclear Information System (INIS)

    Xie Chunli; Liu Yongkuo; Xia Hong

    2009-01-01

    The data fusion is a method suit for complex system fault diagnosis such as nuclear power plants, which is multisource information processing technology. This paper uses data fusion information hierarchical thinking and divides nuclear power plants fault diagnosis into three levels. Data level adopts data mining method to handle data and reduction attributes. Feature level uses three parallel neural networks to deal with attributes of data level reduction and the outputs of three networks are as the basic probability assignment of Dempster-Shafer (D-S) evidence theory. The improved D-S evidence theory synthesizes the outputs of neural networks in decision level, which conquer the traditional D-S evidence theory limitation which can't dispose conflict information. The diagnosis method was tested using correlation data of literature. The test results indicate that the data fusion diagnosis system can diagnose nuclear power plants faults accurately and the method has application value. (authors)

  15. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  16. LLNL nuclear data libraries used for fusion calculations

    International Nuclear Information System (INIS)

    Howerton, R.J.

    1984-01-01

    The Physical Data Group of the Computational Physics Division of the Lawrence Livermore National Laboratory has as its principal responsibility the development and maintenance of those data that are related to nuclear reaction processes and are needed for Laboratory programs. Among these are the Magnetic Fusion Energy and the Inertial Confinement Fusion programs. To this end, we have developed and maintain a collection of data files or libraries. These include: files of experimental data of neutron induced reactions; an annotated bibliography of literature related to charged particle induced reactions with light nuclei; and four main libraries of evaluated data. We also maintain files of calculational constants developed from the evaluated libraries for use by Laboratory computer codes. The data used for fusion calculations are usually these calculational constants, but since they are derived by prescribed manipulation of evaluated data this discussion will describe the evaluated libraries

  17. Coordinated activities on evaluation of collisional data for fusion applications

    International Nuclear Information System (INIS)

    Chung, H.-K.; Braams, B. J.

    2013-01-01

    It is the role of the Atomic and Molecular Data Unit of the International Atomic Energy Agency to review progress in the production, compilation and evaluation of atomic, molecular and plasma-surface interaction (AM/PSI) data for the fusion program and to support the development of internationally recommended libraries of AM/PSI data for fusion. In response to increasing requests from the fusion community the Unit has increased its effort to promote the assessment of data quality by organizing a series of meetings on the relevant issues: 1) Error propagation and sensitivity analysis, 2) Current status of evaluated databases, 3) Uncertainty estimates of theoretical data, 4) Experimental data evaluation, 5) Data evaluation methods and semi-empirical fits and 6) Establishment of an evaluators’ network. The discussions and conclusions are summarized here

  18. Fusion of mass spectrometry-based metabolomics data

    NARCIS (Netherlands)

    Smilde, Age K.; van der Werf, Mariët J.; Bijlsma, Sabina; van der Werff-van der Vat, Bianca J. C.; Jellema, Renger H.

    2005-01-01

    A general method is presented for combining mass spectrometry-based metabolomics data. Such data are becoming more and more abundant, and proper tools for fusing these types of data sets are needed. Fusion of metabolomics data leads to a comprehensive view on the metabolome of an organism or

  19. Data fusion in metabolomics using coupled matrix and tensor factorizations

    DEFF Research Database (Denmark)

    Evrim, Acar Ataman; Bro, Rasmus; Smilde, Age Klaas

    2015-01-01

    of heterogeneous (i.e., in the form of higher order tensors and matrices) data sets with shared/unshared factors. In order to jointly analyze such heterogeneous data sets, we formulate data fusion as a coupled matrix and tensor factorization (CMTF) problem, which has already proved useful in many data mining...

  20. Propagation of nuclear data uncertainties for fusion power measurements

    Directory of Open Access Journals (Sweden)

    Sjöstrand Henrik

    2017-01-01

    Full Text Available Neutron measurements using neutron activation systems are an essential part of the diagnostic system at large fusion machines such as JET and ITER. Nuclear data is used to infer the neutron yield. Consequently, high-quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are not fully taken into account in uncertainty analysis for neutron yield calibrations using activation foils. This paper investigates the neutron yield uncertainty due to nuclear data using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of the JET fusion machine; the uncertainties due to the cross-sections and angular distributions in JET structural materials, as well as the activation cross-sections in the activation foils, are analysed. It is found that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.

  1. International bulletin on atomic and molecular data for fusion

    International Nuclear Information System (INIS)

    Stephens, J.A.; Bannister, M.E.; Fuhr, J.

    1999-12-01

    The International Bulletin on Atomic and Molecular Data for Fusion is prepared by the Atomic and Molecular Data Unit of the International Atomic Energy Agency. It is distributed free of charge by the IAEA to assist in the development of fusion research and technology. In part 1, the Atomic and Molecular Data Information System (AMDIS) is presented. In Part 2, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part 3 contains all the bibliographic data for both the indexed and non-indexed references. Finally, the Author Index (part 4) refers to the bibliographic references contained in part 3

  2. Browsing the fusion data in a Google map way

    International Nuclear Information System (INIS)

    Song, Xianming; Pan, W.; Chen, L.; Song, Xiao; Pan, L.; Luo, C.; Zhang, G.

    2015-01-01

    Full text of publication follows. How to access the ITER data is still an open issue. Concepts from KSTAR(1), W7X(2), EAST(3), and DIIID(4) have been presented. In this paper, a new web application to browse the fusion data in a Google map way is demonstrated on HL-2A database. This dynamic and interactive web application can run in any popular browser(IE, safari, Firefox, Opera), by any hardware (smart phone, PC, ipad, Mac) and operating system (ios, android, windows, linux, Mac OS). No any plug-ins is needed. The details of the framework for this web application are presented. The framework consists of three layers. The front top client layer is developed by Jquery code. The middle layer, which plays a role of a bridge to connect the server and client is developed by PHP code. The behind server layer is developed by Matlab, which responses any command from the front top client, retrieves the data from the HL-2A database, analyses and processes the data, and finally, returns the data to the client in client's favorite way. The way to browse and retrieve the fusion data is well welcomed by many researchers who access fusion data from many other machines. This way may apply to other machines, and present useful idea to the way for accessing ITER data in the future. References: 1) Kim, E.N., Web-based (HTML5) Interactive Graphics for Fusion Research and Collaboration, O4-2, 8. IAEA Technical Meeting on Control, Data Acquisition and Remote Participation for Fusion Research. June 20-24,2011, San Francisco, CA; 2)Davis, W.M., Easy Web Interfaces to IDL Code for NSTX Data Analysis Progress on Standardization and Automation in Software Development on W7X, P2-1. 8. IAEA Technical Meeting on Control, Data Acquisition and Remote Participation for Fusion Research. June 20-24,2011, San Francisco, CA; 3) Yang, F., A Web Based MDSPLUS Data Analysis and Visualization System for EAST, P2-16. 8th IAEA Technical Meeting on Control, Data Acquisition and Remote Participation for

  3. ADAS: Atomic data, modelling and analysis for fusion

    International Nuclear Information System (INIS)

    Summers, H. P.; O'Mullane, M. G.; Whiteford, A. D.; Badnell, N. R.; Loch, S. D.

    2007-01-01

    The Atomic Data and Analysis Structure, ADAS, comprises extensive fundamental and derived atomic data collections, interactive codes for the manipulation and generation of collisional-radiative data and models, off-line codes for large scale fundamental atomic data production and codes for diagnostic analysis in the fusion and astrophysical environments. ADAS data are organized according to precise specifications, tuned to application and are assigned to numbered ADAS data formats. Some of these formats contain very large quantities of data and some have achieved wide-scale adoption in the fusion community.The paper focuses on recent extensions of ADAS designed to orient ADAS to the needs of ITER. The issue of heavy atomic species, expected to be present as ITER wall and divertor materials, dopants or control species, will be addressed with a view to the economized handling of the emission and ionisation state data needed for diagnostic spectral analysis. Charge exchange and beam emission spectroscopic capabilities and developments in ADAS will be reviewed from an ITER perspective and in the context of a shared analysis between fusion laboratories. Finally an overview and summary of current large scale fundamental data production in the framework of the ADAS project will be given and its intended availability in both fusion and astrophysics noted

  4. Multisensor Data Fusion and Integration for Mobile Robots: A Review

    Directory of Open Access Journals (Sweden)

    KS Nagla

    2013-09-01

    Full Text Available One of the most important and useful feature of autonomous mobile robots is their ability to adopt themselves to operate in unstructured environment. Today robots are performing autonomously in industrial floor, office environments, as well as in crowded public places where the robots need to maintain their localization and mapping parameters.The basic requirement of an intelligent mobile robot is to develop and maintain localization and mapping parameters to complete the complex missions. In such situations, several difficulties arise in due to the inaccuracies and uncertainties in sensor measurements. Various techniques are there to handle such noises where the multisensor data fusion is not the exceptional one.From the last two decades, multisensor data fusions in mobile robots become a dominant paradigm  due to its potential advantages like reduction in uncertainty, increase in accuracy and reliability and reduction of cost.This paper presents the reviews of autonomous mobile robots and role of multisenosr data fusion.

  5. Danish heathland manipulation experiment data in Model-Data-Fusion

    Science.gov (United States)

    Thum, Tea; Peylin, Philippe; Ibrom, Andreas; Van Der Linden, Leon; Beier, Claus; Bacour, Cédric; Santaren, Diego; Ciais, Philippe

    2013-04-01

    In ecosystem manipulation experiments (EMEs) the ecosystem is artificially exposed to different environmental conditions that aim to simulate circumstances in future climate. At Danish EME site Brandbjerg the responses of a heathland to drought, warming and increased atmospheric CO2 concentration are studied. The warming manipulation is realized by passive nighttime warming. The measurements include control plots as well as replicates for each three treatment separately and in combination. The Brandbjerg heathland ecosystem is dominated by heather and wavy hairgrass. These experiments provide excellent data for validation and development of ecosystem models. In this work we used a generic vegetation model ORCHIDEE with Model-Data-Fusion (MDF) approach. ORCHIDEE model is a process-based model that describes the exchanges of carbon, water and energy between the atmosphere and the vegetation. It can be run at different spatial scales from global to site level. Different vegetation types are described in ORCHIDEE as plant functional types. In MDF we are using observations from the site to optimize the model parameters. This enables us to assess the modelling errors and the performance of the model for different manipulation treatments. This insight will inform us whether the different processes are adequately modelled or if the model is missing some important processes. We used a genetic algorithm in the MDF. The data available from the site included measurements of aboveground biomass, heterotrophic soil respiration and total ecosystem respiration from years 2006-2008. The biomass was measured six times doing this period. The respiration measurements were done with manual chamber measurements. For the soil respiration we used results from an empirical model that has been developed for the site. This enabled us to have more data for the MDF. Before the MDF we performed a sensitivity analysis of the model parameters to different data streams. Fifteen most influential

  6. Determination of Atomic Data Pertinent to the Fusion Energy Program

    International Nuclear Information System (INIS)

    Reader, J.

    2013-01-01

    We summarize progress that has been made on the determination of atomic data pertinent to the fusion energy program. Work is reported on the identification of spectral lines of impurity ions, spectroscopic data assessment and compilations, expansion and upgrade of the NIST atomic databases, collision and spectroscopy experiments with highly charged ions on EBIT, and atomic structure calculations and modeling of plasma spectra

  7. InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data.

    Directory of Open Access Journals (Sweden)

    Konstantin Okonechnikov

    Full Text Available Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.

  8. Materials data base for fusion reactors-I

    International Nuclear Information System (INIS)

    Iwata, S.; Nogami, A.; Ishino, S.; Mishima, Y.; Takao, Y.; Aruga, T.; Shiraishi, K.

    1982-01-01

    The materials data base is a set of experimental and/or calculated data being compiled to meet the broad needs for materials data by taking advantage of the data base management systems. In this paper the objective of such computerized data base is described and the characteristics of fusion reactor materials are discussed from the viewpoint of the data base development. The near-term emphasis of the development has been put on the irradiation data for 316 type stainless steels. Through the test of this small data base, it can be concluded that this approach is promising for materials data base management and for the establishment of the interface between fusion reactor designer and materials investigator. (orig.)

  9. Data fusion in cyber security: first order entity extraction from common cyber data

    Science.gov (United States)

    Giacobe, Nicklaus A.

    2012-06-01

    The Joint Directors of Labs Data Fusion Process Model (JDL Model) provides a framework for how to handle sensor data to develop higher levels of inference in a complex environment. Beginning from a call to leverage data fusion techniques in intrusion detection, there have been a number of advances in the use of data fusion algorithms in this subdomain of cyber security. While it is tempting to jump directly to situation-level or threat-level refinement (levels 2 and 3) for more exciting inferences, a proper fusion process starts with lower levels of fusion in order to provide a basis for the higher fusion levels. The process begins with first order entity extraction, or the identification of important entities represented in the sensor data stream. Current cyber security operational tools and their associated data are explored for potential exploitation, identifying the first order entities that exist in the data and the properties of these entities that are described by the data. Cyber events that are represented in the data stream are added to the first order entities as their properties. This work explores typical cyber security data and the inferences that can be made at the lower fusion levels (0 and 1) with simple metrics. Depending on the types of events that are expected by the analyst, these relatively simple metrics can provide insight on their own, or could be used in fusion algorithms as a basis for higher levels of inference.

  10. Freeway Multisensor Data Fusion Approach Integrating Data from Cellphone Probes and Fixed Sensors

    Directory of Open Access Journals (Sweden)

    Shanglu He

    2016-01-01

    Full Text Available Freeway traffic state information from multiple sources provides sufficient support to the traffic surveillance but also brings challenges. This paper made an investigation into the fusion of a new data combination from cellular handoff probe system and microwave sensors. And a fusion method based on the neural network technique was proposed. To identify the factors influencing the accuracy of fusion results, we analyzed the sensitivity of those factors by changing the inputs of neural-network-based fusion model. The results showed that handoff link length and sample size were identified as the most influential parameters to the precision of fusion. Then, the effectiveness and capability of proposed fusion method under various traffic conditions were evaluated. And a comparative analysis between the proposed method and other fusion approaches was conducted. The results of simulation test and evaluation showed that the fusion method could complement the drawback of each collection method, improve the overall estimation accuracy, adapt to the variable traffic condition (free flow or incident state, suit the fusion of data from cellphone probes and fixed sensors, and outperform other fusion methods.

  11. A Case for Data and Service Fusions

    Science.gov (United States)

    Huang, T.; Boening, C.; Quach, N. T.; Gill, K.; Zlotnicki, V.; Moore, B.; Tsontos, V. M.

    2015-12-01

    In this distributed, data-intensive era, developing any solution that requires multi-disciplinary data and service requires careful review of interfaces with data and service providers. Information is stored in many different locations and data services are distributed across the Internet. In design and development of mash-up heterogeneous data systems, the challenge is not entirely technological; it is our ability to document the external interface specifications and to create a coherent environment for our users. While is impressive to present a complex web of data, the true measure of our success is in the quality of the data we are serving, the throughput of our creation, and user experience. The presentation presents two current funded NASA projects that require integration of heterogeneous data and service that reside in different locations. The NASA Sea Level Change Portal is designed a "one-stop" source for current sea level change information. Behind this portal is an architecture that integrates data and services from various sources, which includes PI-generated products, satellite products from the DAACs, and metadata from ESDIS Common Metadata Repository (CMR) and other sources, and services reside in the data centers, universities, and ESDIS. The recently funded Distributed Oceanographic Matchup Service (DOMS) project is a project under the NASA Advance Information Technology (AIST) program. DOMS will integrate with satellite products managed by NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC) and three different in-situ projects that are located in difference parts of the U.S. These projects are good examples of delivering content-rich solutions through mash-up of heterogeneous data and systems.

  12. Fusion

    CERN Document Server

    Mahaffey, James A

    2012-01-01

    As energy problems of the world grow, work toward fusion power continues at a greater pace than ever before. The topic of fusion is one that is often met with the most recognition and interest in the nuclear power arena. Written in clear and jargon-free prose, Fusion explores the big bang of creation to the blackout death of worn-out stars. A brief history of fusion research, beginning with the first tentative theories in the early 20th century, is also discussed, as well as the race for fusion power. This brand-new, full-color resource examines the various programs currently being funded or p

  13. Radar image and data fusion for natural hazards characterisation

    Science.gov (United States)

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

    2010-01-01

    Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

  14. Cryogenic hydrogen data pertinent to magnetic fusion energy

    International Nuclear Information System (INIS)

    Souers, P.C.

    1979-01-01

    To aid future hydrogen fusion researchers, I have correlated the measured physical and chemical properties of the hydrogens below 30 0 K. I have further estimated these properties for deuterium--deuterium tritide--tritium (D 2 --DT--T 2 ) fusion fuel. My resulting synthesis offers a timely view and review of cryogenic hydrogen properties, plus some hydrogen data to room temperature. My general thrust is for workers new to the field, although my discussion of the scientific background of the material would suit specialists

  15. Sensor data fusion to predict multiple soil properties

    NARCIS (Netherlands)

    Mahmood, H.S.; Hoogmoed, W.B.; Henten, van E.J.

    2012-01-01

    The accuracy of a single sensor is often low because all proximal soil sensors respond to more than one soil property of interest. Sensor data fusion can potentially overcome this inability of a single sensor and can best extract useful and complementary information from multiple sensors or sources.

  16. Performance evaluation of multi-sensor data-fusion systems

    Indian Academy of Sciences (India)

    In this paper, the utilization of multi-sensors of different types, their characteristics, and their data-fusion in launch vehicles to achieve the goal of injecting the satellite into a precise orbit is explained. Performance requirements of sensors and their redundancy management in a typical launch vehicle are also included.

  17. Atomic data for controlled fusion research

    International Nuclear Information System (INIS)

    Barnett, C.F.; Ray, J.A.; Ricci, E.; Wilker, M.I.; McDaniel, E.W.; Thomas, E.W.; Gilbody, H.B.

    1977-02-01

    Presented is an evaluated graphical and tabular compilation of atomic and molecular cross sections of interest to controlled thermonuclear research. The cross sections are tabulated and graphed as a function of energy for collision processes involving heavy particles, electrons, and photons with atoms and ions. Also included are sections on data for particle penetration through macroscopic matter, particle transport properties, particle interactions with surfaces, and pertinent charged particle nuclear cross sections and reaction rates. In most cases estimates have been made of the data accuracy

  18. Multi sensor national cyber security data fusion

    CSIR Research Space (South Africa)

    Swart, I

    2015-03-01

    Full Text Available in a real world system. The data examined will then be applied to a case study that will show the results of applying available open source security information against the model to relate to the current South African cyber landscape....

  19. Data fusion approach to threat assessment for radar resources management

    Science.gov (United States)

    Komorniczak, Wojciech; Pietrasinski, Jerzy; Solaiman, Basel

    2002-03-01

    The paper deals with the problem of the multifunction radar resources management. The problem consists of target/tasks ranking and tasks scheduling. The paper is focused on the target ranking, with the data fusion approach. The data from the radar (object's velocity, range, altitude, direction etc.), IFF system (Identification Friend or Foe) and ESM system (Electronic Support Measures - information concerning threat's electro - magnetic activities) is used to decide of the importance assignment for each detected target. The main problem consists of the multiplicity of various types of the input information. The information from the radar is of the probabilistic or ambiguous imperfection type and the IFF information is of evidential type. To take the advantage of these information sources the advanced data fusion system is necessary. The system should deal with the following situations: fusion of the evidential and fuzzy information, fusion of the evidential information and a'priori information. The paper describes the system which fuses the fuzzy and the evidential information without previous change to the same type of information. It is also described the proposal of using of the dynamic fuzzy qualifiers. The paper shows the results of the preliminary system's tests.

  20. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks

    CERN Document Server

    Abdelgawad, Ahmed

    2012-01-01

    This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences.  These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative.   Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

  1. ENDF/B-VI nuclear data evaluations for fusion applications

    International Nuclear Information System (INIS)

    Dunford, C.L.; Larson, D.C.; Young, P.G.

    1988-01-01

    The next release of the ENDF/B data library planned for 1989 contains improved data evaluations of interest to the fusion neutronics community. New data formats permit inclusion of energy-angle correlated particle emission spectra and recoil nucleus energy spectra. Enhanced formats for covariance information have been developed. Many new isotopic evaluations will lead to improved energy conservation and kerma factor calculations. Improved nuclear model calculations will provide reliable particle emission data where experimental information is sparse. Improved Bayssian fitting codes will provide more accurate evaluations for data rich reactions such as Li(n,nt)α. All of the most important fusion material evaluations contain these new features. 32 refs., 8 figs

  2. Information management data base for fusion target fabrication processes

    International Nuclear Information System (INIS)

    Reynolds, J.

    1983-01-01

    A computer-based data management system has been developed to handle data associated with target fabrication processes including glass microballoon characterization, gas filling, materials coating, and storage locations. The system provides automatic data storage and computation, flexible data entry procedures, fast access, automated report generation, and secure data transfer. It resides on a CDC CYBER 175 computer and is compatible with the CDC data base language Query Update, but is based on custom fortran software interacting directly with the CYBER's file management system. The described data base maintains detailed, accurate, and readily available records of fusion targets information

  3. Data Fusion for Earth Science Remote Sensing

    Science.gov (United States)

    Braverman, Amy

    2007-01-01

    Beginning in 2004, NASA has supported the development of an international network of ground-based remote sensing installations for the measurement of greenhouse gas columns. This collaboration has been successful and is currently used in both carbon cycle investigations and in the efforts to validate the GOSAT space-based column observations of CO2 and CH4. With the support of a grant, this research group has established a network of ground-based column observations that provide an essential link between the satellite observations of CO2, CO, and CH4 and the extensive global in situ surface network. The Total Carbon Column Observing Network (TCCON) was established in 2004. At the time of this report seven sites, employing modern instrumentation, were operational or were expected to be shortly. TCCON is expected to expand. In addition to providing the most direct means of tying the in situ and remote sensing data sets together, TCCON provides a means of testing the retrieval algorithms of SCIAMACHY and GOSAT over the broadest variation in atmospheric state. TCCON provides a critically maintained and long timescale record for identification of temporal drift and spatial bias in the calibration of the space-based sensors. Finally, the global observations from TCCON are improving our understanding of how to use column observations to provide robust estimates of surface exchange of C02 and CH4 in advance of the launch of OCO and GOSAT. TCCON data are being used to better understand the impact of both regional fluxes and long-range transport on gradients in the C02 column. Such knowledge is essential for identifying the tools required to best use the space-based observations. The technical approach and methodology of retrieving greenhouse gas columns from near-IR solar spectra, data quality and process control are described. Additionally, the impact of and relevance to NASA of TCCON and satellite validation and carbon science are addressed.

  4. Concept of Operations for Data Fusion Visualization

    Energy Technology Data Exchange (ETDEWEB)

    T.R. McJunkin; R.L. Boring; M.A. McQueen; L.P. Shunn; J.L. Wright; D.I. Gertman; O. Linda; K. McCarty; M. Manic

    2011-09-01

    Situational awareness in the operations and supervision of a industrial system means that decision making entity, whether machine or human, have the important data presented in a timely manner. An optimal presentation of information such that the operator has the best opportunity accurately interpret and react to anomalies due to system degradation, failures or adversaries. Anticipated problems are a matter for system design; however, the paper will focus on concepts for situational awareness enhancement for a human operator when the unanticipated or unaddressed event types occur. Methodology for human machine interface development and refinement strategy is described for a synthetic fuels plant model. A novel concept for adaptively highlighting the most interesting information in the system and a plan for testing the methodology is described.

  5. Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

    Science.gov (United States)

    Volponi, Al

    2005-01-01

    Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.

  6. Multi-Modality Registration And Fusion Of Medical Image Data

    International Nuclear Information System (INIS)

    Kassak, P.; Vencko, D.; Cerovsky, I.

    2008-01-01

    Digitalisation of health care providing facilities allows US to maximize the usage of digital data from one patient obtained by various modalities. Complex view on to the problem can be achieved from the site of morphology as well as functionality. Multi-modal registration and fusion of medical image data is one of the examples that provides improved insight and allows more precise approach and treatment. (author)

  7. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  8. Data management in a fusion energy research experiment

    International Nuclear Information System (INIS)

    Glad, A.; Drobnis, D.; McHarg, B.

    1981-07-01

    Present-day fusion research requires extensive support for the large amount of scientific data generated, bringing about three distinct problems computer systems must solve: (1) the processing of large amounts of data in very small time frames; (2) the archiving, analyzing and managing of the entire data output for the project's lifetime; (3) the standardization of data for the exchange of information between laboratories. The computer system supporting General Atomic's Doublet III tokamak, a project funded by the United States Department of Energy, is the first to encounter and address these problems through a system-wide data base structure

  9. Disaster Monitoring using Grid Based Data Fusion Algorithms

    Directory of Open Access Journals (Sweden)

    Cătălin NAE

    2010-12-01

    Full Text Available This is a study of the application of Grid technology and high performance parallelcomputing to a candidate algorithm for jointly accomplishing data fusion from different sensors. Thisincludes applications for both image analysis and/or data processing for simultaneously trackingmultiple targets in real-time. The emphasis is on comparing the architectures of the serial andparallel algorithms, and characterizing the performance benefits achieved by the parallel algorithmwith both on-ground and in-space hardware implementations. The improved performance levelsachieved by the use of Grid technology (middleware for Parallel Data Fusion are presented for themain metrics of interest in near real-time applications, namely latency, total computation load, andtotal sustainable throughput. The objective of this analysis is, therefore, to demonstrate animplementation of multi-sensor data fusion and/or multi-target tracking functions within an integratedmulti-node portable HPC architecture based on emerging Grid technology. The key metrics to bedetermined in support of ongoing system analyses includes: required computational throughput inMFLOPS; latency between receipt of input data and resulting outputs; and scalability, processorutilization and memory requirements. Furthermore, the standard MPI functions are considered to beused for inter-node communications in order to promote code portability across multiple HPCcomputer platforms, both in space and on-ground.

  10. Data fusion analysis of a surface direct-current resistivity and well pick data set

    International Nuclear Information System (INIS)

    Clayton, E.A.; Lewis, R.E.

    1995-09-01

    Pacific Northwest Laboratory (PNL) has been tasked with testing, debugging, and refining the Hanford Site data fusion workstation (DFW), with the assistance of Coleman Research Corporation (CRC), before delivering the DFW to the environmental restoration client at the Hanford Site. Data fusion is the mathematical combination (or fusion) of disparate data sets into a single interpretation. The data fusion software used in this study was developed by CRC. This report discusses the results of evaluating a surface direct-current (dc) resistivity and well-pick data set using two methods: data fusion technology and commercially available software (i.e., RESIX Plus from Interpex Ltd., Golden, Colorado), the conventional method of analysis. The report compares the two technologies; describes the survey, procedures, and results; and includes conclusions and recommendations. The surface dc resistivity and well-pick data set had been acquired by PNL from a study performed in May 1993 at Eielson Air Force Base near Fairbanks, Alaska. The resistivity survey data were acquired to map the top of permafrost in support of a hydrogeologic study. This data set provided an excellent opportunity to test and refine the dc resistivity capabilities of the DFW; previously, the data fusion software was untested on dc resistivity data. The DFW was used to evaluate the dc resistivity survey data and to produce a 3-dimensional earth model of the study area

  11. The role of nuclear data for fusion technology studies

    International Nuclear Information System (INIS)

    Forrest, Robin A.

    2011-01-01

    Highlights: → Nuclear data are of fundamental importance in studies of nuclear technology. → Data libraries cover: experiments (EXFOR), theory (RIPL) and evaluations (ENDF). → Libraries are general purpose or special purpose (decay, dosimetry and activation). → Activation files contain many reactions, only a fraction needs to be known precisely. → Covariance data are important, but details of formatting are being worked out. - Abstract: Nuclear data are of fundamental importance in studies of nuclear technology. In these studies, experiments to measure cross sections and decay properties and simulations of the design of fission power plants, fusion devices and accelerators are included. The large amount of data required is stored in computer readable formats in data libraries and the most common of these are the general purpose files used for neutronics or transport calculations. These files also contain the standards against which most measurements are made. The other class of libraries are the special purpose ones containing decay data, fission yields and cross section data for dosimetry and activation. This paper gives examples of what data are available and describes their use for various fusion applications. The focus will be on neutron-induced activation data with examples of how the reactions of particular importance can be identified. All data should be accompanied by estimates of the uncertainty. This is best achieved by including covariance data; however, this is extremely challenging and only a subset of the available data has such uncertainty data. The general principles of how covariance matrices are used are outlined.

  12. Advances in data representation for hard/soft information fusion

    Science.gov (United States)

    Rimland, Jeffrey C.; Coughlin, Dan; Hall, David L.; Graham, Jacob L.

    2012-06-01

    Information fusion is becoming increasingly human-centric. While past systems typically relegated humans to the role of analyzing a finished fusion product, current systems are exploring the role of humans as integral elements in a modular and extensible distributed framework where many tasks can be accomplished by either human or machine performers. For example, "participatory sensing" campaigns give humans the role of "soft sensors" by uploading their direct observations or as "soft sensor platforms" by using mobile devices to record human-annotated, GPS-encoded high quality photographs, video, or audio. Additionally, the role of "human-in-the-loop", in which individuals or teams using advanced human computer interface (HCI) tools such as stereoscopic 3D visualization, haptic interfaces, or aural "sonification" interfaces can help to effectively engage the innate human capability to perform pattern matching, anomaly identification, and semantic-based contextual reasoning to interpret an evolving situation. The Pennsylvania State University is participating in a Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office to investigate fusion of hard and soft data in counterinsurgency (COIN) situations. In addition to the importance of this research for Intelligence Preparation of the Battlefield (IPB), many of the same challenges and techniques apply to health and medical informatics, crisis management, crowd-sourced "citizen science", and monitoring environmental concerns. One of the key challenges that we have encountered is the development of data formats, protocols, and methodologies to establish an information architecture and framework for the effective capture, representation, transmission, and storage of the vastly heterogeneous data and accompanying metadata -- including capabilities and characteristics of human observers, uncertainty of human observations, "soft" contextual data, and information pedigree

  13. Compilation of benchmark results for fusion related Nuclear Data

    International Nuclear Information System (INIS)

    Maekawa, Fujio; Wada, Masayuki; Oyama, Yukio; Ichihara, Chihiro; Makita, Yo; Takahashi, Akito

    1998-11-01

    This report compiles results of benchmark tests for validation of evaluated nuclear data to be used in nuclear designs of fusion reactors. Parts of results were obtained under activities of the Fusion Neutronics Integral Test Working Group organized by the members of both Japan Nuclear Data Committee and the Reactor Physics Committee. The following three benchmark experiments were employed used for the tests: (i) the leakage neutron spectrum measurement experiments from slab assemblies at the D-T neutron source at FNS/JAERI, (ii) in-situ neutron and gamma-ray measurement experiments (so-called clean benchmark experiments) also at FNS, and (iii) the pulsed sphere experiments for leakage neutron and gamma-ray spectra at the D-T neutron source facility of Osaka University, OKTAVIAN. Evaluated nuclear data tested were JENDL-3.2, JENDL Fusion File, FENDL/E-1.0 and newly selected data for FENDL/E-2.0. Comparisons of benchmark calculations with the experiments for twenty-one elements, i.e., Li, Be, C, N, O, F, Al, Si, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zr, Nb, Mo, W and Pb, are summarized. (author). 65 refs

  14. Parallel file system performances in fusion data storage

    International Nuclear Information System (INIS)

    Iannone, F.; Podda, S.; Bracco, G.; Manduchi, G.; Maslennikov, A.; Migliori, S.; Wolkersdorfer, K.

    2012-01-01

    High I/O flow rates, up to 10 GB/s, are required in large fusion Tokamak experiments like ITER where hundreds of nodes store simultaneously large amounts of data acquired during the plasma discharges. Typical network topologies such as linear arrays (systolic), rings, meshes (2-D arrays), tori (3-D arrays), trees, butterfly, hypercube in combination with high speed data transports like Infiniband or 10G-Ethernet, are the main areas in which the effort to overcome the so-called parallel I/O bottlenecks is most focused. The high I/O flow rates were modelled in an emulated testbed based on the parallel file systems such as Lustre and GPFS, commonly used in High Performance Computing. The test runs on High Performance Computing–For Fusion (8640 cores) and ENEA CRESCO (3392 cores) supercomputers. Message Passing Interface based applications were developed to emulate parallel I/O on Lustre and GPFS using data archival and access solutions like MDSPLUS and Universal Access Layer. These methods of data storage organization are widely diffused in nuclear fusion experiments and are being developed within the EFDA Integrated Tokamak Modelling – Task Force; the authors tried to evaluate their behaviour in a realistic emulation setup.

  15. Parallel file system performances in fusion data storage

    Energy Technology Data Exchange (ETDEWEB)

    Iannone, F., E-mail: francesco.iannone@enea.it [Associazione EURATOM-ENEA sulla Fusione, C.R.ENEA Frascati, via E.Fermi, 45 - 00044 Frascati, Rome (Italy); Podda, S.; Bracco, G. [ENEA Information Communication Tecnologies, Lungotevere Thaon di Revel, 76 - 00196 Rome (Italy); Manduchi, G. [Associazione EURATOM-ENEA sulla Fusione, Consorzio RFX, Corso Stati Uniti, 4 - 35127 Padua (Italy); Maslennikov, A. [CASPUR Inter-University Consortium for the Application of Super-Computing for Research, via dei Tizii, 6b - 00185 Rome (Italy); Migliori, S. [ENEA Information Communication Tecnologies, Lungotevere Thaon di Revel, 76 - 00196 Rome (Italy); Wolkersdorfer, K. [Juelich Supercomputing Centre-FZJ, D-52425 Juelich (Germany)

    2012-12-15

    High I/O flow rates, up to 10 GB/s, are required in large fusion Tokamak experiments like ITER where hundreds of nodes store simultaneously large amounts of data acquired during the plasma discharges. Typical network topologies such as linear arrays (systolic), rings, meshes (2-D arrays), tori (3-D arrays), trees, butterfly, hypercube in combination with high speed data transports like Infiniband or 10G-Ethernet, are the main areas in which the effort to overcome the so-called parallel I/O bottlenecks is most focused. The high I/O flow rates were modelled in an emulated testbed based on the parallel file systems such as Lustre and GPFS, commonly used in High Performance Computing. The test runs on High Performance Computing-For Fusion (8640 cores) and ENEA CRESCO (3392 cores) supercomputers. Message Passing Interface based applications were developed to emulate parallel I/O on Lustre and GPFS using data archival and access solutions like MDSPLUS and Universal Access Layer. These methods of data storage organization are widely diffused in nuclear fusion experiments and are being developed within the EFDA Integrated Tokamak Modelling - Task Force; the authors tried to evaluate their behaviour in a realistic emulation setup.

  16. a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

    Science.gov (United States)

    Hazaymeh, K.; Almagbile, A.

    2018-04-01

    In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

  17. An Online Multisensor Data Fusion Framework for Radar Emitter Classification

    Directory of Open Access Journals (Sweden)

    Dongqing Zhou

    2016-01-01

    Full Text Available Radar emitter classification is a special application of data clustering for classifying unknown radar emitters in airborne electronic support system. In this paper, a novel online multisensor data fusion framework is proposed for radar emitter classification under the background of network centric warfare. The framework is composed of local processing and multisensor fusion processing, from which the rough and precise classification results are obtained, respectively. What is more, the proposed algorithm does not need prior knowledge and training process; it can dynamically update the number of the clusters and the cluster centers when new pulses arrive. At last, the experimental results show that the proposed framework is an efficacious way to solve radar emitter classification problem in networked warfare.

  18. Data fusion: a new concept in non-destructive testing

    International Nuclear Information System (INIS)

    Georgel, B.; Lavayssiere, B.

    1995-01-01

    Non-destructive testing of some components (made of austenitic steel, or of a complex shape for example) requires quite often the use of several methods such as X-ray, ultrasonics, Eddy Currents. Then, a skilled operator is able to perform the expertise of the specimen. The main goal of this paper is to show that 3D diagnosis may be improved in term of reliability and precision by fusion of several NDT techniques. A data fusion algorithm is more that trying to improve the visualisation or the rendering of NDT data sets. It consists for each volume element, in computing a new value representing the combined information and in formulating a diagnosis on this basis. To achieve such a goal, know-how in modeling of physical phenomena and in applied mathematics is crucial. (authors). 4 refs., 2 figs

  19. Importance of interpolation and coincidence errors in data fusion

    Science.gov (United States)

    Ceccherini, Simone; Carli, Bruno; Tirelli, Cecilia; Zoppetti, Nicola; Del Bianco, Samuele; Cortesi, Ugo; Kujanpää, Jukka; Dragani, Rossana

    2018-02-01

    The complete data fusion (CDF) method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.

  20. Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving.

    Science.gov (United States)

    Elfring, Jos; Appeldoorn, Rein; van den Dries, Sjoerd; Kwakkernaat, Maurice

    2016-10-11

    The number of perception sensors on automated vehicles increases due to the increasing number of advanced driver assistance system functions and their increasing complexity. Furthermore, fail-safe systems require redundancy, thereby increasing the number of sensors even further. A one-size-fits-all multisensor data fusion architecture is not realistic due to the enormous diversity in vehicles, sensors and applications. As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle's surroundings. The methodology is accompanied by a software architecture. This combination minimizes the effort required to update the multisensor data fusion system whenever sensors or applications are added or replaced. A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture.

  1. Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving

    Directory of Open Access Journals (Sweden)

    Jos Elfring

    2016-10-01

    Full Text Available The number of perception sensors on automated vehicles increases due to the increasing number of advanced driver assistance system functions and their increasing complexity. Furthermore, fail-safe systems require redundancy, thereby increasing the number of sensors even further. A one-size-fits-all multisensor data fusion architecture is not realistic due to the enormous diversity in vehicles, sensors and applications. As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle’s surroundings. The methodology is accompanied by a software architecture. This combination minimizes the effort required to update the multisensor data fusion system whenever sensors or applications are added or replaced. A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture.

  2. Optimal Transport for Data Fusion in Remote Sensing

    OpenAIRE

    Courty , Nicolas; Flamary , Rémi; Tuia , Devis; Corpetti , Thomas

    2016-01-01

    International audience; One of the main objective of data fusion is the integration of several acquisition of the same physical object, in order to build a new consistent representation that embeds all the information from the different modalities. In this paper, we propose the use of optimal transport theory as a powerful mean of establishing correspondences between the modalities. After reviewing important properties and computational aspects, we showcase its application to three remote sen...

  3. Assessment of nucleonic methods and data for fusion reactors

    International Nuclear Information System (INIS)

    Dudziak, D.J.

    1976-01-01

    An assessment is provided of nucleonic methods, codes, and data necessary for a sound experimental fusion power reactor (EPR) technology base. Gaps in the base are identified and specific development recommendations are made in three areas: computational tools, nuclear data, and integral experiments. The current status of the first two areas is found to be sufficiently inadequate that viable engineering design of an EPR is precluded at this time. However, a program to provide the necessary data and computational capability is judged to be a low-risk effort

  4. Earth Science Data Fusion with Event Building Approach

    Science.gov (United States)

    Lukashin, C.; Bartle, Ar.; Callaway, E.; Gyurjyan, V.; Mancilla, S.; Oyarzun, R.; Vakhnin, A.

    2015-01-01

    Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

  5. International bulletin on atomic and molecular data for fusion. No. 16

    International Nuclear Information System (INIS)

    Katsonis, K.

    1981-06-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. ''Data Request'' in the fusion field are also mentioned. The bulletin contains a list of references covering the years 1980 and 1981 for all the publications on controlled fusion and plasma physics

  6. Survey of atomic and molecular data needs for fusion

    International Nuclear Information System (INIS)

    Lorenz, A.; Phillips, J.; Schmidt, J.J.; Lemley, J.R.

    1976-01-01

    Atomic and molecular data needs in five areas of plasma research and fusion technology are considered: Injection Systems (plasma heating by neutral particle beam injection and particle cluster beam injection); Plasma-Surface Interaction (sputtering, absorption, adsorption, reflection, evaporation, surface electron emission, interactions of atomic hydrogen isotopes, synchrotron radiation); Plasma Impurities and Cooling (electron impact ionization and excitation, recombination processes, charge exchange, reflection of H from wall surfaces); Plasma Diagnostics (atomic structure and transition probabilities, X-ray wave-length shift for highly ionized metals, electron capture collisions with H + and D + , heavy-ion collision ionization probe, photon scattering, emission spectroscopy); Laser-fusion Compression (microexplosion physics, diagnostics, microtarget design, laser systems requirements, laser development, reactor design needs)

  7. Low-energy nuclear fusion data and their relation to magnetic and laser fusion

    International Nuclear Information System (INIS)

    Jarmie, N.

    1980-04-01

    The accuracy of the basic fusion data for the T(d,n) 4 He, 3 He(d,p) 4 He, T(t,2n) 4 He, D(d,n) 3 He, and D(d,p)T reactions was investigated in the 10- to 100-keV bombarding energy region, and the effects of inaccuracies on the design of fusion reactors were assessed. The data base for these reactions [particularly, the most critical T(d,n) 4 He reaction] rests on 25-year-old experiments the accuracy (often assumed to be +- 5%) of which has rarely been questioned: yet, in all except the d + d reactions, there are significant differences among data sets. The errors in the basic data sets may be considerably larger than previously expected, and the effect on design calculations should be significant. Much of the trouble apparently lies in the accuracy of the energy measurements, which are difficult at low energies. Systematic errors of up to 50% are possible in the reactivity values of the present T(d,n) 4 He data base. The errors in the reactivity will propagate proportionately into the errors in fusion probabilities in reactor calculations. 3 He(d,p) 4 He reaction cross sections could be in error by as much as 50% in the low-energy region. The D(d,n) 3 He and D(d,p)T cross sections appear to be well known and consistent. The T(t,2n) 4 He cross section is poorly known and may be subject to large systematic errors. Improved absolute measurements for all the reactions in the low bombarding energy region (10 to 100 keV) are needed, but until they are done, the data sets should be left as they are [except for T(t,2n) 4 He data, which could be lowered by about 50%]. The apparent uncertainties of these data sets should be kept in mind. 14 figures

  8. Remediation planning and risk assessment support through data fusion technology

    International Nuclear Information System (INIS)

    1996-01-01

    Coleman Research's Data Fusion Modeling (DFM) services gives one the ability to use large geophysical and hydrological data sets, which include direct and indirect measurements, to obtain a unified mathematical model of the geology and hydrology at one's site. Coleman Research (CRC) has adapted highly stable and efficient statistical inversion techniques, developed over the past 20 years, to provide a 3D site model with quantified uncertainty based on state-of-the-art modeling codes. This site model supports risk assessment and remediation planning with enhanced numerical accuracy for tradeoff studies of alternate remediation strategies. Further, DFM supports real time model updates during remediation and site investigation

  9. Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

    Science.gov (United States)

    Fan, Lei

    Hyperspectral imaging provides the capability of increased sensitivity and discrimination over traditional imaging methods by combining standard digital imaging with spectroscopic methods. For each individual pixel in a hyperspectral image (HSI), a continuous spectrum is sampled as the spectral reflectance/radiance signature to facilitate identification of ground cover and surface material. The abundant spectrum knowledge allows all available information from the data to be mined. The superior qualities within hyperspectral imaging allow wide applications such as mineral exploration, agriculture monitoring, and ecological surveillance, etc. The processing of massive high-dimensional HSI datasets is a challenge since many data processing techniques have a computational complexity that grows exponentially with the dimension. Besides, a HSI dataset may contain a limited number of degrees of freedom due to the high correlations between data points and among the spectra. On the other hand, merely taking advantage of the sampled spectrum of individual HSI data point may produce inaccurate results due to the mixed nature of raw HSI data, such as mixed pixels, optical interferences and etc. Fusion strategies are widely adopted in data processing to achieve better performance, especially in the field of classification and clustering. There are mainly three types of fusion strategies, namely low-level data fusion, intermediate-level feature fusion, and high-level decision fusion. Low-level data fusion combines multi-source data that is expected to be complementary or cooperative. Intermediate-level feature fusion aims at selection and combination of features to remove redundant information. Decision level fusion exploits a set of classifiers to provide more accurate results. The fusion strategies have wide applications including HSI data processing. With the fast development of multiple remote sensing modalities, e.g. Very High Resolution (VHR) optical sensors, LiDAR, etc

  10. FENDL: International reference nuclear data library for fusion applications

    International Nuclear Information System (INIS)

    Pashchenko, A.B.; Wienke, H.; Ganesan, S.

    1996-01-01

    The IAEA nuclear data section, in co-operation with several national nuclear data centres and research groups, has created the first version of an internationally available fusion evaluated nuclear data library (FENDL-1). The FENDL library has been selected to serve as a comprehensive source of processed and tested nuclear data tailored to the requirements of the engineering design activity (EDA) of the ITER project and other fusion-related development projects. The present version of FENDL consists of the following sublibraries covering the necessary nuclear input for all physics and engineering aspects of the material development, design, operation and safety of the ITER project in its current EDA phase: FENDL/A-1.1: neutron activation cross-sections, selected from different available sources, for 636 nuclides, FENDL/D-1.0: nuclear decay data for 2900 nuclides in ENDF-6 format, FENDL/DS-1.0: neutron activation data for dosimetry by foil activation, FENDL/C-1.0: data for the fusion reactions D(d,n), D(d,p), T(d,n), T(t,2n), He-3(d,p) extracted from ENDF/B-6 and processed, FENDL/E-1.0:data for coupled neutron-photon transport calculations, including a data library for neutron interaction and photon production for 63 elements or isotopes, selected from ENDF/B-6, JENDL-3, or BROND-2, and a photon-atom interaction data library for 34 elements. The benchmark validation of FENDL-1 as required by the customer, i.e. the ITER team, is considered to be a task of high priority in the coming months. The well tested and validated nuclear data libraries in processed form of the FENDL-2 are expected to be ready by mid 1996 for use by the ITER team in the final phase of ITER EDA after extensive benchmarking and integral validation studies in the 1995-1996 period. The FENDL data files can be electronically transferred to users from the IAEA nuclear data section online system through INTERNET. A grand total of 54 (sub)directories with 845 files with total size of about 2 million

  11. Exploration of the gene fusion landscape of glioblastoma using transcriptome sequencing and copy number data.

    Science.gov (United States)

    Shah, Nameeta; Lankerovich, Michael; Lee, Hwahyung; Yoon, Jae-Geun; Schroeder, Brett; Foltz, Greg

    2013-11-22

    RNA-seq has spurred important gene fusion discoveries in a number of different cancers, including lung, prostate, breast, brain, thyroid and bladder carcinomas. Gene fusion discovery can potentially lead to the development of novel treatments that target the underlying genetic abnormalities. In this study, we provide comprehensive view of gene fusion landscape in 185 glioblastoma multiforme patients from two independent cohorts. Fusions occur in approximately 30-50% of GBM patient samples. In the Ivy Center cohort of 24 patients, 33% of samples harbored fusions that were validated by qPCR and Sanger sequencing. We were able to identify high-confidence gene fusions from RNA-seq data in 53% of the samples in a TCGA cohort of 161 patients. We identified 13 cases (8%) with fusions retaining a tyrosine kinase domain in the TCGA cohort and one case in the Ivy Center cohort. Ours is the first study to describe recurrent fusions involving non-coding genes. Genomic locations 7p11 and 12q14-15 harbor majority of the fusions. Fusions on 7p11 are formed in focally amplified EGFR locus whereas 12q14-15 fusions are formed by complex genomic rearrangements. All the fusions detected in this study can be further visualized and analyzed using our website: http://ivygap.swedish.org/fusions. Our study highlights the prevalence of gene fusions as one of the major genomic abnormalities in GBM. The majority of the fusions are private fusions, and a minority of these recur with low frequency. A small subset of patients with fusions of receptor tyrosine kinases can benefit from existing FDA approved drugs and drugs available in various clinical trials. Due to the low frequency and rarity of clinically relevant fusions, RNA-seq of GBM patient samples will be a vital tool for the identification of patient-specific fusions that can drive personalized therapy.

  12. Statistical modeling for visualization evaluation through data fusion.

    Science.gov (United States)

    Chen, Xiaoyu; Jin, Ran

    2017-11-01

    There is a high demand of data visualization providing insights to users in various applications. However, a consistent, online visualization evaluation method to quantify mental workload or user preference is lacking, which leads to an inefficient visualization and user interface design process. Recently, the advancement of interactive and sensing technologies makes the electroencephalogram (EEG) signals, eye movements as well as visualization logs available in user-centered evaluation. This paper proposes a data fusion model and the application procedure for quantitative and online visualization evaluation. 15 participants joined the study based on three different visualization designs. The results provide a regularized regression model which can accurately predict the user's evaluation of task complexity, and indicate the significance of all three types of sensing data sets for visualization evaluation. This model can be widely applied to data visualization evaluation, and other user-centered designs evaluation and data analysis in human factors and ergonomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Atomic Data and Modelling for Fusion: the ADAS Project

    International Nuclear Information System (INIS)

    Summers, H. P.; O'Mullane, M. G.

    2011-01-01

    The paper is an update on the Atomic Data and Analysis Structure, ADAS, since ICAM-DATA06 and a forward look to its evolution in the next five years. ADAS is an international project supporting principally magnetic confinement fusion research. It has participant laboratories throughout the world, including ITER and all its partner countries. In parallel with ADAS, the ADAS-EU Project provides enhanced support for fusion research at Associated Laboratories and Universities in Europe and ITER. OPEN-ADAS, sponsored jointly by the ADAS Project and IAEA, is the mechanism for open access to principal ADAS atomic data classes and facilitating software for their use. EXTENDED-ADAS comprises a variety of special, integrated application software, beyond the purely atomic bounds of ADAS, tuned closely to specific diagnostic analyses and plasma models.The current scientific content and scope of these various ADAS and ADAS related activities are briefly reviewed. These span a number of themes including heavy element spectroscopy and models, charge exchange spectroscopy, beam emission spectroscopy and special features which provide a broad baseline of atomic modelling and support. Emphasis will be placed on 'lifting the fundamental data baseline'--a principal ADAS task for the next few years. This will include discussion of ADAS and ADAS-EU coordinated and shared activities and some of the methods being exploited.

  14. The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion.

    Science.gov (United States)

    Borkowski, Piotr

    2017-06-20

    It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship's current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships.

  15. The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion

    Directory of Open Access Journals (Sweden)

    Piotr Borkowski

    2017-06-01

    Full Text Available It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship’s current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships.

  16. Process models and model-data fusion in dendroecology

    Directory of Open Access Journals (Sweden)

    Joel eGuiot

    2014-08-01

    Full Text Available Dendrochronology (i.e. the study of annually dated tree-ring time series has proved to be a powerful technique to understand tree-growth. This paper intends to show the interest of using ecophysiological modeling not only to understand and predict tree-growth (dendroecology but also to reconstruct past climates (dendroclimatology. Process models have been used for several decades in dendroclimatology, but it is only recently that methods of model-data fusion have led to significant progress in modeling tree-growth as a function of climate and in reconstructing past climates. These model-data fusion (MDF methods, mainly based on the Bayesian paradigm, have been shown to be powerful for both model calibration and model inversion. After a rapid survey of tree-growth modeling, we illustrate MDF with examples based on series of Southern France Aleppo pines and Central France oaks. These examples show that if plants experienced CO2 fertilization, this would have a significant effect on tree-growth which in turn would bias the climate reconstructions. This bias could be extended to other environmental non-climatic factors directly or indirectly affecting annual ring formation and not taken into account in classical empirical models, which supports the use of more complex process-based models. Finally, we conclude by showing the interest of the data assimilation methods applied in climatology to produce climate re-analyses.

  17. Data Fusion for Network Intrusion Detection: A Review

    Directory of Open Access Journals (Sweden)

    Guoquan Li

    2018-01-01

    Full Text Available Rapid progress of networking technologies leads to an exponential growth in the number of unauthorized or malicious network actions. As a component of defense-in-depth, Network Intrusion Detection System (NIDS has been expected to detect malicious behaviors. Currently, NIDSs are implemented by various classification techniques, but these techniques are not advanced enough to accurately detect complex or synthetic attacks, especially in the situation of facing massive high-dimensional data. Besides, the inherent defects of NIDSs, namely, high false alarm rate and low detection rate, have not been effectively solved. In order to solve these problems, data fusion (DF has been applied into network intrusion detection and has achieved good results. However, the literature still lacks thorough analysis and evaluation on data fusion techniques in the field of intrusion detection. Therefore, it is necessary to conduct a comprehensive review on them. In this article, we focus on DF techniques for network intrusion detection and propose a specific definition to describe it. We review the recent advances of DF techniques and propose a series of criteria to compare their performance. Finally, based on the results of the literature review, a number of open issues and future research directions are proposed at the end of this work.

  18. Evaluation of commercial available fusion algorithms for Geoeye data

    Science.gov (United States)

    Vaiopoulos, Aristides D.; Nikolakopoulos, Konstantinos G.

    2013-10-01

    In this study ten commercial available fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, PCA, HCS (Hyperspherical Color Space) and Wavelet were used for the fusion of Geoeye panchromatic and multispectral data. The panchromatic data have a spatial resolution of 0.5m while the multispectral data have a spatial resolution of 2.0m. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q, entropy were examined and the results are presented. The broader area of Pendeli mountain near to the city of Athens Greece and more especially two sub areas with different characteristics were chosen for the comparison. The first sub area is located at the edge of the urban fabric and combines at the same time the characteristics of an urban and a rural area. The second sub area comprises a large open quarry and it is suitable to examine which fused product is more suitable for mine monitoring.

  19. Geophysical data fusion for subsurface imaging. Final report

    International Nuclear Information System (INIS)

    1995-10-01

    This report contains the results of a three year, three-phase project whose long-range goal has been to create a means for the more detailed and accurate definition of the near-surface (0--300 ft) geology beneath a site that had been subjected to environmental pollution. The two major areas of research and development have been: improved geophysical field data acquisition techniques; and analytical tools for providing the total integration (fusion) of all site data. The long-range goal of this project has been to mathematically, integrate the geophysical data that could be derived from multiple sensors with site geologic information and any other type of available site data, to provide a detailed characterization of thin clay layers and geological discontinuities at hazardous waste sites

  20. Geophysical data fusion for subsurface imaging. Final report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-10-01

    This report contains the results of a three year, three-phase project whose long-range goal has been to create a means for the more detailed and accurate definition of the near-surface (0--300 ft) geology beneath a site that had been subjected to environmental pollution. The two major areas of research and development have been: improved geophysical field data acquisition techniques; and analytical tools for providing the total integration (fusion) of all site data. The long-range goal of this project has been to mathematically, integrate the geophysical data that could be derived from multiple sensors with site geologic information and any other type of available site data, to provide a detailed characterization of thin clay layers and geological discontinuities at hazardous waste sites.

  1. Phase 1 report on sensor technology, data fusion and data interpretation for site characterization

    International Nuclear Information System (INIS)

    Beckerman, M.

    1991-10-01

    In this report we discuss sensor technology, data fusion and data interpretation approaches of possible maximal usefulness for subsurface imaging and characterization of land-fill waste sites. Two sensor technologies, terrain conductivity using electromagnetic induction and ground penetrating radar, are described and the literature on the subject is reviewed. We identify the maximum entropy stochastic method as one providing a rigorously justifiable framework for fusing the sensor data, briefly summarize work done by us in this area, and examine some of the outstanding issues with regard to data fusion and interpretation. 25 refs., 17 figs

  2. Statistical Assessment of Gene Fusion Detection Algorithms using RNASequencing Data

    NARCIS (Netherlands)

    Varadan, V.; Janevski, A.; Kamalakaran, S.; Banerjee, N.; Harris, L.; Dimitrova, D.

    2012-01-01

    The detection and quantification of fusion transcripts has both biological and clinical implications. RNA sequencing technology provides a means for unbiased and high resolution characterization of fusion transcript information in tissue samples. We evaluated two fusiondetection algorithms,

  3. Application of the JDL data fusion process model for cyber security

    Science.gov (United States)

    Giacobe, Nicklaus A.

    2010-04-01

    A number of cyber security technologies have proposed the use of data fusion to enhance the defensive capabilities of the network and aid in the development of situational awareness for the security analyst. While there have been advances in fusion technologies and the application of fusion in intrusion detection systems (IDSs), in particular, additional progress can be made by gaining a better understanding of a variety of data fusion processes and applying them to the cyber security application domain. This research explores the underlying processes identified in the Joint Directors of Laboratories (JDL) data fusion process model and further describes them in a cyber security context.

  4. Importance of interpolation and coincidence errors in data fusion

    Directory of Open Access Journals (Sweden)

    S. Ceccherini

    2018-02-01

    Full Text Available The complete data fusion (CDF method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.

  5. Maintenance Decision Based on Data Fusion of Aero Engines

    Directory of Open Access Journals (Sweden)

    Huawei Wang

    2013-01-01

    Full Text Available Maintenance has gained a great importance as a support function for ensuring aero engine reliability and availability. Cost-effectiveness and risk control are two basic criteria for accurate maintenance. Given that aero engines have much condition monitoring data, this paper presents a new condition-based maintenance decision system that employs data fusion for improving accuracy of reliability evaluation. Bayesian linear model has been applied, so that the performance degradation evaluation of aero engines could be realized. A reliability evaluation model has been presented based on gamma process, which achieves the accurate evaluation by information fusion. In reliability evaluation model, the shape parameter is estimated by the performance degradation evaluation result, and the scale parameter is estimated by failure, inspection, and repair information. What is more, with such reliability evaluation as input variables and by using particle swarm optimization (PSO, a stochastic optimization of maintenance decision for aircraft engines has been presented, in which the effectiveness and the accuracy are demonstrated by a numerical example.

  6. Intelligent methods for data retrieval in fusion databases

    International Nuclear Information System (INIS)

    Vega, J.

    2008-01-01

    The plasma behaviour is identified through the recognition of patterns inside signals. The search for patterns is usually a manual and tedious procedure in which signals need to be examined individually. A breakthrough in data retrieval for fusion databases is the development of intelligent methods to search for patterns. A pattern (in the broadest sense) could be a single segment of a waveform, a set of pixels within an image or even a heterogeneous set of features made up of waveforms, images and any kind of experimental data. Intelligent methods will allow searching for data according to technical, scientific and structural criteria instead of an identifiable time interval or pulse number. Such search algorithms should be intelligent enough to avoid passing over the entire database. Benefits of such access methods are discussed and several available techniques are reviewed. In addition, the applicability of the methods from general purpose searching systems to ad hoc developments is covered

  7. Mapping migratory bird prevalence using remote sensing data fusion.

    Science.gov (United States)

    Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

    2012-01-01

    Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

  8. Fusion of navigational data in River Information Services

    Science.gov (United States)

    Kazimierski, W.

    2009-04-01

    . Their main advantage over AIS is total independence from tracked target's facilities. For example, wrong indications of ship's GPS would affect AIS accuracy, but wouldn't have any impact on values estimated by radar. In addition to this in many times update rate for AIS data is longer than for radar. Thus, it can be noticed, that efficient tracking system introduced in RIS shall use both AIS receivers (based on satellite derived positions), and independent radar and camera sensors. This will however cause determining at least two different set of information about positions and movement parameters of targets. Doubled or multiplied vectors for single target are unacceptable, due to safety of navigation and traffic management. Hence the need of data fusion in RIS is obvious. The main goal is to develop unambiguous, clear and reliable information about ships' position and movement for all users in the system. Data fusion itself is not a new problem in maritime navigation. There are systems of Integrated Bridge on sea-going ships, which use information coming out from different sources. However the possibilities of integration of navigational information in the aspect of inland navigation, especially in River Information Services, still needs to be thoroughly surveyed. It is quite useful for simplifying the deduction, to introduce two data fusion levels. First of them is being done on board of the vessel. Its aim is to integrate all information coming from different sensors in the so called Integrated Navigational System. The other task of this fusion is to estimate reliable information about other objects based on AIS and radar. The second level is the integration of AIS, radar and closed-circuit television (CCTV) carried out in coastal station in order to determine Tactical and Strategic Traffic Image. The navigational information in RIS itself can be divided into two main groups. The first one is called static data and contains al basic information related to ship itself

  9. Multisensor multiresolution data fusion for improvement in classification

    Science.gov (United States)

    Rubeena, V.; Tiwari, K. C.

    2016-04-01

    The rapid advancements in technology have facilitated easy availability of multisensor and multiresolution remote sensing data. Multisensor, multiresolution data contain complementary information and fusion of such data may result in application dependent significant information which may otherwise remain trapped within. The present work aims at improving classification by fusing features of coarse resolution hyperspectral (1 m) LWIR and fine resolution (20 cm) RGB data. The classification map comprises of eight classes. The class names are Road, Trees, Red Roof, Grey Roof, Concrete Roof, Vegetation, bare Soil and Unclassified. The processing methodology for hyperspectral LWIR data comprises of dimensionality reduction, resampling of data by interpolation technique for registering the two images at same spatial resolution, extraction of the spatial features to improve classification accuracy. In the case of fine resolution RGB data, the vegetation index is computed for classifying the vegetation class and the morphological building index is calculated for buildings. In order to extract the textural features, occurrence and co-occurence statistics is considered and the features will be extracted from all the three bands of RGB data. After extracting the features, Support Vector Machine (SVMs) has been used for training and classification. To increase the classification accuracy, post processing steps like removal of any spurious noise such as salt and pepper noise is done which is followed by filtering process by majority voting within the objects for better object classification.

  10. Improving Agent Based Models and Validation through Data Fusion.

    Science.gov (United States)

    Laskowski, Marek; Demianyk, Bryan C P; Friesen, Marcia R; McLeod, Robert D; Mukhi, Shamir N

    2011-01-01

    This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

  11. Affordable non-traditional source data mining for context assessment to improve distributed fusion system robustness

    Science.gov (United States)

    Bowman, Christopher; Haith, Gary; Steinberg, Alan; Morefield, Charles; Morefield, Michael

    2013-05-01

    This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data Fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and `big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

  12. Comparison of pH Data Measured with a pH Sensor Array Using Different Data Fusion Methods

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liao

    2012-09-01

    Full Text Available This paper introduces different data fusion methods which are used for an electrochemical measurement using a sensor array. In this study, we used ruthenium dioxide sensing membrane pH electrodes to form a sensor array. The sensor array was used for detecting the pH values of grape wine, generic cola drink and bottled base water. The measured pH data were used for data fusion methods to increase the reliability of the measured results, and we also compared the fusion results with other different data fusion methods.

  13. A generative model for probabilistic label fusion of multimodal data

    DEFF Research Database (Denmark)

    Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Van Leemput, Koen

    2012-01-01

    The maturity of registration methods, in combination with the increasing processing power of computers, has made multi-atlas segmentation methods practical. The problem of merging the deformed label maps from the atlases is known as label fusion. Even though label fusion has been well studied for...

  14. Employing Data Fusion in Cultural Analysis and Counterinsurgency in Tribal Social Systems

    OpenAIRE

    Merten, Steffen

    2009-01-01

    This article was published in Culture and Conflict Review (Fall 2009), v.3 no.3 "The point of this essay has been to outline ways that data fusion may be achieved, and how it can dramatically enhance the analytical capabilities of cultural analysts, especially in tribal social systems. By using Visual Analytics theory and technology to conduct the labor intensive aspects of data fusion, and accepting the theoretical justification of fusion between the geospatial, relational, and temporal d...

  15. Optimized data fusion for K-means Laplacian clustering

    Science.gov (United States)

    Yu, Shi; Liu, Xinhai; Tranchevent, Léon-Charles; Glänzel, Wolfgang; Suykens, Johan A. K.; De Moor, Bart; Moreau, Yves

    2011-01-01

    Motivation: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically. Results: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix. Availability: The MATLAB code of algorithms implemented in this paper is downloadable from http://homes.esat.kuleuven.be/~sistawww/bioi/syu/oklc.html. Contact: shiyu@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20980271

  16. Thought Experiment to Examine Benchmark Performance for Fusion Nuclear Data

    Science.gov (United States)

    Murata, Isao; Ohta, Masayuki; Kusaka, Sachie; Sato, Fuminobu; Miyamaru, Hiroyuki

    2017-09-01

    There are many benchmark experiments carried out so far with DT neutrons especially aiming at fusion reactor development. These integral experiments seemed vaguely to validate the nuclear data below 14 MeV. However, no precise studies exist now. The author's group thus started to examine how well benchmark experiments with DT neutrons can play a benchmarking role for energies below 14 MeV. Recently, as a next phase, to generalize the above discussion, the energy range was expanded to the entire region. In this study, thought experiments with finer energy bins have thus been conducted to discuss how to generally estimate performance of benchmark experiments. As a result of thought experiments with a point detector, the sensitivity for a discrepancy appearing in the benchmark analysis is "equally" due not only to contribution directly conveyed to the deterctor, but also due to indirect contribution of neutrons (named (A)) making neutrons conveying the contribution, indirect controbution of neutrons (B) making the neutrons (A) and so on. From this concept, it would become clear from a sensitivity analysis in advance how well and which energy nuclear data could be benchmarked with a benchmark experiment.

  17. Thought Experiment to Examine Benchmark Performance for Fusion Nuclear Data

    Directory of Open Access Journals (Sweden)

    Murata Isao

    2017-01-01

    Full Text Available There are many benchmark experiments carried out so far with DT neutrons especially aiming at fusion reactor development. These integral experiments seemed vaguely to validate the nuclear data below 14 MeV. However, no precise studies exist now. The author’s group thus started to examine how well benchmark experiments with DT neutrons can play a benchmarking role for energies below 14 MeV. Recently, as a next phase, to generalize the above discussion, the energy range was expanded to the entire region. In this study, thought experiments with finer energy bins have thus been conducted to discuss how to generally estimate performance of benchmark experiments. As a result of thought experiments with a point detector, the sensitivity for a discrepancy appearing in the benchmark analysis is “equally” due not only to contribution directly conveyed to the deterctor, but also due to indirect contribution of neutrons (named (A making neutrons conveying the contribution, indirect controbution of neutrons (B making the neutrons (A and so on. From this concept, it would become clear from a sensitivity analysis in advance how well and which energy nuclear data could be benchmarked with a benchmark experiment.

  18. Possible in-lattice confinement fusion (LCF). Dynamic application of atomic and nuclear data

    International Nuclear Information System (INIS)

    Kawarasaki, Yuuki

    1995-01-01

    New scheme of a nuclear fusion reactor system is proposed, the basic concept of which comes from ingenious combination of hitherto developed techniques and verified facts; 1) so-called cold fusion (CF), 2) plasma of both magnetic confinement fusion (MCF) and inertial confinement fusion (ICF), and 3) accelerator-based D-T(D) neutron source. Details of the LCF reactor physics require dynamics of atomic data as well as nuclear data; interaction of ions with matters in solid and the problems of radiation damage. (author)

  19. Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm

    Directory of Open Access Journals (Sweden)

    Hongye Zhong

    2017-01-01

    Full Text Available With recent advances in health systems, the amount of health data is expanding rapidly in various formats. This data originates from many new sources including digital records, mobile devices, and wearable health devices. Big health data offers more opportunities for health data analysis and enhancement of health services via innovative approaches. The objective of this research is to develop a framework to enhance health prediction with the revised fusion node and deep learning paradigms. Fusion node is an information fusion model for constructing prediction systems. Deep learning involves the complex application of machine-learning algorithms, such as Bayesian fusions and neural network, for data extraction and logical inference. Deep learning, combined with information fusion paradigms, can be utilized to provide more comprehensive and reliable predictions from big health data. Based on the proposed framework, an experimental system is developed as an illustration for the framework implementation.

  20. International bulletin on atomic and molecular data for fusion. No. 14

    International Nuclear Information System (INIS)

    Katsonis, K.

    1980-11-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. The bulletin contains a list of references covering the year 1980 for all the publications on controlled fusion and plasma physics

  1. International bulletin on atomic and molecular data for fusion. No. 9

    International Nuclear Information System (INIS)

    Katsonis, K.; Rumble, J. Jr.; Smith, F.J.

    1979-07-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains a list of references covering the years 1978 and 1979 for all the publications on controlled fusion and plasma physics

  2. International bulletin on atomic and molecular data for fusion. No. 15

    International Nuclear Information System (INIS)

    Katsonis, K.

    1981-03-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains a list of references covering the years 1980 and 1981 for all the publications on controlled fusion and plasma physics

  3. International bulletin on atomic and molecular data for fusion. No. 7

    International Nuclear Information System (INIS)

    Katsonis, K.; Smith, F.J.

    1979-01-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains an extensive list of references covering the years 1977 and 1978 for all the publications on control fusion and plasma physics

  4. International bulletin on atomic and molecular data for fusion. No. 8

    International Nuclear Information System (INIS)

    Katsonis, K.; Smith, F.J.

    1979-04-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains an extensive list of references covering the year 1978 and the beginning of 1979 for all the publications on control fusion and plasma physics

  5. International bulletin on atomic and molecular data for fusion. No. 19

    International Nuclear Information System (INIS)

    Katsonis, K.

    1982-06-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains a list of references covering the years 1981 and 1982 for all the publications on controlled fusion and plasma physics

  6. International bulletin on atomic and molecular data for fusion. No. 20

    International Nuclear Information System (INIS)

    Katsonis, K.

    1982-09-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. The bulletin contains a list of references covering the year 1982 for all the publications on controlled thermonuclear fusion and plasma physics

  7. Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest

    NARCIS (Netherlands)

    Mou, L.; Zhu, X.; Vakalopoulou, M.; Karantzalos, K.; Paragios, N.; Saux, Le B.; Moser, G.; Tuia, D.

    2017-01-01

    In this paper, the scientific outcomes of the 2016 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society are discussed. The 2016 Contest was an open topic competition based on a multitemporal and multimodal dataset,

  8. Atomic and Molecular Data Activities for Fusion Research in JAEA

    International Nuclear Information System (INIS)

    Nakano, T.

    2011-01-01

    The Japan Atomic Energy Agency (JAEA) has been producing, collecting and compiling cross-section data for atomic and molecular collisions and spectral data relevant to fusion research. In this talk, an overview of our activities since the last meeting in September 2009 will be presented. The state selective charge transfer cross-section data of Be 4+ , C 4+ and C 6+ by collision with H(n=2) in the collision energy range between 62 eV/amu and 6.2 keV/amu have been calculated with a molecular-bases close-coupling method. The calculated charge transfer data of C 4+ was implemented in a collisional-radiative model code for C 3+ , and it is shown that in some cases the charge transfer from C 4+ to H(n=2) populates predominantly C 3+ (n = 6, 7). The cross-section data of dissociative recombination and excitation of HD + , D 2+ , DT + , T 2+ 3 HeH + and 4 HeH + were produced by theoretical calculation. The principal quantum number of dissociated H atom isotopes was also given. The analytical expressions for the cross-section data for 26 processes of He-collision systems were produced in order to facilitate practical use of the data. The compiled data are in preparation for the web site at the URL of http://www-jt60.naka.jaea.go.jp/engish/JEAMDL/. The chemical sputtering yield data of CFC materials with hydrogen isotope collisions have been compiled. The ionization rate of W 44+ and the radiative and the dielectronic recombination rates of W 45+ were calculated with FAC. The ratio of these rates was compared with experimentally measured ratio of W 45+ density to W 44+ density in JT-60U, showing that the calculated ratio of the recombination ratio of W 45+ to the ionization rate of W 44+ is accurate within the experimental uncertainty (∼ 30%). The atomic and molecular data activities in JAEA are pursued in collaboration with Japanese universities, and other department of JAEA. (author)

  9. Atomic and plasma-material interaction data for fusion. Vol.1

    International Nuclear Information System (INIS)

    1991-01-01

    The International Atomic Energy Agency, through its Atomic and Molecular Data Unit, coordinates a wide spectrum of programmes for the compilation, evaluation, and generation of atomic, molecular, and plasma-wall interaction data for fusion research. The present, first, volume of Atomic and Plasma-Material Interaction Data for Fusion, contains extended versions of the reviews presented at the IAEA Advisory Group Meeting on Particle-Surface Interaction Data for Fusion, held 19-21 April 1989 at the IAEA Headquarters in Vienna, The plasma-wall interaction processes covered here are those considered most important for the operational performance of magnetic confinement fusion reactors. In addition to processes due to particle impact under normal operation, plasma-wall interaction effects due to off-normal plasma events (disruptions, electron runaway bombardment) are covered, and a summary of the status of data information on these processes is given from the point of view of magnetic fusion reactor design. Refs, figs and tabs

  10. Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest

    NARCIS (Netherlands)

    Yokoya, Naoto; Ghamisi, Pedram; Xia, Junshi; Sukhanov, Sergey; Heremans, Roel; Tankoyeu, Ivan; Bechtel, Benjamin; Saux, Le Bertrand; Moser, Gabriele; Tuia, Devis

    2018-01-01

    In this paper, we present the scientific outcomes of the 2017 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2017 Contest was aimed at addressing the problem of local climate zones classification based on

  11. Data and image fusion for geometrical cloud characterization

    Energy Technology Data Exchange (ETDEWEB)

    Thorne, L.R.; Buch, K.A.; Sun, Chen-Hui; Diegert, C.

    1997-04-01

    Clouds have a strong influence on the Earth`s climate and therefore on climate change. An important step in improving the accuracy of models that predict global climate change, general circulation models, is improving the parameterization of clouds and cloud-radiation interactions. Improvements in the next generation models will likely include the effect of cloud geometry on the cloud-radiation parameterizations. We have developed and report here methods for characterizing the geometrical features and three-dimensional properties of clouds that could be of significant value in developing these new parameterizations. We developed and report here a means of generating and imaging synthetic clouds which we used to test our characterization algorithms; a method for using Taylor`s hypotheses to infer spatial averages from temporal averages of cloud properties; a computer method for automatically classifying cloud types in an image; and a method for producing numerical three-dimensional renderings of cloud fields based on the fusion of ground-based and satellite images together with meteorological data.

  12. Atomic and plasma-material interaction data for fusion. V. 2

    International Nuclear Information System (INIS)

    1992-01-01

    This issues of the Atomic and Plasma-Material Interaction Data for Fusion contains 9 papers on atomic and molecular processes in the edge region of magnetically confined fusion plasmas, including spectroscopic data for fusion edge plasmas; electron collision processes with plasma edge neutrals; electron-ion collisions in the plasma edge; cross-section data for collisions of electrons with hydrocarbon molecules; dissociative and energy transfer reactions involving vibrationally excited hydrogen or deuterium molecules; an assessment of ion-atom collision data for magnetic fusion plasma edge modeling; an extended scaling of cross sections for the ionization of atomic and molecular hydrogen as well as helium by multiply-charged ions; ion-molecule collision processes relevant to fusion edge plasmas; and radiative losses and electron cooling rates for carbon and oxygen plasma impurities. Refs, figs and tabs

  13. Atomic and plasma-material interaction data for fusion. V. 6

    International Nuclear Information System (INIS)

    1995-01-01

    Volume 6 of the supplement ''atomic and plasma-material interaction data for fusion'' to the journal ''Nuclear Fusion'' includes critical assessments and results of original experimental and theoretical studies on inelastic collision processes among the basic and dominant impurity constituents of fusion plasmas. Processes considered in the 15 papers constituting this volume are: electron impact excitation of excited Helium atoms, electron impact excitation and ionization of plasma impurity ions and atoms, electron-impurity-ion recombination and excitation, ionization and electron capture in collisions of plasma protons and impurity ions with the main fusion plasma neutral components helium and atomic and molecular hydrogen. Refs, figs, tabs

  14. A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

    Energy Technology Data Exchange (ETDEWEB)

    Kevin McCarthy; Milos Manic

    2012-08-01

    Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presents an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.

  15. Distributed data fusion across multiple hard and soft mobile sensor platforms

    Science.gov (United States)

    Sinsley, Gregory

    One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion

  16. A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion

    NARCIS (Netherlands)

    Gevaert, C.M.; Garcia-Haro, F.J.

    2015-01-01

    The focus of the current study is to compare data fusion methods applied to sensors with medium- and high-spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to

  17. International bulletin on atomic and molecular data for fusion. No. 22

    International Nuclear Information System (INIS)

    Katsonis, K.

    1983-05-01

    This bulletin deals with atomic and molecular data for fusion. Work in progress is briefly reported (charge exchange of slow ionized ions with neutral gases, cross section for electron impact ionization of Alt). The bulletin contains a list of references covering the years 1981, 1982 and 1983 for publications on controlled thermonuclear fusion and plasma physics

  18. Data fusion from multiple passive sonar nodes for target localisation and false alarm reduction

    NARCIS (Netherlands)

    Hunter, A.J.; Fillinger, L.; Zampolli, M.; Clarijs, M.C.

    2012-01-01

    A PHD particle filter implementation has been detailed for the fusion of measurements from multiple passive sonar nodes. It has been demonstrated on simulated metadata and on experimental passive acoustic data of divers and small boats collected in an operational port environment. Fusion at the

  19. 'Merge' - A Filter for the Fusion of Dual-Frequency Sidescan Sonar Data

    National Research Council Canada - National Science Library

    Neill, Roger

    1997-01-01

    A filtering and data fusion technique is described which uses the correlation between the two data streams of a dual-frequency sidescan sonar in order to discriminate against noise and preferentially...

  20. Raman/LIBS Data Fusion via Two-Way Variational Autoencoders

    Science.gov (United States)

    Parente, M.; Gemp, I.

    2018-04-01

    We propose an original solution to extracting mineral abundances from Raman spectra by combining Raman data with LIBS using a novel deep learning model based on variational autoencoders and data fusion, which outperforms the current state of the art.

  1. Assessment of the critical engineering data needs for the commercialization of magnetic confinement fusion

    International Nuclear Information System (INIS)

    Waganer, L.M.; Zuckerman, D.S.

    1983-01-01

    A survey of twenty-two recent conceptual fusion reactor designs was conducted to ascertain both generic and specific engineering data needs critical for the commercialization of magnetic confinement fusion (MCF). Design experts or advocates for each concept were queried as to the more critical engineering issues and data needs affecting the achievement of commercialization. For each concept, the technical issues were identified and the data needs quantified. Issues and data needs were then ranked based upon the experts' perceptions of the relative importance of each to the concept. The issues encompassed all aspects of the fusion reactor plant design including materials, performance, maintainability, operability, cost, safety and resources

  2. Protein fold recognition using geometric kernel data fusion.

    Science.gov (United States)

    Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

    2014-07-01

    Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

  3. Multimodality imaging: transfer and fusion of SPECT and MRI data

    International Nuclear Information System (INIS)

    Knesaurek, K.

    1994-01-01

    Image fusion is a technique which offers the best of both worlds. It unites the two basic types of medical images: functional body images(PET or SPECT scans), which provide physiological information, and structural images (CT or MRI), which provide an anatomic map of the body. Control-point based registration technique was developed and used. Tc-99m point sources were used as external markers in SPECT studies while, for MRI and CT imaging only anatomic landmarks were used as a control points. The MRI images were acquired on GE Signa 1.2 system and CT data on a GE 9800 scanner. SPECT studies were performed 1h after intravenous injection of the 740 MBq of the Tc-99m-HMPAO on the triple-headed TRIONIX gamma camera. B-spline and bilinear interpolation were used for the rotation, scaling and translation of the images. In the process of creation of a single composite image, in order to retain information from the individual images, MRI (or CT) image was scaled to one color range and a SPECT image to another. In some situations the MRI image was kept black-and-white while the SPECT image was pasted on top of it in 'opaque' mode. Most errors which propagate through the matching process are due to sample size, imperfection of the acquisition system, noise and interpolations used. Accuracy of the registration was investigated by SPECT-CT study performed on a phantom study. The results has shown that accuracy of the matching process is better, or at worse, equal to 2 mm. (author)

  4. Sensor data fusion of radar, ESM, IFF, and data LINK of the Canadian Patrol Frigate and the data alignment issues

    Science.gov (United States)

    Couture, Jean; Boily, Edouard; Simard, Marc-Alain

    1996-05-01

    The research and development group at Loral Canada is now at the second phase of the development of a data fusion demonstration model (DFDM) for a naval anti-air warfare to be used as a workbench tool to perform exploratory research. This project has emphatically addressed how the concepts related to fusion could be implemented within the Canadian Patrol Frigate (CPF) software environment. The project has been designed to read data passively on the CPF bus without any modification to the CPF software. This has brought to light important time alignment issues since the CPF sensors and the CPF command and control system were not important time alignment issues since the CPF sensors and the CPF command and control system were not originally designed to support a track management function which fuses information. The fusion of data from non-organic sensors with the tactical Link-11 data has produced stimulating spatial alignment problems which have been overcome by the use of a geodetic referencing coordinate system. Some benchmark scenarios have been selected to quantitatively demonstrate the capabilities of this fusion implementation. This paper describes the implementation design of DFDM (version 2), and summarizes the results obtained so far when fusing the scenarios simulated data.

  5. International bulletin on atomic and molecular data for fusion. No. 60

    International Nuclear Information System (INIS)

    Stephens, J.A.; Bannister, M.E.; Delcroix, J.L.; Fuhr, J.

    2001-06-01

    This bulletin comprises updated atomic and molecular data for fusion. It includes the Atomic and Molecular Data Information System (AMDIS) of the IAEA. It contains two parts: a bibliographic database for atomic and molecular data for fusion research, and numerical databases of recommended and evaluated atomic, molecular and plasma-surface interaction data. The indexed papers are also listed separately for structure and spectra, atomic and molecular collisions, and surface interactions

  6. Intelligent Networks Data Fusion Web-based Services for Ad-hoc Integrated WSNs-RFID

    Directory of Open Access Journals (Sweden)

    Falah Alshahrany

    2016-01-01

    Full Text Available The use of variety of data fusion tools and techniques for big data processing poses the problem of the data and information integration called data fusion having objectives which can differ from one application to another. The design of network data fusion systems aimed at meeting these objectives, need to take into account of the necessary synergy that can result from distributed data processing within the data networks and data centres, involving increased computation and communication. This papers reports on how this processing distribution is functionally structured as configurable integrated web-based support services, in the context of an ad-hoc wireless sensor network used for sensing and tracking, in the context of distributed detection based on complete observations to support real rime decision making. The interrelated functional and hardware RFID-WSN integration is an essential aspect of the data fusion framework that focuses on multi-sensor collaboration as an innovative approach to extend the heterogeneity of the devices and sensor nodes of ad-hoc networks generating a huge amount of heterogeneous soft and hard raw data. The deployment and configuration of these networks require data fusion processing that includes network and service management and enhances the performance and reliability of networks data fusion support systems providing intelligent capabilities for real-time control access and fire detection.

  7. Uncertainty representation, quantification and evaluation for data and information fusion

    CSIR Research Space (South Africa)

    De Villiers, Johan P

    2015-07-01

    Full Text Available are not or are incorrectly accounted for, fusion processes may provide under- or overconfident results, or in some cases incorrect results. These are often owing to incorrect or invalid simplifying assumptions during the modelling process. The authors investigate the sources...

  8. Remote Sensing Data Fusion to Detect Illicit Crops and Unauthorized Airstrips

    Science.gov (United States)

    Pena, J. A.; Yumin, T.; Liu, H.; Zhao, B.; Garcia, J. A.; Pinto, J.

    2018-04-01

    Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. Multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote sensing data fusion in detecting illicit crop through LSMM, GOBIA, and MCE analyzing of strategic information. This methodology emerges as a complementary and effective strategy to control and eradicate illicit crops.

  9. Atomic and plasma-material interaction data for fusion. V. 3

    International Nuclear Information System (INIS)

    1992-01-01

    This volume of Atomic and Plasma-Material Interaction Data for Fusion is devoted to atomic collision processes of helium atoms and of beryllium and boron atoms and ions in fusion plasmas. Most of the articles included in this volume are extended versions of the contributions presented at the IAEA experts' meetings on Atomic Data for Helium Beam Fusion Alpha Particle Diagnostics and on the Atomic Database for Beryllium and Boron, held in June 1991 at the IAEA headquarters in Vienna, or have resulted from the cross-section data analyses and evaluations performed by the working groups of these meetings. Refs, figs and tabs

  10. Capacity limits introduced by data fusion on cooperative spectrum sensing under correlated environments

    DEFF Research Database (Denmark)

    Pratas, Nuno; Marchetti, Nicola; Rodrigues, Antonio

    2010-01-01

    spectrum sensing scheme, by measuring the perceived capacity limits introduced by the use of data fusion on cooperative sensing schemes. The analysis is supported by evaluation metrics which account for the perceived capacity limits. The analysis is performed along the data fusion chain, comparing several...... scenarios encompassing different degree of environment correlation between the cluster nodes, number of cluster nodes and sensed channel occupation statistics. Through this study we motivate that to maximize the perceived capacity by the cooperative spectrum sensing, the use of data fusion needs...

  11. Beryllium data base for in-pile mockup test on blanket of fusion reactor, (1)

    Energy Technology Data Exchange (ETDEWEB)

    Kawamura, Hiroshi; Ishitsuka, Etsuo (Japan Atomic Energy Research Inst., Oarai, Ibaraki (Japan). Oarai Research Establishment); Sakamoto, Naoki; Kato, Masakazu; Takatsu, Hideyuki.

    1992-11-01

    Beryllium has been used in the fusion blanket designs with ceramic breeder as a neutron multiplier to increase the net tritium breeding ratio (TBR). The properties of beryllium, that is physical properties, chemical properties, thermal properties, mechanical properties, nuclear properties, radiation effects, etc. are necessary for the fusion blanket design. However, the properties of beryllium have not been arranged for the fusion blanket design. Therefore, it is indispensable to check and examine the material data of beryllium reported previously. This paper is the first one of the series of papers on beryllium data base, which summarizes the reported material data of beryllium. (author).

  12. IAEA specialists' meeting on the fusion evaluated nuclear data library related to the ITER activity

    International Nuclear Information System (INIS)

    Goulo, V.; Lorenz, A.

    1988-01-01

    This is the summary report of an IAEA Specialists' Meeting on the Fusion Evaluated Nuclear Data Library Related to the ITER Activity, convened by the IAEA Nuclear Data Section in Vienna from 16 to 18 November 1987. The objective of the meeting was to formulate a detailed programme and time schedule for the development of the Fusion Evaluated Nuclear Data Library (FENDL) to meet the future needs of the ITER activity

  13. Comparison of pH Data Measured with a pH Sensor Array Using Different Data Fusion Methods

    OpenAIRE

    Yi-Hung Liao; Jung-Chuan Chou

    2012-01-01

    This paper introduces different data fusion methods which are used for an electrochemical measurement using a sensor array. In this study, we used ruthenium dioxide sensing membrane pH electrodes to form a sensor array. The sensor array was used for detecting the pH values of grape wine, generic cola drink and bottled base water. The measured pH data were used for data fusion methods to increase the reliability of the measured results, and we also compared the fusion results with other differ...

  14. Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

    Science.gov (United States)

    Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

    2012-01-01

    RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

  15. Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

    Directory of Open Access Journals (Sweden)

    Sara Kangaspeska

    Full Text Available RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60% of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

  16. Atomic and plasma-material interaction data for fusion. V. 5

    International Nuclear Information System (INIS)

    1994-01-01

    Volume 5 of the supplements on ''atomic and plasma-material interaction data for fusion'' to the journal ''Nuclear Fusion'' is devoted to a critical assessment of the physical and thermo-mechanical properties of presently considered candidate plasma-facing and structural materials for next-generation thermonuclear fusion devices. It contains 9 papers. The subjects are: (i) requirements and selection criteria for plasma-facing materials and components in the ITER EDA (Engineering Design Activities) design; (ii) thermomechanical properties of Beryllium; (iii) material properties data for fusion reactor plasma-facing carbon-carbon composites; (iv) high-Z candidate plasma facing materials; (v) recommended property data for Molybdenum, Niobium and Vanadium alloys; (vi) copper alloys for high heat flux structure applications; (vii) erosion of plasma-facing materials during a tokamak disruption; (viii) runaway electron effects; and (ix) data bases for thermo-hydrodynamic coupling with coolants. Refs, figs, tabs

  17. Blob-level active-passive data fusion for Benthic classification

    Science.gov (United States)

    Park, Joong Yong; Kalluri, Hemanth; Mathur, Abhinav; Ramnath, Vinod; Kim, Minsu; Aitken, Jennifer; Tuell, Grady

    2012-06-01

    We extend the data fusion pixel level to the more semantically meaningful blob level, using the mean-shift algorithm to form labeled blobs having high similarity in the feature domain, and connectivity in the spatial domain. We have also developed Bhattacharyya Distance (BD) and rule-based classifiers, and have implemented these higher-level data fusion algorithms into the CZMIL Data Processing System. Applying these new algorithms to recent SHOALS and CASI data at Plymouth Harbor, Massachusetts, we achieved improved benthic classification accuracies over those produced with either single sensor, or pixel-level fusion strategies. These results appear to validate the hypothesis that classification accuracy may be generally improved by adopting higher spatial and semantic levels of fusion.

  18. Present status on atomic and molecular data relevant to fusion plasma diagnostics and modeling

    International Nuclear Information System (INIS)

    Tawara, H.

    1997-01-01

    This issue is the collection of the paper presented status on atomic and molecular data relevant to fusion plasma diagnostics and modeling. The 10 of the presented papers are indexed individually. (J.P.N.)

  19. International Bulletin on Atomic and Molecular Data for Fusion. No. 28

    International Nuclear Information System (INIS)

    Hughes, J.G.

    1985-03-01

    The bulletin presents a selected bibliography (462 literature pieces) on atomic and molecular data relevant to fusion research and technology. It also gives a list of indexed papers, separately on structure and spectra, atomic and molecular collisions, and surface effects

  20. International Bulletin on Atomic and Molecular Data for Fusion. No. 31

    International Nuclear Information System (INIS)

    Hughes, J.G.

    1985-12-01

    This bulletin presents a selected bibliography (363 literature pieces) on atomic and molecular data for fusion. It also gives a list of indexed papers on structure and spectra, atomic and molecular collisions, and surface interactions

  1. Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map

    Directory of Open Access Journals (Sweden)

    Myroslava Lesiv

    2016-03-01

    Full Text Available Data fusion represents a powerful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own. This paper focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study, we compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-weighted logistic regression (GWR, as well as classification and regression trees (CART. We ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference between the methods. However, GWR was found to perform better than the other tested methods in areas with high disagreement between the inputs.

  2. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

    Science.gov (United States)

    Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

    2018-02-06

    This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

  3. Sensor Fusion Techniques for Phased-Array Eddy Current and Phased-Array Ultrasound Data

    Energy Technology Data Exchange (ETDEWEB)

    Arrowood, Lloyd F. [Y-12 National Security Complex, Oak Ridge, TN (United States)

    2018-03-15

    Sensor (or Data) fusion is the process of integrating multiple data sources to produce more consistent, accurate and comprehensive information than is provided by a single data source. Sensor fusion may also be used to combine multiple signals from a single modality to improve the performance of a particular inspection technique. Industrial nondestructive testing may utilize multiple sensors to acquire inspection data depending upon the object under inspection and the anticipated types of defects that can be identified. Sensor fusion can be performed at various levels of signal abstraction with each having its strengths and weaknesses. A multimodal data fusion strategy first proposed by Heideklang and Shokouhi that combines spatially scattered detection locations to improve detection performance of surface-breaking and near-surface cracks in ferromagnetic metals is shown using a surface inspection example and is then extended for volumetric inspections. Utilizing data acquired from an Olympus Omniscan MX2 from both phased array eddy current and ultrasound probes on test phantoms, single and multilevel fusion techniques are employed to integrate signals from the two modalities. Preliminary results demonstrate how confidence in defect identification and interpretation benefit from sensor fusion techniques. Lastly, techniques for integrating data into radiographic and volumetric imagery from computed tomography are described and results are presented.

  4. Data fusion of Landsat TM and IRS images in forest classification

    Science.gov (United States)

    Guangxing Wang; Markus Holopainen; Eero Lukkarinen

    2000-01-01

    Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

  5. International bulletin on atomic and molecular data for fusion. No. 11

    International Nuclear Information System (INIS)

    Katsonis, K.; Rumble, J. Jr.

    1980-01-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported. The bulletin contains a list of references the publications on controlled fusion and plasma physics for 1979. It contains an index to the contributed papers presented at the 11th International Conference on the Physics of Electronics and Atomic Collision (ICPEAC) held in Kyoto (Japan) in summer 1979

  6. REMOTE SENSING DATA FUSION TO DETECT ILLICIT CROPS AND UNAUTHORIZED AIRSTRIPS

    OpenAIRE

    Pena, J. A.; Yumin, T.; Liu, H.; Zhao, B.; Garcia, J. A.; Pinto, J.

    2018-01-01

    Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. Multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote se...

  7. An epidemic model for biological data fusion in ad hoc sensor networks

    Science.gov (United States)

    Chang, K. C.; Kotari, Vikas

    2009-05-01

    Bio terrorism can be a very refined and a catastrophic approach of attacking a nation. This requires the development of a complete architecture dedicatedly designed for this purpose which includes but is not limited to Sensing/Detection, Tracking and Fusion, Communication, and others. In this paper we focus on one such architecture and evaluate its performance. Various sensors for this specific purpose have been studied. The accent has been on use of Distributed systems such as ad-hoc networks and on application of epidemic data fusion algorithms to better manage the bio threat data. The emphasis has been on understanding the performance characteristics of these algorithms under diversified real time scenarios which are implemented through extensive JAVA based simulations. Through comparative studies on communication and fusion the performance of channel filter algorithm for the purpose of biological sensor data fusion are validated.

  8. A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Feng Lu

    2016-10-01

    Full Text Available Gas path fault diagnosis involves the effective utilization of condition-based sensor signals along engine gas path to accurately identify engine performance failure. The rapid development of information processing technology has led to the use of multiple-source information fusion for fault diagnostics. Numerous efforts have been paid to develop data-based fusion methods, such as neural networks fusion, while little research has focused on fusion architecture or the fusion of different method kinds. In this paper, a data hierarchical fusion using improved weighted Dempster–Shaffer evidence theory (WDS is proposed, and the integration of data-based and model-based methods is presented for engine gas-path fault diagnosis. For the purpose of simplifying learning machine typology, a recursive reduced kernel based extreme learning machine (RR-KELM is developed to produce the fault probability, which is considered as the data-based evidence. Meanwhile, the model-based evidence is achieved using particle filter-fuzzy logic algorithm (PF-FL by engine health estimation and component fault location in feature level. The outputs of two evidences are integrated using WDS evidence theory in decision level to reach a final recognition decision of gas-path fault pattern. The characteristics and advantages of two evidences are analyzed and used as guidelines for data hierarchical fusion framework. Our goal is that the proposed methodology provides much better performance of gas-path fault diagnosis compared to solely relying on data-based or model-based method. The hierarchical fusion framework is evaluated in terms to fault diagnosis accuracy and robustness through a case study involving fault mode dataset of a turbofan engine that is generated by the general gas turbine simulation. These applications confirm the effectiveness and usefulness of the proposed approach.

  9. Funding for the 2ND IAEA technical meeting on fusion data processing, validation and analysis

    Energy Technology Data Exchange (ETDEWEB)

    Greenwald, Martin

    2017-06-02

    The International Atomic Energy Agency (IAEA) will organize the second Technical Meeting on Fusion Da Processing, Validation and Analysis from 30 May to 02 June, 2017, in Cambridge, MA USA. The meeting w be hosted by the MIT Plasma Science and Fusion Center (PSFC). The objective of the meeting is to provide a platform where a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolation needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge based understanding of the physical processes governing the dynamics of these plasmas. The meeting will aim at fostering, in particular, discussions of research and development results that set out or underline trends observed in the current major fusion confinement devices. General information on the IAEA, including its mission and organization, can be found at the IAEA websit Uncertainty quantification (UQ) Model selection, validation, and verification (V&V) Probability theory and statistical analysis Inverse problems & equilibrium reconstru ction Integrated data analysis Real time data analysis Machine learning Signal/image proc essing & pattern recognition Experimental design and synthetic diagnostics Data management

  10. Nuclear data for fusion: Validation of typical pre-processing methods for radiation transport calculations

    International Nuclear Information System (INIS)

    Hutton, T.; Sublet, J.C.; Morgan, L.; Leadbeater, T.W.

    2015-01-01

    Highlights: • We quantify the effect of processing nuclear data from ENDF to ACE format. • We consider the differences between fission and fusion angular distributions. • C-nat(n,el) at 2.0 MeV has a 0.6% deviation between original and processed data. • Fe-56(n,el) at 14.1 MeV has a 11.0% deviation between original and processed data. • Processed data do not accurately depict ENDF distributions for fusion energies. - Abstract: Nuclear data form the basis of the radiation transport codes used to design and simulate the behaviour of nuclear facilities, such as the ITER and DEMO fusion reactors. Typically these data and codes are biased towards fission and high-energy physics applications yet are still applied to fusion problems. With increasing interest in fusion applications, the lack of fusion specific codes and relevant data libraries is becoming increasingly apparent. Industry standard radiation transport codes require pre-processing of the evaluated data libraries prior to use in simulation. Historically these methods focus on speed of simulation at the cost of accurate data representation. For legacy applications this has not been a major concern, but current fusion needs differ significantly. Pre-processing reconstructs the differential and double differential interaction cross sections with a coarse binned structure, or more recently as a tabulated cumulative distribution function. This work looks at the validity of applying these processing methods to data used in fusion specific calculations in comparison to fission. The relative effects of applying this pre-processing mechanism, to both fission and fusion relevant reaction channels are demonstrated, and as such the poor representation of these distributions for the fusion energy regime. For the nat C(n,el) reaction at 2.0 MeV, the binned differential cross section deviates from the original data by 0.6% on average. For the 56 Fe(n,el) reaction at 14.1 MeV, the deviation increases to 11.0%. We

  11. International bulletin on atomic and molecular data for fusion. No.2

    International Nuclear Information System (INIS)

    Beaty, E.C.; Katsonis, K.

    1977-10-01

    This bulletin deals with atomic and molecular data for fusion (spectroscopic data, atomic and molecular collisions, surface effects, ...). Particular emphasis is given to data applicable to Tokamak devices. A bibliography for the most recent data presented in the document is provided. A description of work in progress and ''Data Requests'' in the fusion field are also mentioned. Numerical data on light ion sputtering yields of first wall materials, electron capture and impact ionization for iron ions colliding with molecular hydrogen and charge exchange between multicharged ions and helium, argon, and, atomic or molecular hydrogen are given

  12. A study on the nuclear fusion reactor - A study on the data acquisition system for the nuclear fusion reactor

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Seoung Jong; Son, Dong Chul; Park, Il Hung; Oh, Young Do [Kyungpook University, Taegu (Korea, Republic of); Chang, Doo Hee [Hanyang University, Seoul (Korea, Republic of)

    1996-09-01

    We have constructed a VXI data acquisition system to measure plasma position at KT-1 in KAERI, using HP-VEE, HP V/382 and HP E1429A. Currently we are analyzing data. We have also established basic concepts for the plasma feedback control system at KT-1, and selected necessary hardwares and softwares. The system has been set up and is being tested. The digital feedback control system provides more versatile control of plasma position and shape than the analog system by software programming. The digital system has been chosen so that the plasma feedback control could be done in real-time (target feedback loop-time : < 0.5 msec). After considering compatibility and extensibility of the system, we have selected VxWorks for a real-time operating system, MVME 167, Pentek 4284 VME DSP based on the platform of TI TMS320C40, Pentek 4248 ADC, Pentek 4253 DAC. These Pentek modules uses a local bus to maximize the data transfer rate. To evaluate MMI which may provide operators of fusion devices for easy and simple access to data acquisition, we have written test codes with free Tcl/Tk. Tcl/Tk turned out to be easy to write powerful programs and can be useful for MMI of fusion devices. 21 ref., 7 tabs., 24 figs. (author)

  13. Copper benchmark experiment for the testing of JEFF-3.2 nuclear data for fusion applications

    OpenAIRE

    Angelone, M.; Flammini, D.; Loreti, S.; Moro, F.; Pillon, M.; Villar, R.; Klix, A.; Fischer, U.; Kodeli, I.; Perel, R.L.; Pohorecky, W.

    2017-01-01

    A neutronics benchmark experiment on a pure Copper block (dimensions 60 × 70 × 70 cm3) aimed at testing and validating the recent nuclear data libraries for fusion applications was performed in the frame of the European Fusion Program at the 14 MeV ENEA Frascati Neutron Generator (FNG). Reaction rates, neutron flux spectra and doses were measured using different experimental techniques (e.g. activation foils techniques, NE213 scintillator and thermoluminescent detectors). This paper first sum...

  14. Leaf area index uncertainty estimates for model-data fusion applications

    Science.gov (United States)

    Andrew D. Richardson; D. Bryan Dail; D.Y. Hollinger

    2011-01-01

    Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model-data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux...

  15. The fusion evaluated data library (FENDL) its processing and related benchmark calculations

    International Nuclear Information System (INIS)

    Muir, D.W.

    1989-01-01

    FENDL is a nuclear data library being assembled by the IAEA Nuclear Data Section, in support of a variety of national and international fusion research projects. Notable examples of such projects are the International Experimental Thermonuclear Reactor (ITER), Fusion Engineering Reactor (FER, Japan), and the Next European Torus (NET). The development of the FENDL library is an approved program of the IAEA and is supported by several IAEA Coordinated Research Programs. It appears to me that the planned FENDL data processing and data testing efforts will be a shared effort, with significant contributions coming from the IAEA itself and from the participating research laboratories and data centers

  16. International bulletin on atomic and molecular data for fusion. No.6

    International Nuclear Information System (INIS)

    Katsonis, K.; Smith, F.J.

    1978-10-01

    This bulletin deals with atomic and molecular data for fusion (spectroscopic data, atomic and molecular collisions, surface effects, ...). Particular emphasis is given to data applicable to Tokamak devices. A bibliography for the most recent data presented in the document is provided. A description of work in progress and ''Data Requests'' in the fusion field are also mentioned. Cross-sections for the electron impact excitation of 2sub(p1/2) and 2sub(p3/2) states of the lithium-line ions C 3+ , F 23+ , Mo 39+ and W 71+ calculated in the relativistic Coulomb-Born approximation are presented

  17. International bulletin on atomic and molecular data for fusion. No. 47

    International Nuclear Information System (INIS)

    Botero, J.

    1993-12-01

    This bulletin, published by the IAEA, provides atomic and molecular data references relevant to fusion research and technology. In part I the indexation of the papers is provided separately for (i) structure and spectra, (ii) atomic and molecular collisions, and (iii) surface interactions. Part II contains the bibliographic data for the above-listed topics and for high-energy laser and beam-matter interaction of atomic particles with fields. Also included are sections on atomic and molecular data needs for fusion research and on news about ALADDIN (A Labelled Atomic Data INterface) and evaluated data bases

  18. A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

    Science.gov (United States)

    Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

    2011-06-01

    We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

  19. Distributed service-based approach for sensor data fusion in IoT environments.

    Science.gov (United States)

    Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A; Gutiérrez-Guerrero, José M; Muros-Cobos, Jesús L

    2014-10-15

    The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.

  20. Control and data management for a large fusion laser

    International Nuclear Information System (INIS)

    Davis, J.W.; Holloway, F.W.

    1975-01-01

    SHIVA is a powerful (10-kJ 25 TW) neodymium glass laser system to be used (in 1977) for target irradiation in fusion research. SHIVA is also a development project in that it is pushing the state of the art in laser and optical technology. The present design calls for 20 parallel laser amplification chains whose light output is pointed and focused at a small (100 μ) target within a chamber from semi-equally spaced three-dimensional directions. It is probable that SHIVA will be upgraded to as many as 42 chains in the next few years. Each chain of SHIVA contains 7 high energy laser amplifiers and perhaps 20 other major optical components, many of which send and receive control and measurement information. Again future expansion may add additional elements. Each chain has also associated 10 gimbal or translation motions for beam assignment from the oscillator onto the target

  1. Fusion-related work at the Nuclear Energy Agency Data Bank

    International Nuclear Information System (INIS)

    Henriksson, H.; Mompean, F.J.; Kodeli, I.

    2007-01-01

    The OECD Nuclear Energy Agency (NEA) Data Bank is part of an international network of data centres in charge of the compilation and dissemination of basic nuclear reaction data. Through its activities in the reaction data field, the NEA participates in the preparation of data for the modelling of future nuclear facility concepts and the development of reactor installations. A working party at the NEA on international nuclear data evaluation cooperation (WPEC) is established to promote the exchange of nuclear data evaluations, measurements, nuclear model calculations and validation. WPEC provides a framework for co-operative activities, such as the high priority request list for experimental data of special interest for certain applications, such as IFMIF or ITER. The NEA Data Bank administrates the collection and validation as well as the distribution of the Joint Evaluated Fusion and Fission (JEFF) library, where the activities in the European Fusion and Activation File projects (EFF and EAF respectively) play an important role for new data evaluations. The topics cover verification of activation and transport data, calculation methods and validation via integral experiments. The EFF project brings together all available expertise in Europe related to the nuclear data requirements of existing and future fusion devices, and the project contributed greatly to the internationally recognised nuclear data library JEFF-3.1, released in May 2005. The NEA also provides tools for the EFF project, such as computer codes for nuclear energy and radiation physics applications. Of special interest for fusion applications are the integral experiments collected in the Shielding Integral Benchmark Archive Database (SINBAD) database. SINBAD is an internationally established set of radiation shielding and dosimetry data containing over 80 experiments relevant for reactor and accelerator shielding. About 30 of these experiments are dedicated to fusion blanket neutronics. Materials

  2. International bulletin on atomic and molecular data for fusion. No. 59

    International Nuclear Information System (INIS)

    Stephens, J.A.; Bannister, M.E.; Fuhr, J.; Gilbody, H.B.

    2001-03-01

    The International Bulletin on Atomic and Molecular Data for Fusion is prepared by the Atomic and Molecular Data Unit of the International Atomic Energy Agency. It is distributed free of charge by the IAEA to assist in the development of fusion research and technology. In part 1, the Atomic and Molecular Data Information System (AMDIS) is presented. In Part 2, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part 3 contains all the bibliographic data for both the indexed and non-indexed references. Finally, the Author Index (part 4) refers to the bibliographic references contained in part 3

  3. Integral data testing of JENDL-3.2 for fusion reactor and shielding applications

    International Nuclear Information System (INIS)

    Oyama, Yukio

    1995-01-01

    Integral data testing of JENDL-3.2 is being performed in the activities of two working groups of the Japanese Nuclear Data Committee. The continuous and group-wise libraries prepared from JENDL-3.2 are planned to be tested by the working groups. In this paper, the continuous library FSXLIB-J3R2 processed from JENDL-3.2 for MCNP was tested for fission and fusion neutrons using data of integral experiments and compared to the results of JENDL-3.1. The results of integral data testing of JENDL-3.2 for fusion and shielding application are reviewed. (author)

  4. International bulletin on atomic and molecular data for fusion. No. 58

    International Nuclear Information System (INIS)

    Stephens, J.; Bannister, M.E.; Fuhr, J.; Gilbody, H.B.

    2000-06-01

    The International Bulletin on Atomic and Molecular Data for Fusion is prepared by the Atomic and Molecular Data Unit of the International Atomic Energy Agency. It is distributed free of charge by the IAEA to assist in the development of fusion research and technology. In part 1, the Atomic and Molecular Data Information System (AMDIS) is presented. In Part 2, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part 3 contains all the bibliographic data for both the indexed and non-indexed references. Finally, the Author Index (part 4) refers to the bibliographic references contained in part 3

  5. The Activities of the European Consortium on Nuclear Data Development and Analysis for Fusion

    International Nuclear Information System (INIS)

    Fischer, U.; Avrigeanu, M.; Avrigeanu, V.; Cabellos, O.; Kodeli, I.; Koning, A.; Konobeyev, A.Yu.; Leeb, H.; Rochman, D.; Pereslavtsev, P.; Sauvan, P.; Sublet, J.-C.; Trkov, A.; Dupont, E.; Leichtle, D.; Izquierdo, J.

    2014-01-01

    This paper presents an overview of the activities of the European Consortium on Nuclear Data Development and Analysis for Fusion. The Consortium combines available European expertise to provide services for the generation, maintenance, and validation of nuclear data evaluations and data files relevant for ITER, IFMIF and DEMO, as well as codes and software tools required for related nuclear calculations

  6. The Activities of the European Consortium on Nuclear Data Development and Analysis for Fusion

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, U., E-mail: ulrich.fischer@kit.edu [Karlsruhe Institute of Technology, Institute for Neutron Physic and Reactor Technology, 76344 Eggenstein-Leopoldshafen (Germany); Avrigeanu, M.; Avrigeanu, V. [Horia Hulubei National Institute of Physics and Nuclear Engineering (IFIN-HH), RO-077125 Magurele (Romania); Cabellos, O. [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid, 28006 Madrid (Spain); Kodeli, I. [Jozef Stefan Institute (JSI), Jamova 39, 1000 Ljubljana (Slovenia); Koning, A. [Nuclear Research and Consultancy Group (NRG), Westerduinweg 3, 1755 LE Petten (Netherlands); Konobeyev, A.Yu. [Karlsruhe Institute of Technology, Institute for Neutron Physic and Reactor Technology, 76344 Eggenstein-Leopoldshafen (Germany); Leeb, H. [Technische Universitaet Wien, Atominstitut, Wiedner Hauptstrasse 8–10, 1040 Wien (Austria); Rochman, D. [Nuclear Research and Consultancy Group (NRG), Westerduinweg 3, 1755 LE Petten (Netherlands); Pereslavtsev, P. [Karlsruhe Institute of Technology, Institute for Neutron Physic and Reactor Technology, 76344 Eggenstein-Leopoldshafen (Germany); Sauvan, P. [Universidad Nacional de Educacion a Distancia, C. Juan del Rosal, 12, 28040 Madrid (Spain); Sublet, J.-C. [Euratom/CCFE Fusion Association, Culham Science Centre, OX14 3DB (United Kingdom); Trkov, A. [Jozef Stefan Institute (JSI), Jamova 39, 1000 Ljubljana (Slovenia); Dupont, E. [OECD Nuclear Energy Agency, Paris (France); Leichtle, D.; Izquierdo, J. [Fusion for Energy, Barcelona (Spain)

    2014-06-15

    This paper presents an overview of the activities of the European Consortium on Nuclear Data Development and Analysis for Fusion. The Consortium combines available European expertise to provide services for the generation, maintenance, and validation of nuclear data evaluations and data files relevant for ITER, IFMIF and DEMO, as well as codes and software tools required for related nuclear calculations.

  7. SimFuse: A Novel Fusion Simulator for RNA Sequencing (RNA-Seq Data

    Directory of Open Access Journals (Sweden)

    Yuxiang Tan

    2015-01-01

    Full Text Available The performance evaluation of fusion detection algorithms from high-throughput sequencing data crucially relies on the availability of data with known positive and negative cases of gene rearrangements. The use of simulated data circumvents some shortcomings of real data by generation of an unlimited number of true and false positive events, and the consequent robust estimation of accuracy measures, such as precision and recall. Although a few simulated fusion datasets from RNA Sequencing (RNA-Seq are available, they are of limited sample size. This makes it difficult to systematically evaluate the performance of RNA-Seq based fusion-detection algorithms. Here, we present SimFuse to address this problem. SimFuse utilizes real sequencing data as the fusions’ background to closely approximate the distribution of reads from a real sequencing library and uses a reference genome as the template from which to simulate fusions’ supporting reads. To assess the supporting read-specific performance, SimFuse generates multiple datasets with various numbers of fusion supporting reads. Compared to an extant simulated dataset, SimFuse gives users control over the supporting read features and the sample size of the simulated library, based on which the performance metrics needed for the validation and comparison of alternative fusion-detection algorithms can be rigorously estimated.

  8. FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud.

    Science.gov (United States)

    Márquez, Cristina; López, M Isabel; Ruisánchez, Itziar; Callao, M Pilar

    2016-12-01

    Two data fusion strategies (high- and mid-level) combined with a multivariate classification approach (Soft Independent Modelling of Class Analogy, SIMCA) have been applied to take advantage of the synergistic effect of the information obtained from two spectroscopic techniques: FT-Raman and NIR. Mid-level data fusion consists of merging some of the previous selected variables from the spectra obtained from each spectroscopic technique and then applying the classification technique. High-level data fusion combines the SIMCA classification results obtained individually from each spectroscopic technique. Of the possible ways to make the necessary combinations, we decided to use fuzzy aggregation connective operators. As a case study, we considered the possible adulteration of hazelnut paste with almond. Using the two-class SIMCA approach, class 1 consisted of unadulterated hazelnut samples and class 2 of samples adulterated with almond. Models performance was also studied with samples adulterated with chickpea. The results show that data fusion is an effective strategy since the performance parameters are better than the individual ones: sensitivity and specificity values between 75% and 100% for the individual techniques and between 96-100% and 88-100% for the mid- and high-level data fusion strategies, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Description of card input data and formats for the International Bulletin on Atomic and Molecular Data for Fusion

    International Nuclear Information System (INIS)

    Katsonis, K.; Smith, F.J.

    1979-05-01

    This document describes the input data and the corresponding format of the computer programme which is used by the Atomic and Molecular Unit of the IAEA for storing, compiling and retrieving numerical data and/or bibliographic information for publishing the International Bulletin on Atomic and Molecular Data for Fusion

  10. Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

    Science.gov (United States)

    Passman, Dina B.

    2013-01-01

    Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending

  11. A DATA FUSION SYSTEM FOR THE NONDESTRUCTIVE EVALUATION OF NON-PIGGABLE PIPES

    Energy Technology Data Exchange (ETDEWEB)

    Shreekanth Mandayam; Robi Polikar; John C. Chen

    2004-04-01

    The objectives of this research project are: (1) To design sensor data fusion algorithms that can synergistically combine defect related information from heterogeneous sensors used in gas pipeline inspection for reliably and accurately predicting the condition of the pipe-wall. (2) To develop efficient data management techniques for signals obtained during multisensor interrogation of a gas pipeline. During this reporting period, Rowan University designed, developed and exercised multisensor data fusion algorithms for identifying defect related information present in magnetic flux leakage, ultrasonic testing and thermal imaging nondestructive evaluation signatures of a test-specimen suite representative of benign and anomalous indications in gas transmission pipelines.

  12. Deep learning decision fusion for the classification of urban remote sensing data

    Science.gov (United States)

    Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

    2018-01-01

    Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

  13. Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

    Science.gov (United States)

    Czaja, Wojciech; Le Moigne-Stewart, Jacqueline

    2014-01-01

    In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

  14. Retrieval of the vertical column of an atmospheric constituent from data fusion of remote sensing measurements

    International Nuclear Information System (INIS)

    Ceccherini, Simone; Carli, Bruno; Cortesi, Ugo; Del Bianco, Samuele; Raspollini, Piera

    2010-01-01

    Techniques of data fusion are presently being considered with increasing interest for application to atmospheric observations from space because of their capability to optimally exploit the complementary information provided by different instruments operating aboard on-going and future satellite missions. The task of combining measurements of the same target, when carried out at the level of the retrieved state vectors, faces with two major problems: the need to interpolate the products represented on different retrieval grids which determines a loss of information and the presence of a priori information in the products that can determine a bias in the product of the data fusion. The measurement space solution method avoids these problems. Based on this method we present a novel approach to retrieve the vertical column of an atmospheric constituent from data fusion of remote sensing measurements. We apply the method to retrieve the ozone column from the fusion of simulated measurements of the IASI nadir-viewing spectrometer onboard the METOP-A platform and of the MIPAS limb sounder onboard the ENVISAT satellite. The performance of the method is evaluated in terms of retrieval errors and averaging kernels of the products. The results show the evidence of improved retrieval quality when comparing the outcome of data fusion with that of the inversion process applied to spectra from either of the two instruments.

  15. Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach.

    Science.gov (United States)

    Peng, Changhui; Guiot, Joel; Wu, Haibin; Jiang, Hong; Luo, Yiqi

    2011-05-01

    It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. Model-data fusion (MDF) is an emerging area of research in ecology and palaeoecology. It provides a new quantitative approach that offers a high level of empirical constraint over model predictions based on observations using inverse modelling and data assimilation (DA) techniques. Increasing demands to integrate model and data methods in the past decade has led to MDF utilization in palaeoecology, ecology and earth system sciences. This paper reviews key features and principles of MDF and highlights different approaches with regards to DA. After providing a critical evaluation of the numerous benefits of MDF and its current applications in palaeoecology (i.e., palaeoclimatic reconstruction, palaeovegetation and palaeocarbon storage) and ecology (i.e. parameter and uncertainty estimation, model error identification, remote sensing and ecological forecasting), the paper discusses method limitations, current challenges and future research direction. In the ongoing data-rich era of today's world, MDF could become an important diagnostic and prognostic tool in which to improve our understanding of ecological processes while testing ecological theory and hypotheses and forecasting changes in ecosystem structure, function and services. © 2011 Blackwell Publishing Ltd/CNRS.

  16. Towards a Unified Approach to Information Integration - A review paper on data/information fusion

    Energy Technology Data Exchange (ETDEWEB)

    Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

    2005-10-14

    Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, information is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.

  17. Atomic and Plasma-Material Interaction Data for Fusion. V. 16

    International Nuclear Information System (INIS)

    Braams, B.J.; Chung, H.-K.

    2014-03-01

    A wide variety of atomic, molecular, radiative and plasma-wall interaction processes involving a mixture of atoms, ions and molecules occur in the plasmas produced in nuclear fusion experiments. In the low temperature divertor and near wall region, molecules and molecular ions are formed. The plasma particles react with electrons and with each other. Plasma modelling requires cross-sections and rate coefficients for all these processes, and in addition spectral signatures to support interpretation of data from fusion experiments. The mission of the International Atomic Energy Agency Nuclear Data Section (IAEA/NDS) in the area of atomic and molecular data is to enhance the competencies of Member States in their research into nuclear fusion through the provision of internationally recommended atomic, molecular, plasma-material interaction and material properties databases. One mechanism by which the IAEA pursues this mission is the Coordinated Research Project (CRP). The present volume of Atomic and Plasma-Material Interaction Data for Fusion contains contributions from participants in the CRP 'Atomic and Molecular Data for Plasma Modelling' (2004-2008). This CRP was concerned with data for processes in the near wall and divertor plasma and plasma-wall interaction in fusion experiments, with focus on cross-sections for molecular reactions. Participants in the CRP came from 14 different institutes, many with strong ties to fusion plasma modelling and experiment. D. Humbert of the Nuclear Data Section was scientific secretary of the CRP. Participants' contributions for this volume were collected and refereed after the conclusion of the CRP

  18. System Capacity Limits Introduced by Data Fusion on Cooperative Spectrum Sensing under Correlated Environments

    DEFF Research Database (Denmark)

    Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

    2010-01-01

    on cooperative sensing schemes. The analysis is supported by evaluation metrics which accounts for the perceived capacity limits. The analysis is performed along the data fusion chain, comparing several scenarios encompassing different degrees of environment correlation between the cluster nodes, number......Spectrum sensing, the cornerstone of the Cognitive Radio paradigm, has been the focus of intensive research, from which the main conclusion was that its performance can be greatly enhanced through the use of cooperative sensing schemes. Nevertheless, if a proper design of the cooperative scheme...... is not followed, then the use of cooperative schemes will introduce some limitations in the network perceived capacity. In this paper, we analyze the performance of a cooperative spectrum sensing scheme based on Data Fusion, by measuring the perceived capacity limits introduced by the use of Data Fusion...

  19. Distributed Pedestrian Detection Alerts Based on Data Fusion with Accurate Localization

    Directory of Open Access Journals (Sweden)

    Arturo de la Escalera

    2013-09-01

    Full Text Available Among Advanced Driver Assistance Systems (ADAS pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

  20. Distributed pedestrian detection alerts based on data fusion with accurate localization.

    Science.gov (United States)

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-09-04

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

  1. Encoding technique for high data compaction in data bases of fusion devices

    International Nuclear Information System (INIS)

    Vega, J.; Cremy, C.; Sanchez, E.; Portas, A.; Dormido, S.

    1996-01-01

    At present, data requirements of hundreds of Mbytes/discharge are typical in devices such as JET, TFTR, DIII-D, etc., and these requirements continue to increase. With these rates, the amount of storage required to maintain discharge information is enormous. Compaction techniques are now essential to reduce storage. However, general compression techniques may distort signals, but this is undesirable for fusion diagnostics. We have developed a general technique for data compression which is described here. The technique, which is based on delta compression, does not require an examination of the data as in delayed methods. Delta values are compacted according to general encoding forms which satisfy a prefix code property and which are defined prior to data capture. Several prefix codes, which are bit oriented and which have variable code lengths, have been developed. These encoding methods are independent of the signal analog characteristics and enable one to store undistorted signals. The technique has been applied to databases of the TJ-I tokamak and the TJ-IU torsatron. Compaction rates of over 80% with negligible computational effort were achieved. Computer programs were written in ANSI C, thus ensuring portability and easy maintenance. We also present an interpretation, based on information theory, of the high compression rates achieved without signal distortion. copyright 1996 American Institute of Physics

  2. International bulletin on atomic and molecular data for fusion. No. 39

    International Nuclear Information System (INIS)

    Smith, J.J.

    1989-07-01

    The Bulletin provides information on atomic and molecular data relevant for fusion research. In part I the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface interactions. Part II contains all the bibliographic data for both the indexed and non-indexed references (514 references). An author index is included

  3. International bulletin on atomic and molecular data for fusion. No. 25

    International Nuclear Information System (INIS)

    Katsonis, K.

    1984-06-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is also briefly reported (Collision strengths and recombination coefficients for ions of C,N,O; Reactions between ions and atomic hydrogen; Cross sections for electron impact ionisation of Ne + , Ti + and Ni + ions)

  4. International bulletin on atomic and molecular data for fusion. No. 35

    International Nuclear Information System (INIS)

    Smith, J.J.

    1987-05-01

    The bulletin provides information on atomic and molecular data for fusion research. In Part I the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface effects. Part II contains all the bibliographic data for both indexed and non-indexed references (536 references). An author index is included

  5. International bulletin on atomic and molecular data for fusion. No. 24

    International Nuclear Information System (INIS)

    Katsonis, K.

    1984-01-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided, work in progress is briefly reported: Transport on tokamak plasmas simulation, post collisions of gold ions in helium

  6. International bulletin on atomic and molecular data for fusion. No. 27

    International Nuclear Information System (INIS)

    Hughes, J.G.

    1984-12-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent relevent data, summarized in the document, is provided (373 literature pieces). Work in progress on the ionization by electron impact (theoretical results) is also briefly reported on

  7. Atomic data for controlled fusion research. Volume III. Particle interactions with surfaces

    International Nuclear Information System (INIS)

    Thomas, E.W.

    1985-02-01

    This report provides a handbook of data concerning particle solid interactions that are relevant to plasma-wall interactions in fusion devices. Published data have been collected, assessed, and represented by a single functional relationship which is presented in both tabular and graphical form. Mechanisms reviewed here include sputtering, secondary electron emission, particle reflection, and trapping

  8. International bulletin on atomic and molecular data for fusion. No. 23

    International Nuclear Information System (INIS)

    Katsonis, K.

    1983-09-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported (OIV in temperature and density diagnostics, measured cross section for electron impact ionization of Iron and Tungsten)

  9. International Bulletin on Atomic and Molecular Data for Fusion. No. 36

    International Nuclear Information System (INIS)

    Smith, J.J.

    1987-10-01

    The bulletin provides information on atomic and molecular data relevant for fusion research. In Part I the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part II contains all the bibliographic data for both the indexed and non-indexed references (555 references). An author index is included

  10. International bulletin on atomic and molecular data for fusion. No. 38

    International Nuclear Information System (INIS)

    Smith, J.J.

    1989-01-01

    The Bulletin provides information on atomic and molecular data relevant for fusion research. In Part I the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part II contains all the bibliographic data for both the indexed and non-indexed references (654 references). An author index is included

  11. International bulletin on atomic and molecular data for fusion. No. 18

    International Nuclear Information System (INIS)

    Katsonis, K.

    1982-02-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported (electron impact excitation of hydrogen-like argon ions, excitation and charge transfer in collisions of Li atoms with alpha particles)

  12. Atomic and plasma-material interaction data for fusion. V.4

    International Nuclear Information System (INIS)

    1993-01-01

    The International Atomic Energy Agency, through its Atomic and Molecular Data Unit, coordinates a wide spectrum of programmes for the compilation, evaluation, and generation of atomic, molecular, and plasma-wall interaction data for fusion research. The present volume is exclusively devoted to cross sections for collisions of hydrogen atoms with electron, protons and multiply charged ions

  13. On data mining in context : cases, fusion and evaluation

    NARCIS (Netherlands)

    Putten, Petrus Wilhelmus Henricus van der

    2010-01-01

    Data mining can be seen as a process, with modeling as the core step. However, other steps such as planning, data preparation, evaluation and deployment are of key importance for applications. This thesis studies data mining in the context of these other steps with the goal of improving data mining

  14. Computational methods, tools and data for nuclear analyses of fusion technology systems

    International Nuclear Information System (INIS)

    Fischer, U.

    2006-01-01

    An overview is presented of the Research and Development work conducted at Forschungszentrum Karlsruhe in co-operation with other associations in the framework of the European Fusion Technology Programme on the development and qualification of computational tools and data for nuclear analyses of Fusion Technology systems. The focus is on the development of advanced methods and tools based on the Monte Carlo technique for particle transport simulations, and the evaluation and qualification of dedicated nuclear data to satisfy the needs of the ITER and the IFMIF projects. (author)

  15. Actinide cross section data and inertial confinement fusion for long term waste disposal

    International Nuclear Information System (INIS)

    Meldner, H.

    1979-01-01

    Actinide cross section data at thermonuclear neutron energies are needed for the calculation of ICF pellet center burnup of fission reactor waste, viz. 14 MeV neutron fission of the very long-lived actinides that pose storage problems. A major advantage of pellet center burnup is safety: only milligrams of highly toxic and active material need to be present in the fusion chamber, whereas blanket burnup requires the continued presence of tons of actinides in a small volume. The actinide data tables required for Monte Carlo calculations of the burnup of 241 Am and 243 Am are discussed in connection with typical burnup reactor fusion and fission spectra. 2 figures

  16. International bulletin on atomic and molecular data for fusion. No. 17

    International Nuclear Information System (INIS)

    Katsonis, K.; Langley, R.A.

    1981-11-01

    This bulletin deals with atomic and molecular data for fusion. A bibliography for the most recent data presented in the document is provided. Work in progress is briefly reported: Electron ionization cross sections for light elements, single electron capture by highly charged ions colliding with hydrogen, inconel 626 surface exfoliation, cavities in nickel induced by helium ion irradiation, electron impact excitation of hydrogenic ions. The bulletin contains a list of references for the publications on controlled fusion and plasma physics for 1980 and 1981

  17. Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Kouri, Tina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.

  18. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-12-16

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

  19. IAEA workshop on 'Atomic and molecular data for fusion energy research'. Summary report

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2004-05-01

    On September 8-12 a workshop on Atomic and Molecular (A+M) Data for Fusion Energy Research was hosted by the International Centre for Theoretical Physics in Trieste Italy. The workshop was attended by twelve students representing eleven Member States. A total of five lecturers, including four external to the Agency, made presentations to the workshop. All lecturers provided advance copies of the lecture materials and all provided written assignments for the students, to provide practical examples of applications of data issues to actual problems related to fusion energy research. All materials were collected on CDs, which were distributed to the students by the conclusion of the workshop. During the course of the workshop the students were given the opportunity to describe their backgrounds and research interests. The workshop did arouse interest in A+M processes related to fusion. The workshop was viewed as successful by the students. (author)

  20. Summary report of IAEA workshop on atomic and molecular data for fusion energy research

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2007-02-01

    A workshop on Atomic and Molecular (A+M) Data for Fusion Energy Research was held at the International Centre for Theoretical Physics (ICTP) in Trieste, Italy, from 28 August until 8 September 2006. The workshop was attended by fourteen students and three ICTP associates representing eleven Member States. A total of eight lecturers, including six external to the Agency, made presentations to the workshop. All lecturers provided advance copies of the lecture materials, and provided written assignments for the students to provide practical examples of applications of data issues to actual problems related to fusion energy research. All materials were collected on CDs, which were distributed to the students at the conclusion of the workshop. During the course of the workshop, the students were given the opportunity to describe their background and research interests. The workshop did arouse interest in A+M processes related to fusion, and was viewed as successful by both the students and lecturers. (author)

  1. Flexible and Scalable Data Fusion using Proactive, Schemaless Information Services

    Energy Technology Data Exchange (ETDEWEB)

    Widener, Patrick M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Scalable System Software Dept.

    2014-05-01

    Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once-read- never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are

  2. Flexible and Scalable Data Fusion using Proactive Schemaless Information Services

    Energy Technology Data Exchange (ETDEWEB)

    Widener, Patrick [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-05-01

    Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once- read-never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are

  3. Visualization of multi-INT fusion data using Java Viewer (JVIEW)

    Science.gov (United States)

    Blasch, Erik; Aved, Alex; Nagy, James; Scott, Stephen

    2014-05-01

    Visualization is important for multi-intelligence fusion and we demonstrate issues for presenting physics-derived (i.e., hard) and human-derived (i.e., soft) fusion results. Physics-derived solutions (e.g., imagery) typically involve sensor measurements that are objective, while human-derived (e.g., text) typically involve language processing. Both results can be geographically displayed for user-machine fusion. Attributes of an effective and efficient display are not well understood, so we demonstrate issues and results for filtering, correlation, and association of data for users - be they operators or analysts. Operators require near-real time solutions while analysts have the opportunities of non-real time solutions for forensic analysis. In a use case, we demonstrate examples using the JVIEW concept that has been applied to piloting, space situation awareness, and cyber analysis. Using the open-source JVIEW software, we showcase a big data solution for multi-intelligence fusion application for context-enhanced information fusion.

  4. Electron beam fusion data acquisition program DATAIN (EBD)

    International Nuclear Information System (INIS)

    Boyer, W.B.

    1977-02-01

    This report describes the e beam automatic data acquisition program DATAIN. The program was written for a Modular Computer Systems Modcomp II computer interfaced to Tektronix R7912 Transient Digitizers. Operator Communications and data handling steps are described

  5. Data acquisition system for fusion diagnostics on the ARGUS laser

    International Nuclear Information System (INIS)

    Greenwood, J.R.; Campbell, D.E.; Frerking, C.E.

    1976-09-01

    An extensive data acquisition and analysis system has been implemented for experiments on the ARGUS laser. The system is based upon a PDP-11/40 minicomputer and CAMAC interfaces. Highspeed transient digitizers, calorimeter digitizing modules and time integrated data are interfaced through CAMAC over a fiber optic serial highway. The system allows for dynamic definition of the experimental environment by an operator, automatic data acquisition during a shot. Two interactive graphics terminals allow experimenters real-time access to target shot data

  6. Statistical methods of combining information: Applications to sensor data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Burr, T.

    1996-12-31

    This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.

  7. Integrating Crowdsourced Data with a Land Cover Product: A Bayesian Data Fusion Approach

    Directory of Open Access Journals (Sweden)

    Sarah Gengler

    2016-06-01

    Full Text Available For many environmental applications, an accurate spatial mapping of land cover is a major concern. Currently, land cover products derived from satellite data are expected to offer a fast and inexpensive way of mapping large areas. However, the quality of these products may also largely depend on the area under study. As a result, it is common that various products disagree with each other, and the assessment of their respective quality still relies on ground validation datasets. Recently, crowdsourced data have been suggested as an alternate source of information that might help overcome this problem. However, crowdsourced data still remain largely discarded in scientific studies due to their inherent poor quality assurance. The aim of this paper is to present an efficient methodology that allows the user to code information brought by crowdsourced data even if no prior quality estimation is at hand and possibly to fuse this information with existing land cover products in order to improve their accuracy. It is first suggested that information brought by volunteers can be coded as a set of inequality constraints about the probabilities of the various land use classes at the visited places. This in turn allows estimating optimal probabilities based on a maximum entropy principle and to proceed afterwards with a spatial interpolation of these volunteers’ information. Finally, a Bayesian data fusion approach can be used for fusing multiple volunteers’ contributions with a remotely-sensed land cover product. This methodology is illustrated in this paper by focusing on the mapping of croplands in Ethiopia, where the aim is to improve the mapping of cropland as coming out from a land cover product with mitigated performances. It is shown how crowdsourced information can seriously improve the quality of the final product. The corresponding results also suggest that a prior assessing of remotely-sensed data quality can seriously improve the benefit

  8. Space-Time Data fusion for Remote Sensing Applications

    Science.gov (United States)

    Braverman, Amy; Nguyen, H.; Cressie, N.

    2011-01-01

    NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

  9. A Markov game theoretic data fusion approach for cyber situational awareness

    Science.gov (United States)

    Shen, Dan; Chen, Genshe; Cruz, Jose B., Jr.; Haynes, Leonard; Kruger, Martin; Blasch, Erik

    2007-04-01

    This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors (IPSs) are fed into the data refinement (Level 0) and object assessment (L1) data fusion components. High-level situation/threat assessment (L2/L3) data fusion based on Markov game model and Hierarchical Entity Aggregation (HEA) are proposed to refine the primitive prediction generated by adaptive feature/pattern recognition and capture new unknown features. A Markov (Stochastic) game method is used to estimate the belief of each possible cyber attack pattern. Game theory captures the nature of cyber conflicts: determination of the attacking-force strategies is tightly coupled to determination of the defense-force strategies and vice versa. Also, Markov game theory deals with uncertainty and incompleteness of available information. A software tool is developed to demonstrate the performance of the high level information fusion for cyber network defense situation and a simulation example shows the enhanced understating of cyber-network defense.

  10. Data fusion methodologies for food and beverage authentication and quality assessment – A review

    International Nuclear Information System (INIS)

    Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Busto, Olga

    2015-01-01

    The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment. - Highlights: • Multivariate data fusion is used in food authentication and quality assessment. • Data fusion approaches and their applications are reviewed. • Data preprocessing, variable selection and feature extraction are considered. • Model selection and validation are also considered.

  11. Data fusion methodologies for food and beverage authentication and quality assessment – A review

    Energy Technology Data Exchange (ETDEWEB)

    Borràs, Eva [iSens Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona (Spain); Ferré, Joan, E-mail: joan.ferre@urv.cat [Chemometrics, Qualimetrics and Nanosensors Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona (Spain); Boqué, Ricard [Chemometrics, Qualimetrics and Nanosensors Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona (Spain); Mestres, Montserrat; Aceña, Laura; Busto, Olga [iSens Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona (Spain)

    2015-09-03

    The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment. - Highlights: • Multivariate data fusion is used in food authentication and quality assessment. • Data fusion approaches and their applications are reviewed. • Data preprocessing, variable selection and feature extraction are considered. • Model selection and validation are also considered.

  12. Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

    Science.gov (United States)

    Rababaah, Haroun; Shirkhodaie, Amir

    2009-04-01

    The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

  13. The fusion of satellite and UAV data: simulation of high spatial resolution band

    Science.gov (United States)

    Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

    2017-10-01

    Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

  14. A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization

    Directory of Open Access Journals (Sweden)

    Minxiang Liu

    2013-01-01

    Full Text Available We present a novel feature-level data fusion method for autonomous localization in an inactive multiple reference unknown indoor environment. Since monocular sensors cannot provide the depth information directly, the proposed method incorporates the edge information of images from a camera with homologous depth information received from an infrared sensor. Real-time experimental results demonstrate that the accuracies of position and orientation are greatly improved by using the proposed fusion method in an unknown complex indoor environment. Compared to monocular localization, the proposed method is found to have up to 70 percent improvement in accuracy.

  15. 1988 failure rate screening data for fusion reliability and risk analysis

    International Nuclear Information System (INIS)

    Cadwallader, L.C.; Piet, S.J.

    1988-01-01

    This document contains failure rate screening data for application to fusion components. The screening values are generally fission or aerospace industry failure rate estimates that can be extrapolated for use by fusion system designers, reliability engineers and risk analysts. Failure rate estimates for tritium-bearing systems, liquid metal-cooled systems, gas-cooled systems, water-cooled systems and containment systems are given. Preliminary system availability estimates and selected initiating event frequency estimates are presented. This first edition document is valuable to design and safety analysis for the Compact Ignition Tokamak and the International Thermonuclear Experimental Reactor. 20 refs., 28 tabs

  16. Magnetic-fusion data acquisition at Los Alamos

    International Nuclear Information System (INIS)

    Wilkins, R.W.; Klare, K.A.

    1986-01-01

    The authors discuss the use of a single software program to acquire data from hundreds of CAMAC recorders. For the past five years, this program has been used in all of their experiments, both manual and computer controlled. A variety of signals are stored on transient digitizers and other memories. The computer retrieves the data and applies an efficient compression algorithm before storing it on disk. The physicist can plan the next shot from the acquired data even as the rest is read. The readout is list-directed with device, amplifier, and time base types and their settings selected by the physicist. A new experiment may be set up in minutes

  17. Magnetic-fusion data acquisition at Los Alamos

    International Nuclear Information System (INIS)

    Wilkins, R.W.; Klare, K.A.

    1986-01-01

    The Controlled Thermonuclear Research (CTR) division uses a single software package to acquire data from hundreds of CAMAC recorders. For the past five years, this package has been used by all experiments, both manual and computer controlled. A variety of signals are stored in transient digitizers and other memories. The computer retrieves the data and applies an efficient compression algorithm before storing it on disk. The physicist can plan his next shot from the acquired data even as the rest is read. The readout is list directed with device, amplifier, and time-base types and their settings selected by the physicist. A new experiment may be set up in minutes

  18. Magnetic-fusion data acquisition at Los Alamos

    International Nuclear Information System (INIS)

    Wilkins, R.W.; Klare, K.A.

    1986-01-01

    The CTR division uses a single software package to acquire data from hundreds of CAMAC recorders. For the past five years, this package has been used by all experiments, both manual and computer controlled. A variety of signals are stored in transient digitizers and other memories. The computer retrieves the data and applies an efficient compression algorithm before storing it on disk. The physicist can plan his next shot from the acquired data even as the rest is read. The readout is list-directed with device, amplifier, and time base types and their settings selected by the physicist. A new experiment may be set up in minutes

  19. The Fusion Evaluated Nuclear Data Library (FENDL). Summary Report of an IAEA Consultants’ Meeting

    International Nuclear Information System (INIS)

    Fleming, Michael; Trkov, Andrej

    2016-08-01

    The Consultants’ Meeting on the Fusion Evaluated Nuclear Data Library (FENDL) was held at the IAEA Headquarters in Vienna from 1 to 4 August 2016. A summary of the presentations, discussions, actions and strategies for the future library versions and distributions are provided in this report. (author)

  20. International bulletin on atomic and molecular data for fusion. No. 40

    International Nuclear Information System (INIS)

    Smith, J.J.

    1990-03-01

    Indexed papers relating to structure and spectra, atomic and molecular collisions, and surface interactions relevant to nuclear fusion are given. Included is the bibliography for all indexed papers. In addition, a list of evaluated numerical atomic databases stored in the IAEA data bank is given

  1. Fusion of Color and Depth Camera Data for Robust Fall Detection

    NARCIS (Netherlands)

    Josemans, W.; Englebienne, G.; Kröse, B.; Battiato, S.; Braz, J.

    2013-01-01

    The availability of cheap imaging sensors makes it possible to increase the robustness of vision-based alarm systems. This paper explores the benefit of data fusion in the application of fall detection. Falls are a common source of injury for elderly people and automatic fall detection is,

  2. Preparation of processed nuclear data libraries for thermal, fast and fusion research and power reactor applications

    International Nuclear Information System (INIS)

    Ganesan, S.

    1994-03-01

    A Consultants Meeting on ''Preparation of Processed Nuclear Data Libraries for Thermal, Fast and Fusion Research and Power Reactor Applications'' was convened by the International Atomic Energy Agency and held during December 13-16, 1993 December 8-10, 1993 at the IAEA Headquarters, Vienna. The detailed agenda, the complete list of participants and the recommendations are presented in this report. (author)

  3. Anomaly Detection for Resilient Control Systems Using Fuzzy-Neural Data Fusion Engine

    Energy Technology Data Exchange (ETDEWEB)

    Ondrej Linda; Milos Manic; Timothy R. McJunkin

    2011-08-01

    Resilient control systems in critical infrastructures require increased cyber-security and state-awareness. One of the necessary conditions for achieving the desired high level of resiliency is timely reporting and understanding of the status and behavioral trends of the control system. This paper describes the design and development of a neural-network based data-fusion system for increased state-awareness of resilient control systems. The proposed system consists of a dedicated data-fusion engine for each component of the control system. Each data-fusion engine implements three-layered alarm system consisting of: (1) conventional threshold-based alarms, (2) anomalous behavior detector using self-organizing maps, and (3) prediction error based alarms using neural network based signal forecasting. The proposed system was integrated with a model of the Idaho National Laboratory Hytest facility, which is a testing facility for hybrid energy systems. Experimental results demonstrate that the implemented data fusion system provides timely plant performance monitoring and cyber-state reporting.

  4. A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

    Science.gov (United States)

    Turso, James A.; Litt, Jonathan S.

    2004-01-01

    A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

  5. Semantic intrusion detection with multisensor data fusion using ...

    Indian Academy of Sciences (India)

    spatiotemporal relations to form complex events which model the intrusion patterns. ... Wireless sensor networks; complex event processing; event stream; ...... of the 2006 ACM SIGMOD International Conference on Management of Data, 407– ...

  6. Function and Phenotype prediction through Data and Knowledge Fusion

    KAUST Repository

    Vespoor, Karen

    2016-01-01

    I will introduce the use of text mining techniques to support analysis of biological data sets, and will specifically discuss applications in protein function and phenotype prediction, as well as analysis of genetic variants that are supported

  7. Bathymetry from fusion of airborne hyperspectral and laser data

    Science.gov (United States)

    Kappus, Mary E.; Davis, Curtiss O.; Rhea, W. Joseph

    1998-10-01

    Airborne hyperspectral and nadir-viewing laser data can be combined to ascertain shallow water bathymetry. The combination emphasizes the advances and overcomes the disadvantages of each method used alone. For laser systems, both the hardware and software for obtaining off-nadir measurement are complicated and expensive, while for the nadir view the conversion of laser pulse travel time to depth is straightforward. The hyperspectral systems can easily collect data in a full swath, but interpretation for water depth requires careful calibration and correction for transmittance through the atmosphere and water. Relative depths are apparent in displays of several subsets of hyperspectral data, for example, single blue-green wavelengths, endmembers that represent the pure water component of the data, or ratios of deep to shallow water endmembers. A relationship between one of these values and the depth measured by the aligned nadir laser can be determined, and then applied to the rest of the swath to obtain depth in physical units for the entire area covered. We demonstrate this technique using bathymetric charts as a proxy for laser data, and hyperspectral data taken by AVIRIS over Lake Tahoe and Key West.

  8. A Standard Data Access Layer for Fusion Devices

    International Nuclear Information System (INIS)

    Neto, A.; Fernandes, H.; Valcarcel, D.; Varandas, C.; Vega, J.; Sanchez, E.; Pena, A.; Hron, M.

    2006-01-01

    Each EURATOM association stores data using proprietary schemes, usually developed by the research unit or using third party software. The temporary exchange of researchers between laboratories is a common practice nowadays. When the researchers returns to the home laboratory, usually there is the need to continue to follow the work started in the foreign country. The quantity of available data has also become enormous and the principal data index is changing from the shot number to time and events, where the shot number is just one of the most relevant. To solve these problems a common software layer between end-users and laboratories must exist. The components needed to create this software abstraction layer, between users and laboratories data, have already been developed using an universal and well known remote procedure call standard based on XML: XML-RPC. The library allows data retrieving using the same methods for all associations. Users are authenticated through the PAPI system (http://papi.rediris.es), allowing each organization to use its own authentication schema. Presently there are libraries and server implementations in Java and C++. These libraries have been included and tested in some of the most common data analysis programs like MatLab and IDL. The system is already being used in ISTTOK/PT and CASTOR/CZ. (author)

  9. International bulletin on atomic and molecular data for fusion. No. 48

    International Nuclear Information System (INIS)

    1994-10-01

    This bulletin provides atomic and molecular data references relevant to thermonuclear fusion research and technology. In part I the indexing of the papers is given separately for (i) structure and spectra (energy levels, wavelengths; transition probabilities, oscillator strengths; interatomic potentials), (ii) atomic and molecular collisions (photon collisions, electron collisions, heavy particle collisions), and (iii) surface interactions (sputtering, surface damage, blistering, flaking, arcing, chemical reactions). Part II contains the bibliographic data for the above listed topics and for plasma composition and impurities, plasma heating, cooling and fuelling, high energy laser- and beam- matter interaction, bibliographic and numerical data collections, and on interaction of atomic particles with fields. Also included are sections on atomic and molecular data needs for fusion research and on news about ALADDIN (A Labelled Atomic Data Interface) and evaluated-data bases

  10. A Big Network Traffic Data Fusion Approach Based on Fisher and Deep Auto-Encoder

    Directory of Open Access Journals (Sweden)

    Xiaoling Tao

    2016-03-01

    Full Text Available Data fusion is usually performed prior to classification in order to reduce the input space. These dimensionality reduction techniques help to decline the complexity of the classification model and thus improve the classification performance. The traditional supervised methods demand labeled samples, and the current network traffic data mostly is not labeled. Thereby, better learners will be built by using both labeled and unlabeled data, than using each one alone. In this paper, a novel network traffic data fusion approach based on Fisher and deep auto-encoder (DFA-F-DAE is proposed to reduce the data dimensions and the complexity of computation. The experimental results show that the DFA-F-DAE improves the generalization ability of the three classification algorithms (J48, back propagation neural network (BPNN, and support vector machine (SVM by data dimensionality reduction. We found that the DFA-F-DAE remarkably improves the efficiency of big network traffic classification.

  11. IAEA advisory group meeting on atomic and molecular data for fusion, Culham Laboratory, UK, 1 - 5 November 1976

    International Nuclear Information System (INIS)

    Lorenz, A.

    1977-02-01

    The IAEA Nuclear Data Section convened an Advisory Group Meeting on Atomic and Molecular Data for Fusion at the UKAEA Laboratory at Culham, from 1-5 November 1976. Three detailed working group reports identifying requirements and availability of atomic collision data, atomic structure data, and surface interaction data in fusion research are presented. The meeting recommended the formation of an international network of data centres for the compilation and dissemination of atomic and molecular data required for fusion, and recommended that the IAEA Nuclear Data Section be given the responsibility to establish and coordinate this network

  12. A New Developed GIHS-BT-SFIM Fusion Method Based On Edge and Class Data

    Directory of Open Access Journals (Sweden)

    S. Dehnavi

    2013-09-01

    Full Text Available The objective of image fusion (or sometimes pan sharpening is to produce a single image containing the best aspects of the source images. Some desirable aspects are high spatial resolution and high spectral resolution. With the development of space borne imaging sensors, a unified image fusion approach suitable for all employed imaging sources becomes necessary. Among various image fusion methods, intensity-hue-saturation (IHS and Brovey Transforms (BT can quickly merge huge amounts of imagery. However they often face color distortion problems with fused images. The SFIM fusion is one of the most frequently employed approaches in practice to control the tradeoff between the spatial and spectral information. In addition it preserves more spectral information but suffer more spatial information loss. Its effectiveness is heavily depends on the filter design. In this work, two modifications were tested to improve the spectral quality of the images and also investigating class-based fusion results. First, a Generalized Intensity-Hue-Saturation (GIHS, Brovey Transform (BT and smoothing-filter based intensity modulation (SFIM approach was implemented. This kind of algorithm has shown computational advantages among other fusion methods like wavelet, and can be extended to different number of bands as in literature discussed. The used IHS-BT-SFIM algorithm incorporates IHS, IHS-BT, BT, BT-SFIM and SFIM methods by two adjustable parameters. Second, a method was proposed to plus edge information in previous GIHS_BT_SFIM and edge enhancement by panchromatic image. Adding panchromatic data to images had no much improvement. Third, an edge adaptive GIHS_BT_SFIM was proposed to enforce fidelity away from the edges. Using MS image off edges has shown spectral improvement in some fusion methods. Fourth, a class based fusion was tested, which tests different coefficients for each method due to its class. The best parameters for vegetated areas was k1 = 0.6, k2

  13. Data Fusion: A decision analysis tool that quantifies geological and parametric uncertainty

    International Nuclear Information System (INIS)

    Porter, D.W.

    1995-01-01

    Engineering projects such as siting waste facilities and performing remediation are often driven by geological and hydrogeological uncertainties. Geological understanding and hydrogeological parameters such as hydraulic conductivity are needed to achieve reliable engineering design. Information form non-invasive and minimal invasive data sets offers potential for reduction in uncertainty, but a single data type does not usually meet all needs. Data Fusion uses Bayesian statistics to update prior knowledge with information from diverse data sets as the data is acquired. Prior knowledge takes the form of first principles models (e.g., groundwater flow) and spatial continuity models for heterogeneous properties. The variability of heterogeneous properties is modeled in a form motivated by statistical physics as a Markov random field. A computer reconstruction of targets of interest is produced within a quantified statistical uncertainty. The computed uncertainty provides a rational basis for identifying data gaps for assessing data worth to optimize data acquisition. Further, the computed uncertainty provides a way to determine the confidence of achieving adequate safety, margins in engineering design. Beyond design, Data Fusion provides the basis for real time computer monitoring of remediation. Working with the DOE Office of Technology (OTD), the authors have developed and patented a Data Fusion Workstation system that has been used on jobs at the Hanford, Savannah River, Pantex and Fernald DOE sites. Further, applications include an army depot at Letterkenney, PA and commercial industrial sites

  14. Data Fusion: A decision analysis tool that quantifies geological and parametric uncertainty

    International Nuclear Information System (INIS)

    Porter, D.W.

    1996-01-01

    Engineering projects such as siting waste facilities and performing remediation are often driven by geological and hydrogeological uncertainties. Geological understanding and hydrogeological parameters such as hydraulic conductivity are needed to achieve reliable engineering design. Information from non-invasive and minimally invasive data sets offers potential for reduction in uncertainty, but a single data type does not usually meet all needs. Data Fusion uses Bayesian statistics to update prior knowledge with information from diverse data sets as the data is acquired. Prior knowledge takes the form of first principles models (e.g., groundwater flow) and spatial continuity models for heterogeneous properties. The variability of heterogeneous properties is modeled in a form motivated by statistical physics as a Markov random field. A computer reconstruction of targets of interest is produced within a quantified statistical uncertainty. The computed uncertainty provides a rational basis for identifying data gaps for assessing data worth to optimize data acquisition. Further, the computed uncertainty provides a way to determine the confidence of achieving adequate safety margins in engineering design. Beyond design, Data Fusion provides the basis for real time computer monitoring of remediation. Working with the DOE Office of Technology (OTD), the author has developed and patented a Data Fusion Workstation system that has been used on jobs at the Hanford, Savannah River, Pantex and Fernald DOE sites. Further applications include an army depot at Letterkenney, PA and commercial industrial sites

  15. On the increase of predictive performance with high-level data fusion

    International Nuclear Information System (INIS)

    Doeswijk, T.G.; Smilde, A.K.; Hageman, J.A.; Westerhuis, J.A.; Eeuwijk, F.A. van

    2011-01-01

    The combination of the different data sources for classification purposes, also called data fusion, can be done at different levels: low-level, i.e. concatenating data matrices, medium-level, i.e. concatenating data matrices after feature selection and high-level, i.e. combining model outputs. In this paper the predictive performance of high-level data fusion is investigated. Partial least squares is used on each of the data sets and dummy variables representing the classes are used as response variables. Based on the estimated responses y-hat j for data set j and class k, a Gaussian distribution p(g k |y-hat j ) is fitted. A simulation study is performed that shows the theoretical performance of high-level data fusion for two classes and two data sets. Within group correlations of the predicted responses of the two models and differences between the predictive ability of each of the separate models and the fused models are studied. Results show that the error rate is always less than or equal to the best performing subset and can theoretically approach zero. Negative within group correlations always improve the predictive performance. However, if the data sets have a joint basis, as with metabolomics data, this is not likely to happen. For equally performing individual classifiers the best results are expected for small within group correlations. Fusion of a non-predictive classifier with a classifier that exhibits discriminative ability lead to increased predictive performance if the within group correlations are strong. An example with real life data shows the applicability of the simulation results.

  16. International bulletin on atomic and molecular data for fusion. No. 64. October 2005

    International Nuclear Information System (INIS)

    Humbert, D.; Bannister, M.E.; Bretagne, J.; Fuhr, J.

    2005-10-01

    This bulletin comprises updated atomic and molecular data for fusion. It contains four parts. In part one the Atomic and Molecular Data Information System (AMDIS) of the IAEA is presented. In part two, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface interactions. Part three contains the bibliographic data for both indexed and and non-indexed references. The author index (part four) refers to the bibliographic references contained in part three

  17. A Scenario to Provide Atomic Data for Fusion Research in the Stage of Precision Physics

    International Nuclear Information System (INIS)

    Li Jiaming; Gao Xiang; Cheng Cheng; Zhang Xiaole; Qing Bo

    2010-01-01

    In order to provide abundant atomic data for fusion research in the stage of precision physics, a scenario, being a combination of indispensable theoretical calculations and bench-mark experimental measurements, is proposed. Such abundant atomic data are compiled mainly by theoretical calculations. Accuracies of such abundant data (i.e., atomic energy levels and corresponding cross sections) are ascertained only by a finite number of bench-mark experimental measurements based on analytical calculation of scattering matrices.

  18. International bulletin on atomic and molecular data for fusion. No. 63

    International Nuclear Information System (INIS)

    Humbert, D.; Bannister, M.E.; Bretagne, J.; Fuhr, J.

    2004-10-01

    This bulletin comprises updated atomic and molecular data for fusion. It contains four parts. In part one the Atomic and Molecular Data Information System (AMDIS) of the IAEA is presented. In part two, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface interactions. Part three contains the bibliographic data for both indexed and and non-indexed references. The author index (part four) refers to the bibliographic references contained in part three

  19. International bulletin on atomic and molecular data for fusion. No. 62. August 2003

    International Nuclear Information System (INIS)

    Humbert, D.; Bannister, M.E.; Delcroix, J.L.; Fuhr, J.

    2003-10-01

    This bulletin comprises updated atomic and molecular data for fusion. It contains four parts. In part one the Atomic and Molecular Data Information System (AMDIS) of the IAEA is presented. In part two, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface interactions. Part three contains the bibliographic data for both indexed and and non-indexed references. The author index (part four) refers to the bibliographic references contained in part three

  20. International bulletin on atomic and molecular data for fusion. No. 65. July 2006

    International Nuclear Information System (INIS)

    Humbert, D.; Bannister, M.E.; Bretagne, J.; Fuhr, J.

    2006-08-01

    This bulletin comprises updated atomic and molecular data for fusion. It contains four parts. In part one the Atomic and Molecular Data Information System (AMDIS) of the IAEA is presented. In part two, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions, and surface interactions. Part three contains the bibliographic data for both indexed and and non-indexed references. The author index (part four) refers to the bibliographic references contained in part three

  1. International bulletin on atomic and molecular data for fusion. No. 53

    International Nuclear Information System (INIS)

    Stephens, J.A.

    1997-11-01

    The International Bulletin on Atomic and Molecular Data for Fusion is presented in four parts: 1) The Atomic and Molecular Data Information System (AMDIS) of the IAEA; 2) the indexed papers listed separately for structure and spectra, atomic and molecular collisions, and surface interactions; 3) all bibliographic data for both the indexed and non-indexed references; 4) the Author Index refers to the bibliographic references contained in Part 3

  2. Consumer-oriented social data fusion: controlled learning in social environments, social advertising, and more

    Science.gov (United States)

    Grewe, L.

    2013-05-01

    This paper explores the current practices in social data fusion and analysis as it applies to consumer-oriented applications in a slew of areas including business, economics, politics, sciences, medicine, education and more. A categorization of these systems is proposed and contributions to each area are explored preceded by a discussion of some special issues related to social data and networks. From this work, future paths of consumer-based social data analysis research and current outstanding problems are discovered.

  3. Data Summarization in the Node by Parameters (DSNP): Local Data Fusion in an IoT Environment.

    Science.gov (United States)

    Maschi, Luis F C; Pinto, Alex S R; Meneguette, Rodolfo I; Baldassin, Alexandro

    2018-03-07

    With the advent of the Internet of Things, billions of objects or devices are inserted into the global computer network, generating and processing data at a volume never imagined before. This paper proposes a way to collect and process local data through a data fusion technology called summarization. The main feature of the proposal is the local data fusion, through parameters provided by the application, ensuring the quality of data collected by the sensor node. In the evaluation, the sensor node was compared when performing the data summary with another that performed a continuous recording of the collected data. Two sets of nodes were created, one with a sensor node that analyzed the luminosity of the room, which in this case obtained a reduction of 97% in the volume of data generated, and another set that analyzed the temperature of the room, obtaining a reduction of 80% in the data volume. Through these tests, it has been proven that the local data fusion at the node can be used to reduce the volume of data generated, consequently decreasing the volume of messages generated by IoT environments.

  4. Data Summarization in the Node by Parameters (DSNP: Local Data Fusion in an IoT Environment

    Directory of Open Access Journals (Sweden)

    Luis F. C. Maschi

    2018-03-01

    Full Text Available With the advent of the Internet of Things, billions of objects or devices are inserted into the global computer network, generating and processing data at a volume never imagined before. This paper proposes a way to collect and process local data through a data fusion technology called summarization. The main feature of the proposal is the local data fusion, through parameters provided by the application, ensuring the quality of data collected by the sensor node. In the evaluation, the sensor node was compared when performing the data summary with another that performed a continuous recording of the collected data. Two sets of nodes were created, one with a sensor node that analyzed the luminosity of the room, which in this case obtained a reduction of 97% in the volume of data generated, and another set that analyzed the temperature of the room, obtaining a reduction of 80% in the data volume. Through these tests, it has been proven that the local data fusion at the node can be used to reduce the volume of data generated, consequently decreasing the volume of messages generated by IoT environments.

  5. Mirror Fusion Test Facility data compression study. Final report

    International Nuclear Information System (INIS)

    1979-11-01

    This report is organized as follows. Discussions are given of three of the most important data compression methods that have been developed and studied over the years: coding, transforms, and redundancy reduction. (A brief discussion of how to combine and synthesize these ideas, and others, into a system is given). Specific ideas for compressing MFTF diagnostics and control data are developed. Listings and instructions for using FORTRAN programs that were compiled on the Livermore MFTF computers during the course of the study are also given

  6. Current status of fusion-relevant covariance data

    International Nuclear Information System (INIS)

    Muir, D.W.

    1994-01-01

    The following review of the current status of formatted data covariance files and their multigroup processing is a contribution to the IAEA Advisory Group Meeting on ''Improved Evaluations and Integral Data Testing for FENDL,'' to be held at the Max-Planck-Institut fuer Plasmaphysik, Garching, Germany, 12--16 September 1994. The draft agenda of this meeting lists as Item 6 the ''assessment of present status and role of uncertainty files, their processing and sensitivity studies related to FENDL.'' We conclude that this is an important and timely topic and recommend needed actions in this field

  7. Atomic and plasma-material interaction data for fusion. V. 14

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2008-01-01

    Plasmas in fusion energy devices consist of hot core plasmas with cooler regions near the edge. The temperatures are much lower in the edge region than in the core and there is a relatively high population of neutral species. Neutral and charged molecular species may form in this region and influence the plasma diagnostics. A variety of molecules, including species of hydrocarbons, form in the edge region, and hydrocarbon species up to C 3 H 8 may be produced. As the plasma interacts with the surface of the containment vessel, erosion from the surface will take place. There is then the potential for a number of chemical reactions to occur near the surface. A wide variety of interaction processes will take place involving these molecules in the edge region. It is not well known to what extent these processes affect the efficiency of the divertor itself. Thus there is a need to gather spectroscopic and collisional data to better understand the extent to which these processes are important in the edge regions, including data derived from infrared spectroscopy. The importance of these molecular processes to fusion research led to a strong recommendation from the A+M Subcommittee of the International Fusion Research Council at its twelfth meeting in May 2000 to initiate a coordinated research project (CRP) to address data needs in this area. The IAEA initiated the CRP on Data for Molecular Processes in Edge Plasmas in 2001. The purpose of the CRP was to identify the specific molecular processes that are important to the plasma physics in the edge region and to provide data for some of these processes. During the course of the CRP that concluded in 2005, new data have been generated for a variety of processes impacting a number of issues in the edge region of fusion plasmas. Essentially all the goals of the original work plan were fulfilled during the course of the CRP, with the generation of new theoretical and measured cross-sections for a variety of processes in

  8. A simple data fusion method for instantaneous travel time estimation

    NARCIS (Netherlands)

    Do, Michael; Pueboobpaphan, R.; Miska, Marc; Kuwahara, Masao; van Arem, Bart; Viegas, J.M.; Macario, R.

    2010-01-01

    Travel time is one of the most understandable parameters to describe traffic condition and an important input to many intelligent transportation systems applications. Direct measurement from Electronic Toll Collection (ETC) system is promising but the data arrives too late, only after the vehicles

  9. Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis

    International Nuclear Information System (INIS)

    Jesneck, Jonathan L.; Nolte, Loren W.; Baker, Jay A.; Floyd, Carey E.; Lo, Joseph Y.

    2006-01-01

    As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p<0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets

  10. Multisource Data Fusion Framework for Land Use/Land Cover Classification Using Machine Vision

    Directory of Open Access Journals (Sweden)

    Salman Qadri

    2017-01-01

    Full Text Available Data fusion is a powerful tool for the merging of multiple sources of information to produce a better output as compared to individual source. This study describes the data fusion of five land use/cover types, that is, bare land, fertile cultivated land, desert rangeland, green pasture, and Sutlej basin river land derived from remote sensing. A novel framework for multispectral and texture feature based data fusion is designed to identify the land use/land cover data types correctly. Multispectral data is obtained using a multispectral radiometer, while digital camera is used for image dataset. It has been observed that each image contained 229 texture features, while 30 optimized texture features data for each image has been obtained by joining together three features selection techniques, that is, Fisher, Probability of Error plus Average Correlation, and Mutual Information. This 30-optimized-texture-feature dataset is merged with five-spectral-feature dataset to build the fused dataset. A comparison is performed among texture, multispectral, and fused dataset using machine vision classifiers. It has been observed that fused dataset outperformed individually both datasets. The overall accuracy acquired using multilayer perceptron for texture data, multispectral data, and fused data was 96.67%, 97.60%, and 99.60%, respectively.

  11. Detailed benchmark test of JENDL-4.0 iron data for fusion applications

    Energy Technology Data Exchange (ETDEWEB)

    Konno, Chikara, E-mail: konno.chikara@jaea.go.jp [Japan Atomic Energy Agency, Tokai-Mura, Ibaraki-ken, 319-1195 (Japan); Wada, Masayuki [Japan Computer System, Mito, 310-0805 (Japan); Kondo, Keitaro; Ohnishi, Seiki; Takakura, Kosuke; Ochiai, Kentaro; Sato, Satoshi [Japan Atomic Energy Agency, Tokai-Mura, Ibaraki-ken, 319-1195 (Japan)

    2011-10-15

    The major revised version of Japanese Evaluated Nuclear Data Library (JENDL), JENDL-4.0, was released in May, 2010. As one of benchmark tests, we have carried out a benchmark test of JENDL-4.0 iron data, which are very important for radiation shielding in fusion reactors, by analyzing the iron fusion neutronics integral experiments (in situ and Time-of-Flight (TOF) experiments) at JAEA/FNS. It is demonstrated that the problems of the iron data in the previous version of JENDL, JENDL-3.3, are solved in JENDL-4.0; the first inelastic scattering cross section data of {sup 57}Fe and the angular distribution of the elastic scattering of {sup 56}Fe. The iron data in JENDL-4.0 are comparable to or are partly better than those in ENDF/B-VII.0 and JEFF-3.1.

  12. Bayesian tomography and integrated data analysis in fusion diagnostics

    Science.gov (United States)

    Li, Dong; Dong, Y. B.; Deng, Wei; Shi, Z. B.; Fu, B. Z.; Gao, J. M.; Wang, T. B.; Zhou, Yan; Liu, Yi; Yang, Q. W.; Duan, X. R.

    2016-11-01

    In this article, a Bayesian tomography method using non-stationary Gaussian process for a prior has been introduced. The Bayesian formalism allows quantities which bear uncertainty to be expressed in the probabilistic form so that the uncertainty of a final solution can be fully resolved from the confidence interval of a posterior probability. Moreover, a consistency check of that solution can be performed by checking whether the misfits between predicted and measured data are reasonably within an assumed data error. In particular, the accuracy of reconstructions is significantly improved by using the non-stationary Gaussian process that can adapt to the varying smoothness of emission distribution. The implementation of this method to a soft X-ray diagnostics on HL-2A has been used to explore relevant physics in equilibrium and MHD instability modes. This project is carried out within a large size inference framework, aiming at an integrated analysis of heterogeneous diagnostics.

  13. Maintenance Decision Making based on different types of data fusion

    OpenAIRE

    Galar, D.; Gustafson, A.; Tormos Martínez, Bernardo Vicente; Berges, Luis

    2012-01-01

    [EN] Over the last decade, system integration is applied more as it allows organizations to streamline business processes. A recent development in the asset engineering management is to leverage the investment already made in process control systems. This allows the operations, maintenance, and process control teams to monitor and determine new alarm level based on the physical condition data of the critical machines. Condition-based maintenance (CBM) is a maintenance philosophy base...

  14. Computer Aided Multi-Data Fusion Dismount Modeling

    Science.gov (United States)

    2012-03-22

    dependent on a particular environmental condition. They are costly, cumbersome, and involve dedicated software practices and particular knowledge to operate...allow manipulation of 2D matrices, like Microsoft Excel or Libre Office. The second alternative is to modify an already created model (MEM). The model... software . Therefore, with the described computer aided multi-data dismount model the researcher will be able to attach signatures to any desired

  15. Problems of lead nuclear data in fusion blanket design

    International Nuclear Information System (INIS)

    Kondo, Keitaro; Murata, Isao; Klix, Axel; Seidel, Klaus; Freiesleben, Hartwig

    2009-01-01

    In an irradiation experiment using a LiAl/Pb assembly, we found out that the neutron flux inside the assembly calculated with JENDL-3.3 underestimates an experimental value in the 10-16 MeV region by around 30% and that in the 0.5-5 MeV region by around 15%, while the calculated flux with JEFF-3.1 overestimates the measurement in the 5-10 MeV region by around 20%. In order to reveal a reason of the discrepancy, problems of the nuclear data libraries for lead were investigated. As a result, the following problems of the evaluated libraries were pointed out: the cross-sections of the (n,2n) reaction in JENDL-3.3 for lead isotopes are too large and cause a significant underestimation of the neutron flux above 10 MeV, which appeared in the analysis of the above experiment. Inelastic scattering data for 208 Pb in JENDL-3.3 reproduce previous experimental double-differential cross-section data most well. However, those for the other lead isotopes have some problems and cause a large underestimation of the neutron flux from 0.5 to 5 MeV. The reason of the overestimation in the energy region of 5-10 MeV with JEFF-3.1 is still unclear.

  16. Information-management data base for fusion-target fabrication processes

    International Nuclear Information System (INIS)

    Reynolds, J.

    1982-01-01

    A computer-based data-management system has been developed to handle data associated with target-fabrication processes including glass microballoon characterization, gas filling, materials coating, and storage locations. The system provides automatic data storage and computation, flexible data-entry procedures, fast access, automated report generation, and secure data transfer. It resides on a CDC CYBER 175 computer and is compatible with the CDC data-base-language Query Update, but is based on custom FORTRAN software interacting directly with the CYBER's file-management system. The described data base maintains detailed, accurate, and readily available records of fusion targets information

  17. Intelligent Data Fusion for Wide-Area Assessment of UXO Contamination. SERDP Project MM-1510. 2006 Annual Report

    National Research Council Canada - National Science Library

    Rose-Pehrsson, Susan L; Johnson, Kevin; Minor, Christian; Guthrie, Verner

    2007-01-01

    .... A data fusion framework will be created to provide a cohesive data management and decision-making utility that will capture all available data and more efficiently direct the expenditure of time, labor, and resources...

  18. Atomic and plasma-material interaction data for fusion. Vol. 13

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2007-01-01

    Plasmas generated in fusion energy research cover a wide range of conditions involving electron temperature, electron density and plasma constituents, as well as electric and magnetic fields. Performing diagnostics on such plasmas is a complex problem requiring many different types of atomic and molecular (A+M) data. The typical plasmas in fusion research naturally divide into a core region and an edge/divertor region, and the physical conditions differ significantly between these two regions. There is a need to use soft X-ray spectroscopy as well as optical spectroscopy for diagnostics in the core region. This requires information on the emission properties of the plasma under the core conditions. Information about several different processes for atomic species relevant to the plasma is needed in this process. Some data can be measured directly in experimental devices such as the electron beam ion trap (EBIT). This type of measurement would prove very useful in furthering databases for plasma diagnostics of core regions. Heating beams are used to raise the core temperature and doped beams are used for diagnostic purposes. Thus, beam spectroscopy is an important consideration in the core region. Radiation from impurities in the edge region is very important in understanding the formation of advanced discharge regimes (transport barriers). Temperatures are significantly lower in the edge/ divertor region and there is a relatively high population of neutral species. Molecules will also form in this region, requiring extensive data on a variety of molecular processes for diagnostic procedures. Processes such as charge exchange will also be important for diagnostic purposes in the edge - data needed for diagnostics include radiative as well as collision processes. Collision processes include both electron and heavy particle collisions. The importance of generating new data for support of diagnostics in fusion plasmas led to a strong recommendation at the 12th meeting

  19. Research in the field of neutronics and nuclear data for fusion

    International Nuclear Information System (INIS)

    Batistoni, P.

    2001-01-01

    A reliable and validated nuclear database is required for the design of a fusion reactor. Neutrons produced by the fusion reactions between deuterium and tritium have a very peaked energy spectrum at 14 MeV, requiring a substantial extrapolation with respect to the database made available from fission studies. The correct evaluation of shielding properties, damage, nuclear heating and of tritium breeding performance in the blanket surrounding the reaction chamber is crucial to the correct reactor design. Moreover, the attractiveness of fusion relies in the low activation of the reactor components and in the minimal production of long-term radioactive waste that is pursued with development of low activation materials. Beside the materials development, Europe is carrying out a co-ordinated program for the development of adequate nuclear database and numerical tools, directed to evaluations, processing, application, and benchmarking of cross sections including uncertainty information. Experimental validation of data and of the relative uncertainties is also pursued, both on material samples and on more design-oriented experiments. A general view of the research work in the field of neutronics and nuclear data for fusion will be given in the presentation, with emphasis to the experimental validation activity.(author)

  20. Radiation Shielding Information Center: a source of computer codes and data for fusion neutronics studies

    International Nuclear Information System (INIS)

    McGill, B.L.; Roussin, R.W.; Trubey, D.K.; Maskewitz, B.F.

    1980-01-01

    The Radiation Shielding Information Center (RSIC), established in 1962 to collect, package, analyze, and disseminate information, computer codes, and data in the area of radiation transport related to fission, is now being utilized to support fusion neutronics technology. The major activities include: (1) answering technical inquiries on radiation transport problems, (2) collecting, packaging, testing, and disseminating computing technology and data libraries, and (3) reviewing literature and operating a computer-based information retrieval system containing material pertinent to radiation transport analysis. The computer codes emphasize methods for solving the Boltzmann equation such as the discrete ordinates and Monte Carlo techniques, both of which are widely used in fusion neutronics. The data packages include multigroup coupled neutron-gamma-ray cross sections and kerma coefficients, other nuclear data, and radiation transport benchmark problem results

  1. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    Science.gov (United States)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1993-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  2. A Data Fusion System for the Nondestructive Evaluation of Non-Piggable Pipes

    Energy Technology Data Exchange (ETDEWEB)

    Shreekanth Mandayam; Robi Polikar; John C. Chen

    2006-02-01

    The objectives of this research project are: (1) To design sensor data fusion algorithms that can synergistically combine defect related information from heterogeneous sensors used in gas pipeline inspection for reliably and accurately predicting the condition of the pipe-wall; and (2) To develop efficient data management techniques for signals obtained during multisensor interrogation of a gas pipeline. This final report summarizes all research activities conducted by Rowan University during the project period. This includes the design and development of experimental validation test platforms, the design and development of data fusion algorithms for defect identification and sizing, and finally, the design and development of advanced visualization algorithms for the effective management of data resulting from multi-sensor interrogation of gas transmission pipelines.

  3. Function and Phenotype prediction through Data and Knowledge Fusion

    KAUST Repository

    Vespoor, Karen

    2016-01-27

    The biomedical literature captures the most current biomedical knowledge and is a tremendously rich resource for research. With over 24 million publications currently indexed in the US National Library of Medicine’s PubMed index, however, it is becoming increasingly challenging for biomedical researchers to keep up with this literature. Automated strategies for extracting information from it are required. Large-scale processing of the literature enables direct biomedical knowledge discovery. In this presentation, I will introduce the use of text mining techniques to support analysis of biological data sets, and will specifically discuss applications in protein function and phenotype prediction, as well as analysis of genetic variants that are supported by analysis of the literature and integration with complementary structured resources.

  4. International bulletin on atomic and molecular data for fusion. No. 46

    International Nuclear Information System (INIS)

    Botero, J.

    1993-06-01

    The bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In Part I the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths; transition probabilities, oscillator strengths; interatomic potentials); (ii) atomic and molecular collisions (photon collisions; electron collisions; heavy-particle collisions; homonuclear sequences; isoelectronic sequences), and (iii) surface interactions (sputtering; chemical reactions; trapping and detrapping; surface damage; blistering, flaking; secondary electron emission). Part II contains the bibliographic data for the above listed topics and for high energy laser- and beam-matter interaction; interaction of atomic particles with fields. The atomic and molecular data needs in fusion research, as identified during the IAEA Consultants' Meeting on 'Atomic and Molecular Database for Hydrogen Recycling and Helium Exhaust from Fusion Reactors', June 1992, Vienna, are listed, covering (i) atomic and molecular collision processes, (ii) particle-surface interaction processes, and (iii) the status of data bases on atomic and molecular data and plasma-surface interactions. News on the ALADDIN (A labelled Atomic Data INterface) system is provided. Finally, a list of evaluated atomic and molecular data bases is provided

  5. ChimerDB 3.0: an enhanced database for fusion genes from cancer transcriptome and literature data mining.

    Science.gov (United States)

    Lee, Myunggyo; Lee, Kyubum; Yu, Namhee; Jang, Insu; Choi, Ikjung; Kim, Pora; Jang, Ye Eun; Kim, Byounggun; Kim, Sunkyu; Lee, Byungwook; Kang, Jaewoo; Lee, Sanghyuk

    2017-01-04

    Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

    OpenAIRE

    Chaoyang Shi; Bi Yu Chen; William H. K. Lam; Qingquan Li

    2017-01-01

    Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are f...

  7. The use of proximal soil sensor data fusion and digital soil mapping for precision agriculture

    OpenAIRE

    Ji, Wenjun; Adamchuk, Viacheslav; Chen, Songchao; Biswas, Asim; Leclerc, Maxime; Viscarra Rossel, Raphael

    2017-01-01

    Proximal soil sensing (PSS) is a promising approach when it comes to detailed characterization of spatial soil heterogeneity. Since none of existing PSS systems can measure all soil information needed for implementation precision agriculture, sensor data fusion can provide a reasonable al- ternative to characterize the complexity of soils. In this study, we fused the data measured using a gamma-ray sensor, an apparent electrical conductivity (ECa) sensor, and a commercial Veris MS...

  8. International bulletin on atomic and molecular data for fusion. No. 61

    International Nuclear Information System (INIS)

    Stephens, J.A.; Bannister, M.E.; Delcroix, J.L.; Fuhr, J.

    2002-01-01

    This bulletin is prepared by the IAEA to assist in the development of fusion research and technology. In part 1 the Atomic and Molecular Data Information System (AMDIS) of the IAEA is presented. In part 2, the indexed papers are listed separately for structure and spectra, atomic and molecular collisions and surface interactions. Part 3 contains all the bibliographic data for both indexed and non-indexed references

  9. A DNA-based semantic fusion model for remote sensing data.

    Directory of Open Access Journals (Sweden)

    Heng Sun

    Full Text Available Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  10. A DNA-based semantic fusion model for remote sensing data.

    Science.gov (United States)

    Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

    2013-01-01

    Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  11. Conceptual requirements for large fusion experiment control, data, robotics, and management systems

    International Nuclear Information System (INIS)

    Gaudreau, M.P.J.; Sullivan, J.D.

    1987-05-01

    The conceptual system requirements for the control, data, robotics, and project management (CDRM) system for the next generation of fusion experiments are developed by drawing on the success of the Tara control and data system. The requirements are described in terms of an integrated but separable matrix of well-defined interfaces among the various systems and subsystems. The study stresses modularity, performance, cost effectiveness, and exportability

  12. Analyzing large data sets from XGC1 magnetic fusion simulations using apache spark

    Energy Technology Data Exchange (ETDEWEB)

    Churchill, R. Michael [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)

    2016-11-21

    Apache Spark is explored as a tool for analyzing large data sets from the magnetic fusion simulation code XGCI. Implementation details of Apache Spark on the NERSC Edison supercomputer are discussed, including binary file reading, and parameter setup. Here, an unsupervised machine learning algorithm, k-means clustering, is applied to XGCI particle distribution function data, showing that highly turbulent spatial regions do not have common coherent structures, but rather broad, ring-like structures in velocity space.

  13. Geometric and Colour Data Fusion for Outdoor 3D Models

    Directory of Open Access Journals (Sweden)

    Ricardo Chacón

    2012-05-01

    Full Text Available This paper deals with the generation of accurate, dense and coloured 3D models of outdoor scenarios from scanners. This is a challenging research field in which several problems still remain unsolved. In particular, the process of 3D model creation in outdoor scenes may be inefficient if the scene is digitalized under unsuitable technical (specific scanner on-board camera and environmental (rain, dampness, changing illumination conditions. We address our research towards the integration of images and range data to produce photorealistic models. Our proposal is based on decoupling the colour integration and geometry reconstruction stages, making them independent and controlled processes. This issue is approached from two different viewpoints. On the one hand, given a complete model (geometry plus texture, we propose a method to modify the original texture provided by the scanner on-board camera with the colour information extracted from external images taken at given moments and under specific environmental conditions. On the other hand, we propose an algorithm to directly assign external images onto the complete geometric model, thus avoiding tedious on-line calibration processes. We present the work conducted on two large Roman archaeological sites dating from the first century A.D., namely, the Theatre of Segobriga and the Fori Porticus of Emerita Augusta, both in Spain. The results obtained demonstrate that our approach could be useful in the digitalization and 3D modelling fields.

  14. DECISION LEVEL FUSION OF ORTHOPHOTO AND LIDAR DATA USING CONFUSION MATRIX INFORMATION FOR LNAD COVER CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Daneshtalab

    2017-09-01

    Full Text Available Automatic urban objects extraction from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Lidar data available today. The aim of this study is to propose a new approach for the integration of high-resolution aerial imagery and Lidar data to improve the accuracy of classification in the city complications. In the proposed method, first, the classification of each data is separately performed using Support Vector Machine algorithm. In this case, extracted Normalized Digital Surface Model (nDSM and pulse intensity are used in classification of LiDAR data, and three spectral visible bands (Red, Green, Blue are considered as feature vector for the orthoimage classification. Moreover, combining the extracted features of the image and Lidar data another classification is also performed using all the features. The outputs of these classifications are integrated in a decision level fusion system according to the their confusion matrices to find the final classification result. The proposed method was evaluated using an urban area of Zeebruges, Belgium. The obtained results represented several advantages of image fusion with respect to a single shot dataset. With the capabilities of the proposed decision level fusion method, most of the object extraction difficulties and uncertainty were decreased and, the overall accuracy and the kappa values were improved 7% and 10%, respectively.

  15. Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

    Science.gov (United States)

    Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

    2010-01-01

    Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P forests (R2 = 0.93, P forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

  16. Sensor data fusion for textured reconstruction and virtual representation of alpine scenes

    Science.gov (United States)

    Häufel, Gisela; Bulatov, Dimitri; Solbrig, Peter

    2017-10-01

    The concept of remote sensing is to provide information about a wide-range area without making physical contact with this area. If, additionally to satellite imagery, images and videos taken by drones provide a more up-to-date data at a higher resolution, or accurate vector data is downloadable from the Internet, one speaks of sensor data fusion. The concept of sensor data fusion is relevant for many applications, such as virtual tourism, automatic navigation, hazard assessment, etc. In this work, we describe sensor data fusion aiming to create a semantic 3D model of an extremely interesting yet challenging dataset: An alpine region in Southern Germany. A particular challenge of this work is that rock faces including overhangs are present in the input airborne laser point cloud. The proposed procedure for identification and reconstruction of overhangs from point clouds comprises four steps: Point cloud preparation, filtering out vegetation, mesh generation and texturing. Further object types are extracted in several interesting subsections of the dataset: Building models with textures from UAV (Unmanned Aerial Vehicle) videos, hills reconstructed as generic surfaces and textured by the orthophoto, individual trees detected by the watershed algorithm, as well as the vector data for roads retrieved from openly available shapefiles and GPS-device tracks. We pursue geo-specific reconstruction by assigning texture and width to roads of several pre-determined types and modeling isolated trees and rocks using commercial software. For visualization and simulation of the area, we have chosen the simulation system Virtual Battlespace 3 (VBS3). It becomes clear that the proposed concept of sensor data fusion allows a coarse reconstruction of a large scene and, at the same time, an accurate and up-to-date representation of its relevant subsections, in which simulation can take place.

  17. The ORNL Controlled Fusion Atomic Data Center: Overview of Activities 2011

    International Nuclear Information System (INIS)

    Schultz, D.R.

    2011-01-01

    The Controlled Fusion Atomic Data Center (CFADC) of the Oak Ridge National Laboratory continued operation aimed at collecting, evaluating, and disseminating atomic, molecular, and particle-surface interaction (AM and PSI) data needed by both the U.S. and international plasma science communities. This work has been carried out within an overarching atomic physics research group which produces much of the required data through an active experimental and theoretical science program. The production of an annotated bibliography of AM and PSI literature relevant to plasma science continues to be among the most important activities of the data center, forming the basis for the CFADC on-line bibliographic search engine and a significant part of the IAEA A+M Data Unit's 'International Bulletin on Atomic and Molecular Data for Fusion.' Also chief among the data center's activities are responses to specific data requests from the plasma science community, leading to either rapid feedback using existing data resources or long term data production projects, as well as participation in IAEA Coordinated Research Programs including recently 'Data for Surface Composition Dynamics Relevant to Erosion Processes' and 'Atomic and Molecular Data for Plasma Modeling.' Highlights of recent data production projects include the following: Experimental and theoretical data for inelastic electron-hydrocarbon reactions, large scale computational results for particle reflection from surfaces, measurements of chemical sputtering from carbon, inaugural experiments considering molecular ion collisions with neutral hydrogen, and expansion of the database of elastic and related transport cross sections calculated for intrinsic and extrinsic impurities in hydrogen plasmas. Progress is being hampered owing to news from the US Department of Energy that it plans to close out the program after a ramp down of funding in 2012, following a distinguished 52 year history of contributions to the US and

  18. International bulletin on atomic and molecular data for fusion. No. 42-45

    International Nuclear Information System (INIS)

    Botero, J.

    1991-01-01

    The bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In Part I the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths; transition probabilities, oscillator strengths; polarizabilities, electric moments; interatomic potentials); (ii) atomic and molecular collisions (photon collisions; electro collisions; heavy-particle collisions; homonuclear sequences), and (iii) surface interactions (sputtering; trapping, detrapping; adsorption, desorption; surface damage; blistering, flaking; chemical reactions). Part II contains the bibliographic data for the above listed topics and for plasma composition and impurities; plasma heating, cooling and fuelling; fusion research of general interest; high energy laser- and beam-matter interaction; interaction of atomic particles with fields. A list of evaluated data bases on atomic and molecular collisions and on particle-surface interactions is also given

  19. Data Fusion for a Vision-Radiological System: a Statistical Calibration Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip [University of Florida, Gainesville, FL 32611 (United States)

    2015-07-01

    Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data. (authors)

  20. Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication

    Energy Technology Data Exchange (ETDEWEB)

    Biancolillo, Alessandra; Bucci, Remo; Magrì, Antonio L.; Magrì, Andrea D.; Marini, Federico, E-mail: fmmonet@hotmail.com

    2014-04-01

    Highlights: • Characterization of beer samples by five different fingerprinting techniques. • Chemometric discriminant and class-modeling techniques used for their authentication. • Mid-level data fusion allowed correct classification of all samples. - Abstract: Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies – in particular, the mid-level one – to integrate the data from the different platforms allowed the correct classification of all the training and validation samples.

  1. Data Fusion for a Vision-Radiological System: a Statistical Calibration Algorithm

    International Nuclear Information System (INIS)

    Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip

    2015-01-01

    Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data. (authors)

  2. Nuclear data needs for neutron spectrum tailoring at International Fusion Materials Irradiation Facility (IFMIF)

    International Nuclear Information System (INIS)

    Sugimoto, Masayoshi

    2001-01-01

    International Fusion Materials Irradiation Facility (IFMIF) is a proposal of D-Li intense neutron source to cover all aspects of the fusion materials development in the framework of IEA collaboration. The new activity has been started to qualifying the important technical issues called Key Element technology Phase since 2000. Although the neutron spectrum can be adjusted by changing the incident beam energy, it is favorable to be carried out many irradiation tasks at the same time under the unique beam condition. For designing the tailored neutron spectrum, neutron nuclear data for the moderator-reflector materials up to 50 MeV are required. The data for estimating the induced radioactivity is also required to keep the radiation level low enough at maintenance time. The candidate materials and the required accuracy of nuclear data are summarized. (author)

  3. Nuclear data needs for neutron spectrum tailoring at International Fusion Materials Irradiation Facility (IFMIF)

    Energy Technology Data Exchange (ETDEWEB)

    Sugimoto, Masayoshi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-03-01

    International Fusion Materials Irradiation Facility (IFMIF) is a proposal of D-Li intense neutron source to cover all aspects of the fusion materials development in the framework of IEA collaboration. The new activity has been started to qualifying the important technical issues called Key Element technology Phase since 2000. Although the neutron spectrum can be adjusted by changing the incident beam energy, it is favorable to be carried out many irradiation tasks at the same time under the unique beam condition. For designing the tailored neutron spectrum, neutron nuclear data for the moderator-reflector materials up to 50 MeV are required. The data for estimating the induced radioactivity is also required to keep the radiation level low enough at maintenance time. The candidate materials and the required accuracy of nuclear data are summarized. (author)

  4. A Bayes-Maximum Entropy method for multi-sensor data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Beckerman, M.

    1991-01-01

    In this paper we introduce a Bayes-Maximum Entropy formalism for multi-sensor data fusion, and present an application of this methodology to the fusion of ultrasound and visual sensor data as acquired by a mobile robot. In our approach the principle of maximum entropy is applied to the construction of priors and likelihoods from the data. Distances between ultrasound and visual points of interest in a dual representation are used to define Gibbs likelihood distributions. Both one- and two-dimensional likelihoods are presented, and cast into a form which makes explicit their dependence upon the mean. The Bayesian posterior distributions are used to test a null hypothesis, and Maximum Entropy Maps used for navigation are updated using the resulting information from the dual representation. 14 refs., 9 figs.

  5. Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication

    International Nuclear Information System (INIS)

    Biancolillo, Alessandra; Bucci, Remo; Magrì, Antonio L.; Magrì, Andrea D.; Marini, Federico

    2014-01-01

    Highlights: • Characterization of beer samples by five different fingerprinting techniques. • Chemometric discriminant and class-modeling techniques used for their authentication. • Mid-level data fusion allowed correct classification of all samples. - Abstract: Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies – in particular, the mid-level one – to integrate the data from the different platforms allowed the correct classification of all the training and validation samples

  6. Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Shezhou Luo

    2015-12-01

    Full Text Available Accurate land cover classification information is a critical variable for many applications. This study presents a method to classify land cover using the fusion data of airborne discrete return LiDAR (Light Detection and Ranging and CASI (Compact Airborne Spectrographic Imager hyperspectral data. Four LiDAR-derived images (DTM, DSM, nDSM, and intensity and CASI data (48 bands with 1 m spatial resolution were spatially resampled to 2, 4, 8, 10, 20 and 30 m resolutions using the nearest neighbor resampling method. These data were thereafter fused using the layer stacking and principal components analysis (PCA methods. Land cover was classified by commonly used supervised classifications in remote sensing images, i.e., the support vector machine (SVM and maximum likelihood (MLC classifiers. Each classifier was applied to four types of datasets (at seven different spatial resolutions: (1 the layer stacking fusion data; (2 the PCA fusion data; (3 the LiDAR data alone; and (4 the CASI data alone. In this study, the land cover category was classified into seven classes, i.e., buildings, road, water bodies, forests, grassland, cropland and barren land. A total of 56 classification results were produced, and the classification accuracies were assessed and compared. The results show that the classification accuracies produced from two fused datasets were higher than that of the single LiDAR and CASI data at all seven spatial resolutions. Moreover, we find that the layer stacking method produced higher overall classification accuracies than the PCA fusion method using both the SVM and MLC classifiers. The highest classification accuracy obtained (OA = 97.8%, kappa = 0.964 using the SVM classifier on the layer stacking fusion data at 1 m spatial resolution. Compared with the best classification results of the CASI and LiDAR data alone, the overall classification accuracies improved by 9.1% and 19.6%, respectively. Our findings also demonstrated that the

  7. FENDL/A-2.0. Neutron activation cross section data library for fusion applications

    International Nuclear Information System (INIS)

    Pashchenko, A.B.; Wienke, H.; Kopecky, J.; Sublet, J.C. Sublet; Forrest, R.A.

    1997-01-01

    This document describes the contents of a comprehensive neutron cross section data library for 13,006 neutron activation reactions with 739 target nuclides from H (A=1,Z=1) to Cm (A=248,Z=96), in the incident energy range up to 20 MeV. FENDL/A-2 is a sublibrary of FENDL-2, the second revision of the evaluated nuclear data library for fusion applications. It is supplemented by a decay data library FENDL/D-2 in ENDF-6 format for 1867 nuclides. The data are available from the IAEA Nuclear Data Section online via INTERNET by FTP command, or on magnetic tape upon request. (author)

  8. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

    Directory of Open Access Journals (Sweden)

    Jesse S. Jin

    2010-10-01

    Full Text Available Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  9. Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond

    Science.gov (United States)

    Pietsch, Stephan

    2017-04-01

    Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

  10. The role of data fusion in predictive maintenance using digital twin

    Science.gov (United States)

    Liu, Zheng; Meyendorf, Norbert; Mrad, Nezih

    2018-04-01

    Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called "Digital Twin." The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

  11. Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

    Directory of Open Access Journals (Sweden)

    Hao Lv

    2016-09-01

    Full Text Available This paper investigated the feasibility for improved detection of human respiration using data fusion based on a multistatic ultra-wideband (UWB radar. UWB-radar-based respiration detection is an emerging technology that has great promise in practice. It can be applied to remotely sense the presence of a human target for through-wall surveillance, post-earthquake search and rescue, etc. In these applications, a human target’s position and posture are not known a priori. Uncertainty of the two factors results in a body orientation issue of UWB radar, namely the human target’s thorax is not always facing the radar. Thus, the radial component of the thorax motion due to respiration decreases and the respiratory motion response contained in UWB radar echoes is too weak to be detected. To cope with the issue, this paper used multisensory information provided by the multistatic UWB radar, which took the form of impulse radios and comprised one transmitting and four separated receiving antennas. An adaptive Kalman filtering algorithm was then designed to fuse the UWB echo data from all the receiving channels to detect the respiratory-motion response contained in those data. In the experiment, a volunteer’s respiration was correctly detected when he curled upon a camp bed behind a brick wall. Under the same scenario, the volunteer’s respiration was detected based on the radar’s single transmitting-receiving channels without data fusion using conventional algorithm, such as adaptive line enhancer and single-channel Kalman filtering. Moreover, performance of the data fusion algorithm was experimentally investigated with different channel combinations and antenna deployments. The experimental results show that the body orientation issue for human respiration detection via UWB radar can be dealt well with the multistatic UWB radar and the Kalman-filter-based data fusion, which can be applied to improve performance of UWB radar in real applications.

  12. UAV hyperspectral and lidar data and their fusion for arid and semi-arid land vegetation monitoring

    Science.gov (United States)

    We demonstrate a unique fusion of unmanned aerial vehicle (UAV) lidar and hyperspectral imagery for individual plant species identification and 3D characterization of the earth surface at sub-meter scales in southeastern Arizona, USA. We hypothesized that the fusion of the two different data sources...

  13. IAEA technical meeting: 13th meeting of the IFRC Subcommittee on Atomic and Molecular Data for Fusion. Summary report

    International Nuclear Information System (INIS)

    Clark, R.E.H.; Peacock, N.J.

    2002-11-01

    This report briefly describes the proceedings, conclusions and recommendations of the 13th Meeting of the Subcommittee on Atomic and Molecular Data for Fusion of the International Fusion Research Council held on 24-25 June, 2002 at the IAEA Headquarters in Vienna Austria. The report includes an Executive Summary of the Subcommittee from this Meeting. (author)

  14. Lesion classification using clinical and visual data fusion by multiple kernel learning

    Science.gov (United States)

    Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

    2014-03-01

    To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

  15. A data fusion approach for track monitoring from multiple in-service trains

    Science.gov (United States)

    Lederman, George; Chen, Siheng; Garrett, James H.; Kovačević, Jelena; Noh, Hae Young; Bielak, Jacobo

    2017-10-01

    We present a data fusion approach for enabling data-driven rail-infrastructure monitoring from multiple in-service trains. A number of researchers have proposed using vibration data collected from in-service trains as a low-cost method to monitor track geometry. The majority of this work has focused on developing novel features to extract information about the tracks from data produced by individual sensors on individual trains. We extend this work by presenting a technique to combine extracted features from multiple passes over the tracks from multiple sensors aboard multiple vehicles. There are a number of challenges in combining multiple data sources, like different relative position coordinates depending on the location of the sensor within the train. Furthermore, as the number of sensors increases, the likelihood that some will malfunction also increases. We use a two-step approach that first minimizes position offset errors through data alignment, then fuses the data with a novel adaptive Kalman filter that weights data according to its estimated reliability. We show the efficacy of this approach both through simulations and on a data-set collected from two instrumented trains operating over a one-year period. Combining data from numerous in-service trains allows for more continuous and more reliable data-driven monitoring than analyzing data from any one train alone; as the number of instrumented trains increases, the proposed fusion approach could facilitate track monitoring of entire rail-networks.

  16. Nuclear data for the production of radioisotopes in fusion materials irradiation facility

    International Nuclear Information System (INIS)

    Cheng, E.T.; Schenter, R.E.; Mann, F.M.; Ikeda, Y.

    1991-01-01

    The fusion materials irradiation facility (FMIF) is a neutron source generator that will produce a high-intensity 14-MeV neutron field for testing candidate fusion materials under reactor irradiation conditions. The construction of such a facility is one of the very important development stages toward realization of fusion energy as a practical energy source for electricity production. As a result of the high-intensity neutron field, 10 MW/m 2 or more equivalent neutron wall loading, and the relatively high-energy (10- to 20-MeV) neutrons, the FMIF, as future fusion reactors, also bears the potential capability of producing a significant quantity of radioisotopes. A study is being conducted to identify the potential capability of the FMIF to produce radioisotopes for medical and industrial applications. Two types of radioisotopes are involved: one is already available; the second might not be readily available using conventional production methods. For those radioisotopes that are not readily available, the FMIF could develop significant benefits for future generations as a result of the availability of such radioisotopes for medical or industrial applications. The current production of radioisotopes could help finance the operation of the FMIF for irradiating the candidate fusion materials; thus this concept is attractive. In any case, nuclear data are needed for calculating the neutron flux and spectrum in the FMIF and the potential production rates of these isotopes. In this paper, the authors report the result of a preliminary investigation on the production of 99 Mo, the parent radioisotope for 99m Tc

  17. Research on the use of data fusion technology to evaluate the state of electromechanical equipment

    Science.gov (United States)

    Lin, Lin

    2018-04-01

    Aiming at the problems of different testing information modes and the coexistence of quantitative and qualitative information in the state evaluation of electromechanical equipment, the paper proposes the use of data fusion technology to evaluate the state of electromechanical equipment. This paper introduces the state evaluation process of mechanical and electrical equipment in detail, uses the D-S evidence theory to fuse the decision-making layers of mechanical and electrical equipment state evaluation and carries out simulation tests. The simulation results show that it is feasible and effective to apply the data fusion technology to the state evaluation of the mechatronic equipment. After the multiple decision-making information provided by different evaluation methods are fused repeatedly and the useful information is extracted repeatedly, the fuzziness of judgment can be reduced and the state evaluation Credibility.

  18. Real-time data acquisition and processing platform for fusion experiments

    International Nuclear Information System (INIS)

    Ruiz, M.; Barrera, E.; Lopez, S.; Machon, D.; Vega, J.; Sanchez, E.

    2004-01-01

    This paper describes the features of the hardware and low-level software of the PXI real-time data acquisition and processing system developed for the TJ-II device located in the Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT) in Madrid. This system fulfills three objectives: (1) to increase processing capabilities of standard data acquisition systems by adding specific processing cards, (2) to acquire and process data in real time with a view to deployment on steady state fusion devices, and (3) to develop the data acquisition and processing applications using graphical languages like LabView

  19. Minutes of the second meeting of the Joint IFRC/INDC sub-committee on atomic and molecular data for fusion, Vienna, 14 May 1977

    International Nuclear Information System (INIS)

    Lorenz, A.; Seamon, R.E.

    1977-08-01

    In this paper the minutes of the second meeting of the Joint IFRC/INDC Subcommittee (International Fusion Research Committee - International Nuclear Data Committee) on Atomic and Molecular Data for Fusion are given

  20. Automatic calibration and signal switching system for the particle beam fusion research data acquisition facility

    Energy Technology Data Exchange (ETDEWEB)

    Boyer, W.B.

    1979-09-01

    This report describes both the hardware and software components of an automatic calibration and signal system (Autocal) for the data acquisition system for the Sandia particle beam fusion research accelerators Hydra, Proto I, and Proto II. The Autocal hardware consists of off-the-shelf commercial equipment. The various hardware components, special modifications and overall system configuration are described. Special software has been developed to support the Autocal hardware. Software operation and maintenance are described.

  1. Automatic calibration and signal switching system for the particle beam fusion research data acquisition facility

    International Nuclear Information System (INIS)

    Boyer, W.B.

    1979-09-01

    This report describes both the hardware and software components of an automatic calibration and signal system (Autocal) for the data acquisition system for the Sandia particle beam fusion research accelerators Hydra, Proto I, and Proto II. The Autocal hardware consists of off-the-shelf commercial equipment. The various hardware components, special modifications and overall system configuration are described. Special software has been developed to support the Autocal hardware. Software operation and maintenance are described

  2. SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

    Science.gov (United States)

    Kaplan, G.; Avdan, U.

    2018-04-01

    Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

  3. International bulletin on atomic and molecular data for fusion. No. 54-55

    International Nuclear Information System (INIS)

    Stephens, J.A.

    1998-12-01

    This bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In the first part the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths, transition probabilities, oscillator strengths, polarizabilities, electric moments, interatomic potentials), (ii) atomic and molecular collisions (photon collisions, electron collisions, heavy-particle collisions), and (iii) surface interactions (sputtering, chemical reactions, trapping and detrapping, adsorption, desorption, reflection, and secondary electron emission). There are also chapters with beam-matter interactions and data on interactions of atomic particles with fields. In the second Part contains the bibliographic data, essentially for the above listed topics

  4. Experimental validation of decay heat calculation codes and associated nuclear data libraries for fusion energy

    International Nuclear Information System (INIS)

    Maekawa, Fujio; Wada, Masayuki; Ikeda, Yujiro

    2001-01-01

    Validity of decay heat calculations for safety designs of fusion reactors was investigated by using decay heat experimental data on thirty-two fusion reactor relevant materials obtained at the 14-MeV neutron source facility of FNS in JAERI. Calculation codes developed in Japan, ACT4 and CINAC version 4, and nuclear data bases such as JENDL/Act-96, FENDL/A-2.0 and Lib90 were used for the calculation. Although several corrections in algorithms for both the calculation codes were needed, it was shown by comparing calculated results with the experimental data that most of activation cross sections and decay data were adequate. In cases of type 316 stainless steel and copper which were important for ITER, prediction accuracy of decay heat within ±10% was confirmed. However, it was pointed out that there were some problems in parts of data such as improper activation cross sections, e,g., the 92 Mo(n, 2n) 91g Mo reaction in FENDL, and lack of activation cross section data, e.g., the 138 Ba(n, 2n) 137m Ba reaction in JENDL. Modifications of cross section data were recommended for 19 reactions in JENDL and FENDL. It was also pointed out that X-ray and conversion electron energies should be included in decay data. (author)

  5. Experimental validation of decay heat calculation codes and associated nuclear data libraries for fusion energy

    Energy Technology Data Exchange (ETDEWEB)

    Maekawa, Fujio; Wada, Masayuki; Ikeda, Yujiro [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-01-01

    Validity of decay heat calculations for safety designs of fusion reactors was investigated by using decay heat experimental data on thirty-two fusion reactor relevant materials obtained at the 14-MeV neutron source facility of FNS in JAERI. Calculation codes developed in Japan, ACT4 and CINAC version 4, and nuclear data bases such as JENDL/Act-96, FENDL/A-2.0 and Lib90 were used for the calculation. Although several corrections in algorithms for both the calculation codes were needed, it was shown by comparing calculated results with the experimental data that most of activation cross sections and decay data were adequate. In cases of type 316 stainless steel and copper which were important for ITER, prediction accuracy of decay heat within {+-}10% was confirmed. However, it was pointed out that there were some problems in parts of data such as improper activation cross sections, e,g., the {sup 92}Mo(n, 2n){sup 91g}Mo reaction in FENDL, and lack of activation cross section data, e.g., the {sup 138}Ba(n, 2n){sup 137m}Ba reaction in JENDL. Modifications of cross section data were recommended for 19 reactions in JENDL and FENDL. It was also pointed out that X-ray and conversion electron energies should be included in decay data. (author)

  6. International bulletin on atomic and molecular data for fusion. No. 49

    International Nuclear Information System (INIS)

    Botero, J.

    1995-06-01

    This issue of the bulletin provides atomic and molecular data references relevant to fusion research and technology. In part 1 the indexation of the papers is provided separately for (i) structure and spectra, (ii) atomic and molecular collisions, and (iii) surface interactions. Part 2 contains the bibliographic data for the above-listed topics and brief bibliographic lists for the following topics: (a) fusion research of general interest, (b) high energy laser- and beam-matter interaction, (c) bibliographic and numerical data collections, and (d) interaction of atomic particles with fields. Moreover, the creation of the Atomic and Molecular Data Information System (AMDIS) is announced by the IAEA. AMDIS contains three main parts: the Atomic and Molecular Bibliographic Data System (AMBDAS), the numerical database of recommended and evaluated atomic, molecular and plasma-surface interaction data ALADDIN and an electronic bulletin board with information regarding data needs, meetings and programs of the IAEA Atomic and Molecular Data Unit. AMDIS may be reached via INTERNET. For information on how to access AMDIS, an electronic mail inquiry can be sent (address: ''pms'' followed by the usual ''at'' symbol followed by ''ripcrs01.iaea.or.at'')

  7. Improvement of training set structure in fusion data cleaning using Time-Domain Global Similarity method

    International Nuclear Information System (INIS)

    Liu, J.; Lan, T.; Qin, H.

    2017-01-01

    Traditional data cleaning identifies dirty data by classifying original data sequences, which is a class-imbalanced problem since the proportion of incorrect data is much less than the proportion of correct ones for most diagnostic systems in Magnetic Confinement Fusion (MCF) devices. When using machine learning algorithms to classify diagnostic data based on class-imbalanced training set, most classifiers are biased towards the major class and show very poor classification rates on the minor class. By transforming the direct classification problem about original data sequences into a classification problem about the physical similarity between data sequences, the class-balanced effect of Time-Domain Global Similarity (TDGS) method on training set structure is investigated in this paper. Meanwhile, the impact of improved training set structure on data cleaning performance of TDGS method is demonstrated with an application example in EAST POlarimetry-INTerferometry (POINT) system.

  8. Data analysis software tools for enhanced collaboration at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schachter, J.; Peng, Q.; Schissel, D.P.

    2000-01-01

    Data analysis at the DIII-D National Fusion Facility is simplified by the use of two software packages in analysis codes. The first is 'GAPlotObj', an IDL-based object-oriented library used in visualization tools for dynamic plotting. GAPlotObj gives users the ability to manipulate graphs directly through mouse and keyboard-driven commands. The second software package is 'MDSplus', which is used at DIII-D as a central repository for analyzed data. GAPlotObj and MDSplus reduce the effort required for a collaborator to become familiar with the DIII-D analysis environment by providing uniform interfaces for data display and retrieval. Two visualization tools at DIII-D that benefit from them are 'ReviewPlus' and 'EFITviewer'. ReviewPlus is capable of displaying interactive 2D and 3D graphs of raw, analyzed, and simulation code data. EFITviewer is used to display results from the EFIT analysis code together with kinetic profiles and machine geometry. Both bring new possibilities for data exploration to the user, and are able to plot data from any fusion research site with an MDSplus data server

  9. Data Analysis Software Tools for Enhanced Collaboration at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schachter, J.; Peng, Q.; Schissel, D.P.

    1999-01-01

    Data analysis at the DIII-D National Fusion Facility is simplified by the use of two software packages in analysis codes. The first is GAP1otObj, an IDL-based object-oriented library used in visualization tools for dynamic plotting. GAPlotObj gives users the ability to manipulate graphs directly through mouse and keyboard-driven commands. The second software package is MDSplus, which is used at DIED as a central repository for analyzed data. GAPlotObj and MDSplus reduce the effort required for a collaborator to become familiar with the DIII-D analysis environment by providing uniform interfaces for data display and retrieval. Two visualization tools at DIII-D that benefit from them are ReviewPlus and EFITviewer. ReviewPlus is capable of displaying interactive 2D and 3D graphs of raw, analyzed, and simulation code data. EFITviewer is used to display results from the EFIT analysis code together with kinetic profiles and machine geometry. Both bring new possibilities for data exploration to the user, and are able to plot data from any fusion research site with an MDSplus data server

  10. Lipid characterization of individual porcine oocytes by dual mode DESI-MS and data fusion

    International Nuclear Information System (INIS)

    Pirro, Valentina; Oliveri, Paolo; Ferreira, Christina Ramires; González-Serrano, Andrés Felipe; Machaty, Zoltan; Cooks, Robert Graham

    2014-01-01

    Highlights: • Repeated analysis by DESI(±)-MS of intact single oocytes for lipid characterization. • Deployment of a data fusion strategy to merge positive and negative ion mode data. • Enhanced interpretation of metabolic changes by more efficient analysis of spectral data. • Discovery of increased fatty acid metabolism and membrane complexity during maturation. • Assistance in the improvement of in vitro embryo production for porcine species. - Abstract: The development of sensitive measurements to analyze individual cells is of relevance to elucidate specialized roles or metabolic functions of each cell under physiological and pathological conditions. Lipids play multiple and critical roles in cellular functions and the application of analytical methods in the lipidomics area is of increasing interest. In this work, in vitro maturation of porcine oocytes was studied. Two independent sources of chemical information (represented by mass spectra in the positive and negative ion modes) from single oocytes (immature oocytes, 24-h and 44-h in vitro matured oocytes) were acquired by using desorption electrospray ionization-mass spectrometry (DESI-MS). Low and mid-level data fusion strategies are presented with the aim of better exploring the large amount of chemical information contained in the two mass spectrometric lipid profiles. Data were explored by principal component analysis (PCA) within the two multi-block approaches to include information on free fatty acids, phospholipids, cholesterol-related molecules, di- and triacylglycerols. After data fusion, clearer differences among immature and in vitro matured porcine oocytes were observed, which provide novel information regarding lipid metabolism throughout oocyte maturation. In particular, changes in TAG composition, as well as increase in fatty acid metabolism and membrane complexity were evidenced during the in vitro maturation process. This information can assist the improvement of in vitro embryo

  11. Joint sparsity based heterogeneous data-level fusion for target detection and estimation

    Science.gov (United States)

    Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

    2017-05-01

    Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

  12. New nuclear data group constant sets for fusion reactor nuclear analyses based on JENDL-4.0 and FENDL-3.0

    International Nuclear Information System (INIS)

    Konno, Chikara; Ohta, Masayuki; Kwon, Saerom; Ochiai, Kentaro; Sato, Satoshi

    2015-01-01

    We have produced new nuclear data group constant sets from JENDL-4.0 and FENDL-3.0 for fusion reactor nuclear analyses; FUSION-J40-175, FUSION-F30-175 (40 materials, neutron 175 groups, gamma 42 groups), FUSION-J40-42 and FUSION-F30-42 (40 materials, neutron 42 groups, gamma 21 groups). MATXS files of JENDL-4.0 and FENDL-3.0 were newly produced with the NJOY2012 code. FUSION-J40-175, FUSION-J40-42, FUSION-F30-175 and FUSION-F30-42 were produced with the TRANSX code. KERMA factors, DPA and gas production cross-section data were also prepared from the MATXS files with TRANSX. Test calculations were carried out in order to validate these nuclear group constant sets. They suggested that these group constant sets had no problem. (author)

  13. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

    OpenAIRE

    Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

    2013-01-01

    Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagn...

  14. Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

    Science.gov (United States)

    Schenker, Paul S. (Editor)

    1992-01-01

    Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

  15. International bulletin on atomic and molecular data for fusion. No. 52

    Energy Technology Data Exchange (ETDEWEB)

    Stephens, J A [ed.

    1997-08-01

    This bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In part 1 the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths, transition probabilities, oscillator strengths, interatomic potentials); (ii) atomic and molecular collisions (photon collisions, electron collisions, heavy-particle collisions); and (iii) surface interactions (sputtering, chemical reactions, trapping and detrapping, adsorption, desorption, reflection, and secondary electron emission). Part 2 contains the bibliographic data, essentially for the above listed topics.

  16. International bulletin on atomic and molecular data for fusion. Nos. 50-51

    International Nuclear Information System (INIS)

    Botero, J.; Stephens, J.A.

    1996-10-01

    This bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In part 1 the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths, transition probabilities, oscillator strengths, polarizabilities, electric moments, interatomic potentials); (ii) atomic and molecular collisions (photon collisions, electron collisions, heavy-particle collisions); and (iii) surface interactions (sputtering, chemical reactions, trapping and detrapping, adsorption, desorption, reflection, and secondary electron emission). Part 2 contains the bibliographic data, essentially for the above listed topics

  17. International bulletin on atomic and molecular data for fusion. No. 52

    International Nuclear Information System (INIS)

    Stephens, J.A.

    1997-08-01

    This bulletin is published by the International Atomic Energy Agency to provide atomic and molecular data relevant to fusion research and technology. In part 1 the indexed papers are listed separately for (i) structure and spectra (energy levels, wavelengths, transition probabilities, oscillator strengths, interatomic potentials); (ii) atomic and molecular collisions (photon collisions, electron collisions, heavy-particle collisions); and (iii) surface interactions (sputtering, chemical reactions, trapping and detrapping, adsorption, desorption, reflection, and secondary electron emission). Part 2 contains the bibliographic data, essentially for the above listed topics

  18. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    DEFF Research Database (Denmark)

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw

    2015-01-01

    downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even...... in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine....

  19. Generalized information fusion and visualization using spatial voting and data modeling

    Science.gov (United States)

    Jaenisch, Holger M.; Handley, James W.

    2013-05-01

    We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

  20. 'Low-activation' fusion materials development and related nuclear data needs

    International Nuclear Information System (INIS)

    Cierjacks, S.

    1990-01-01

    So-called ''low-activation'' materials are presently considered as an important means of improving the safety characteristics of future DT fusion reactors. Essential benefits are expected in various problem areas ranging from operation considerations to aspects of decommissioning and waste disposal. Present programs on ''low-activation'' materials development depend strongly on reliable activity calculations for a wide range of technologically important materials. The related nuclear data requirements and important needs for more and improved nuclear data are discussed. (author). 32 refs, 4 figs, 4 tabs

  1. Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

    Science.gov (United States)

    Ledezma, Carlos A.; Perpiñan, Gilberto; Severeyn, Erika; Altuve, Miguel

    2015-12-01

    Heart diseases are the main cause of death worldwide. The first step in the diagnose of these diseases is the analysis of the electrocardiographic (ECG) signal. In turn, the ECG analysis begins with the detection of the QRS complex, which is the one with the most energy in the cardiac cycle. Numerous methods have been proposed in the bibliography for QRS complex detection, but few authors have analyzed the possibility of taking advantage of the information redundancy present in multiple ECG leads (simultaneously acquired) to produce accurate QRS detection. In our previous work we presented such an approach, proposing various data fusion techniques to combine the detections made by an algorithm on multiple ECG leads. In this paper we present further studies that show the advantages of this multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance. A well known QRS detection algorithm was used to test the fusion techniques on the St. Petersburg Institute of Cardiological Technics database. Results show improvement in the detection performance with as little as three leads, but the reliability of these results becomes interesting only after using seven or more leads. Results were evaluated using the detection error rate (DER). The multi-lead detection approach allows an improvement from DER = 3:04% to DER = 1:88%. Further works are to be made in order to improve the detection performance by implementing further fusion steps.

  2. Data Evaluation and the Establishment of a Standard Library of Atomic, Molecular and Plasma-Material Interaction Data for Fusion. Summary Report of an IAEA Consultants' Meeting

    International Nuclear Information System (INIS)

    Braams, B.J.

    2012-08-01

    Seven experts in the field of atomic, molecular and plasma-material interaction (A+M+PMI) data and data evaluation for fusion plasma physics met with IAEA A+M Data Unit staff at IAEA Headquarters to provide advice towards the establishment of an evaluated and recommended library of A+M+PMI data for fusion. The proceedings and conclusions of the meeting are summarized here. (author)

  3. Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

    Science.gov (United States)

    Leptoukh, Gregory; Zubko, V.; Gopalan, A.

    2007-01-01

    The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

  4. Robust site security using smart seismic array technology and multi-sensor data fusion

    Science.gov (United States)

    Hellickson, Dean; Richards, Paul; Reynolds, Zane; Keener, Joshua

    2010-04-01

    Traditional site security systems are susceptible to high individual sensor nuisance alarm rates that reduce the overall system effectiveness. Visual assessment of intrusions can be intensive and manually difficult as cameras are slewed by the system to non intrusion areas or as operators respond to nuisance alarms. Very little system intrusion performance data are available other than discrete sensor alarm indications that provide no real value. This paper discusses the system architecture, integration and display of a multi-sensor data fused system for wide area surveillance, local site intrusion detection and intrusion classification. The incorporation of a novel seismic array of smart sensors using FK Beamforming processing that greatly enhances the overall system detection and classification performance of the system is discussed. Recent test data demonstrates the performance of the seismic array within several different installations and its ability to classify and track moving targets at significant standoff distances with exceptional immunity to background clutter and noise. Multi-sensor data fusion is applied across a suite of complimentary sensors eliminating almost all nuisance alarms while integrating within a geographical information system to feed a visual-fusion display of the area being secured. Real-time sensor detection and intrusion classification data is presented within a visual-fusion display providing greatly enhanced situational awareness, system performance information and real-time assessment of intrusions and situations of interest with limited security operator involvement. This approach scales from a small local perimeter to very large geographical area and can be used across multiple sites controlled at a single command and control station.

  5. CT-MR image data fusion for computer assisted navigated neurosurgery of temporal bone tumors

    International Nuclear Information System (INIS)

    Nemec, Stefan Franz; Donat, Markus Alexander; Mehrain, Sheida; Friedrich, Klaus; Krestan, Christian; Matula, Christian; Imhof, Herwig; Czerny, Christian

    2007-01-01

    Purpose: To demonstrate the value of multi detector computed tomography (MDCT) and magnetic resonance imaging (MRI) in the preoperative work up of temporal bone tumors and to present, especially, CT and MR image fusion for surgical planning and performance in computer assisted navigated neurosurgery of temporal bone tumors. Materials and methods: Fifteen patients with temporal bone tumors underwent MDCT and MRI. MDCT was performed in high-resolution bone window level setting in axial plane. The reconstructed MDCT slice thickness was 0.8 mm. MRI was performed in axial and coronal plane with T2-weighted fast spin-echo (FSE) sequences, un-enhanced and contrast-enhanced T1-weighted spin-echo (SE) sequences, and coronal T1-weighted SE sequences with fat suppression and with 3D T1-weighted gradient-echo (GE) contrast-enhanced sequences in axial plane. The 3D T1-weighted GE sequence had a slice thickness of 1 mm. Image data sets of CT and 3D T1-weighted GE sequences were merged utilizing a workstation to create CT-MR fusion images. MDCT and MR images were separately used to depict and characterize lesions. The fusion images were utilized for interventional planning and intraoperative image guidance. The intraoperative accuracy of the navigation unit was measured, defined as the deviation between the same landmark in the navigation image and the patient. Results: Tumorous lesions of bone and soft tissue were well delineated and characterized by CT and MR images. The images played a crucial role in the differentiation of benign and malignant pathologies, which consisted of 13 benign and 2 malignant tumors. The CT-MR fusion images supported the surgeon in preoperative planning and improved surgical performance. The mean intraoperative accuracy of the navigation system was 1.25 mm. Conclusion: CT and MRI are essential in the preoperative work up of temporal bone tumors. CT-MR image data fusion presents an accurate tool for planning the correct surgical procedure and is a

  6. FENDL-3.0: Processing the Evaluated Nuclear Data Library for Fusion Applications

    International Nuclear Information System (INIS)

    Lopez Aldama, D.; Noy, R. Capote

    2011-12-01

    A description of the work undertaken towards the development of a new version of the neutron-induced part of the Fusion Evaluated Nuclear Data Library (FENDL) for applications is summarized. The main issues related to the selection and processing of evaluated nuclear data files using the NJOY-99 and PREPRO-2010 processing systems are described. The new version of FENDL for applications, termed FENDL-3.0, includes the evaluated nuclear data files in ENDF-6 format, the continuous-energy cross section files in ACE format for the MCNP family of Monte Carlo codes and the multi-group data library in MATXS format for deterministic transport calculations up to 55 MeV for 180 isotopes. Further, additional data are supplied in GENDF format for sensitivity studies. The library is freely available from the Nuclear Data Section at the International Atomic Energy Agency. (author)

  7. DECISION LEVEL FUSION OF LIDAR DATA AND AERIAL COLOR IMAGERY BASED ON BAYESIAN THEORY FOR URBAN AREA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available Airborne Light Detection and Ranging (LiDAR generates high-density 3D point clouds to provide a comprehensive information from object surfaces. Combining this data with aerial/satellite imagery is quite promising for improving land cover classification. In this study, fusion of LiDAR data and aerial imagery based on Bayesian theory in a three-level fusion algorithm is presented. In the first level, pixel-level fusion, the proper descriptors for both LiDAR and image data are extracted. In the next level of fusion, feature-level, using extracted features the area are classified into six classes of “Buildings”, “Trees”, “Asphalt Roads”, “Concrete roads”, “Grass” and “Cars” using Naïve Bayes classification algorithm. This classification is performed in three different strategies: (1 using merely LiDAR data, (2 using merely image data, and (3 using all extracted features from LiDAR and image. The results of three classifiers are integrated in the last phase, decision level fusion, based on Naïve Bayes algorithm. To evaluate the proposed algorithm, a high resolution color orthophoto and LiDAR data over the urban areas of Zeebruges, Belgium were applied. Obtained results from the decision level fusion phase revealed an improvement in overall accuracy and kappa coefficient.

  8. Computerized cost estimation spreadsheet and cost data base for fusion devices

    International Nuclear Information System (INIS)

    Hamilton, W.R.; Rothe, K.E.

    1985-01-01

    An automated approach to performing and cataloging cost estimates has been developed at the Fusion Engineering Design Center (FEDC), wherein the cost estimate record is stored in the LOTUS 1-2-3 spreadsheet on an IBM personal computer. The cost estimation spreadsheet is based on the cost coefficient/cost algorithm approach and incorporates a detailed generic code of cost accounts for both tokamak and tandem mirror devices. Component design parameters (weight, surface area, etc.) and cost factors are input, and direct and indirect costs are calculated. The cost data base file derived from actual cost experience within the fusion community and refined to be compatible with the spreadsheet costing approach is a catalog of cost coefficients, algorithms, and component costs arranged into data modules corresponding to specific components and/or subsystems. Each data module contains engineering, equipment, and installation labor cost data for different configurations and types of the specific component or subsystem. This paper describes the assumptions, definitions, methodology, and architecture incorporated in the development of the cost estimation spreadsheet and cost data base, along with the type of input required and the output format

  9. Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions

    Directory of Open Access Journals (Sweden)

    Xiaolin Zhu

    2018-03-01

    Full Text Available Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.

  10. Information fusion performance evaluation for motion imagery data using mutual information: initial study

    Science.gov (United States)

    Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik

    2015-06-01

    As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

  11. Temporal Data Fusion Approaches to Remote Sensing-Based Wetland Classification

    Science.gov (United States)

    Montgomery, Joshua S. M.

    This thesis investigates the ecology of wetlands and associated classification in prairie and boreal environments of Alberta, Canada, using remote sensing technology to enhance classification of wetlands in the province. Objectives of the thesis are divided into two case studies, 1) examining how satellite borne Synthetic Aperture Radar (SAR), optical (RapidEye & SPOT) can be used to evaluate surface water trends in a prairie pothole environment (Shepard Slough); and 2) investigating a data fusion methodology combining SAR, optical and Lidar data to characterize wetland vegetation and surface water attributes in a boreal environment (Utikuma Regional Study Area (URSA)). Surface water extent and hydroperiod products were derived from SAR data, and validated using optical imagery with high accuracies (76-97% overall) for both case studies. High resolution Lidar Digital Elevation Models (DEM), Digital Surface Models (DSM), and Canopy Height Model (CHM) products provided the means for data fusion to extract riparian vegetation communities and surface water; producing model accuracies of (R2 0.90) for URSA, and RMSE of 0.2m to 0.7m at Shepard Slough when compared to field and optical validation data. Integration of Alberta and Canadian wetland classifications systems used to classify and determine economic value of wetlands into the methodology produced thematic maps relevant for policy and decision makers for potential wetland monitoring and policy development.

  12. IAEA technical meeting on atomic and plasma-material interaction data for fusion science technology. Summary report

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2003-10-01

    The proceedings and conclusions of the Technical Meeting on 'Atomic and Plasma- Material Interaction Data for Fusion Science Technology' held in Juelich, Germany on October 28-31 are summarized. During the course of the meetings working groups were formed to review the status of specific areas of atomic, molecular and material physics of relevance to fusion and to make recommendations on data needs in fusion from these areas. The reports of those working groups are summarized and the complete reports included as appendices. This meeting brought together over fifty leading scientists in fusion related data. Results of research in a number of topics were presented and very useful discussions were held. The meeting was extremely successful. (author)

  13. Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

    Science.gov (United States)

    Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

    2018-06-01

    Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

  14. An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

    Science.gov (United States)

    Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

    2017-01-01

    A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

  15. A metadata catalog for organization and systemization of fusion simulation data

    International Nuclear Information System (INIS)

    Greenwald, M.; Fredian, T.; Schissel, D.; Stillerman, J.

    2012-01-01

    Highlights: ► We find that modeling and simulation data need better systemization. ► Workflow, data provenance and relations among data items need to be captured. ► We have begun a design for a simulation metadata catalog that meets these needs. ► The catalog design also supports creation of science notebooks for simulation. - Abstract: Careful management of data and associated metadata is a critical part of any scientific enterprise. Unfortunately, most current fusion simulation efforts lack systematic, project-wide organization of their data. This paper describes an approach to managing simulation data through creation of a comprehensive metadata catalog, currently under development. The catalog is intended to document all past and current simulation activities (including data provenance); to enable global data location and to facilitate data access, analysis and visualization through uniform provision of metadata. The catalog will capture workflow, holding entries for each simulation activity including, at least, data importing and staging, data pre-processing and input preparation, code execution, data storage, post-processing and exporting. The overall aim is that between the catalog and the main data archive, the system would hold a complete and accessible description of the data, all of its attributes and the processes used to generate the data. The catalog will describe data collections, including those representing simulation workflows as well as any other useful groupings. Finally it would be populated with user supplied comments to explain the motivation and results of any activity documented by the catalog.

  16. US-Japan Workshop on atomic-collision data for fusion

    International Nuclear Information System (INIS)

    Crandall, D.H.; Hafford, P.M.; Itikawa, Y.

    1981-04-01

    This report, containing abstracts of each of the presentations and discussions, includes: brief talks on the applications of atomic data in tokamaks and in inertial confinement; reviews of the specific atomic collisions projects for fusion in Japan and the United States; discussions of how the data centers operate and manner of exchanging data; brief reviews of the status of electron-ion scattering and ion-atom scattering; discussions of criteria to be used in evaluating and selecting both experimental and theoretical data in these two areas; comparisons of data selected for each of six specific collision reactions which were evaluated by both groups prior to the workshop; brief reviews of activities in the related areas of atomic structure and plasma wall interactions; and a decision to pursue a joint or collaborative compilation of recommended cross sections for oxygen ions for electron impact excitation and electron capture from atomic hydrogen

  17. Computerized cost estimation spreadsheet and cost data base for fusion devices

    International Nuclear Information System (INIS)

    Hamilton, W.R.; Rothe, K.E.

    1985-01-01

    Component design parameters (weight, surface area, etc.) and cost factors are input and direct and indirect costs are calculated. The cost data base file derived from actual cost experience within the fusion community and refined to be compatible with the spreadsheet costing approach is a catalog of cost coefficients, algorithms, and component costs arranged into data modules corresponding to specific components and/or subsystems. Each data module contains engineering, equipment, and installation labor cost data for different configurations and types of the specific component or subsystem. This paper describes the assumptions, definitions, methodology, and architecture incorporated in the development of the cost estimation spreadsheet and cost data base, along with the type of input required and the output format

  18. Atomic data for beam-stimulated plasma spectroscopy in fusion plasmas

    International Nuclear Information System (INIS)

    Marchuk, O.; Biel, W.; Schlummer, T.; Ralchenko, Yu.; Schultz, D. R.

    2013-01-01

    Injection of high energy atoms into a confined plasma volume is an established diagnostic technique in fusion research. This method strongly depends on the quality of atomic data for charge-exchange recombination spectroscopy (CXRS), motional Stark effect (MSE) and beam-emission spectroscopy (BES). We present some examples of atomic data for CXRS and review the current status of collisional data for parabolic states of hydrogen atoms that are used for accurate MSE modeling. It is shown that the collisional data require knowledge of the excitation density matrix including the off-diagonal matrix elements. The new datasets for transitions between parabolic states are used in an extended collisional-radiative model. The ratios between the σ- and π-components and the beam-emission rate coefficients are calculated in a quasi-steady state approximation. Good agreement with the experimental data from JET is found which points out to strong deviations from the statistical distribution for magnetic sublevels

  19. Data fusion concept in multispectral system for perimeter protection of stationary and moving objects

    Science.gov (United States)

    Ciurapiński, Wieslaw; Dulski, Rafal; Kastek, Mariusz; Szustakowski, Mieczyslaw; Bieszczad, Grzegorz; Życzkowski, Marek; Trzaskawka, Piotr; Piszczek, Marek

    2009-09-01

    The paper presents the concept of multispectral protection system for perimeter protection for stationary and moving objects. The system consists of active ground radar, thermal and visible cameras. The radar allows the system to locate potential intruders and to control an observation area for system cameras. The multisensor construction of the system ensures significant improvement of detection probability of intruder and reduction of false alarms. A final decision from system is worked out using image data. The method of data fusion used in the system has been presented. The system is working under control of FLIR Nexus system. The Nexus offers complete technology and components to create network-based, high-end integrated systems for security and surveillance applications. Based on unique "plug and play" architecture, system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provides high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering.

  20. A data fusion approach to indications and warnings of terrorist attacks

    Science.gov (United States)

    McDaniel, David; Schaefer, Gregory

    2014-05-01

    Indications and Warning (I&W) of terrorist attacks, particularly IED attacks, require detection of networks of agents and patterns of behavior. Social Network Analysis tries to detect a network; activity analysis tries to detect anomalous activities. This work builds on both to detect elements of an activity model of terrorist attack activity - the agents, resources, networks, and behaviors. The activity model is expressed as RDF triples statements where the tuple positions are elements or subsets of a formal ontology for activity models. The advantage of a model is that elements are interdependent and evidence for or against one will influence others so that there is a multiplier effect. The advantage of the formality is that detection could occur hierarchically, that is, at different levels of abstraction. The model matching is expressed as a likelihood ratio between input text and the model triples. The likelihood ratio is designed to be analogous to track correlation likelihood ratios common in JDL fusion level 1. This required development of a semantic distance metric for positive and null hypotheses as well as for complex objects. The metric uses the Web 1Terabype database of one to five gram frequencies for priors. This size requires the use of big data technologies so a Hadoop cluster is used in conjunction with OpenNLP natural language and Mahout clustering software. Distributed data fusion Map Reduce jobs distribute parts of the data fusion problem to the Hadoop nodes. For the purposes of this initial testing, open source models and text inputs of similar complexity to terrorist events were used as surrogates for the intended counter-terrorist application.

  1. Radioactive waste produced by DEMO and commerical fusion reactors extrapolated from ITER and advanced data bases

    International Nuclear Information System (INIS)

    Stacey, W.M.; Hertel, N.E.; Hoffman, E.A.

    1994-01-01

    The potential for providing energy with minimal environmental impact is a powerful motivation for the development of fusion and is the long-term objective of most fusion programs. However, the societal acceptability of magnetic fusion may well be decided in the near-term when decisions are taken on the construction of DEMO to follow ITER (if not when the construction decision is taken on ITER). Component wastes were calculated for DEMOs based on each data base by first calculating reactor sizes needed to satisfy the physics, stress and radiation attenuation requirements, and then calculating component replacement rates based on radiation damage and erosion limits. Then, radioactive inventories were calculated and compared to a number of international criteria for open-quote near-surface close-quote burial. None of the components in either type of design would meet the Japanese LLW criterion ( 3 ) within 10 years of shutdown, although the advanced (V/Li) blanket would do so soon afterwards. The vanadium first wall, divertor and blanket would satisfy the IAEA LLW criterion (<2 mSv/h contact dose) within about 10 years after shutdown, but none of the stainless steel or copper components would. All the components in the advanced data base designs except the stainless steel vacuum vessel and shield readily satisfy the US extended 10CFR61 intruder dose criterion, but none of the components in the open-quotes ITER data baseclose quotes designs do so. It seems unlikely that a stainless steel first wall or a copper divertor plate could satisfy the US (class C) criterion for near surface burial, much less the more stringent international, criteria. On the other hand, the first wall, divertor and blanket of the V/Li system would still satisfy the intruder dose concentration limits even if the dose criterion was reduced by two orders of magnitude

  2. Data Fusion Research of Triaxial Human Body Motion Gesture based on Decision Tree

    Directory of Open Access Journals (Sweden)

    Feihong Zhou

    2014-05-01

    Full Text Available The development status of human body motion gesture data fusion domestic and overseas has been analyzed. A triaxial accelerometer is adopted to develop a wearable human body motion gesture monitoring system aimed at old people healthcare. On the basis of a brief introduction of decision tree algorithm, the WEKA workbench is adopted to generate a human body motion gesture decision tree. At last, the classification quality of the decision tree has been validated through experiments. The experimental results show that the decision tree algorithm could reach an average predicting accuracy of 97.5 % with lower time cost.

  3. Evaluation of the fusion-related neutron nuclear data for JENDL-3

    International Nuclear Information System (INIS)

    Chiba, Satoshi

    1988-01-01

    Status of the neutron nuclear data evaluations for JENDL-3 will be described for nuclides important in the development of D-T fusion reactors. In this article, however, only explanation of the evaluations for the very light mass region will be presented to avoid overlapping with what are given in another papers submitted to this seminar. Emphases are placed on the tritium production cross sections, inelastic scattering cross sections including the double-differential neutron emission spectrum (DDX), threshold reaction cross sections and photon production cross sections. The methods employed to prepare JENDL-3T library and their results will be summarized. (author)

  4. IAEA technical meeting on nuclear data library for advanced systems - Fusion devices

    International Nuclear Information System (INIS)

    Forrest, R.; Mengoni, A.

    2008-04-01

    A Technical Meeting on 'Nuclear Data Library for Advanced Systems - Fusion Devices' was held at the IAEA Headquarters in Vienna from 31 October to 2 November 2007. The main objective of the initiative has been to define a proposal and detailed plan of activities for a Co-ordinated Research Project on this subject. Details of the discussions which took place at the meeting, including a review of the current activities in the field, a list of recommendations and a proposed timeline schedule for the CRP are summarized in this report. (author)

  5. Intelligent Data Fusion for Wide-Area Assessment of UXO Contamination

    Science.gov (United States)

    2008-02-29

    Development Program (SERDP). The authors thank the SERDP staff and team members for their assistance, particularly Dr. Herb Nelson and Dr. Dan Steinhurst...Fusion and Integration for Intelligent Systems, Taipei, Taiwan , R.O.C., Aug., 1999. 4. B.J. Johnson, T.G. Moore, B.J. Blejer, C.F. Lee, T.P. Opar, S...gene-expression data using Dempster-Shafer Theory of evidence to predict breast cancer tumors,” Bioinformation 1(5), 170-5, (2006) 21. Dr. Herb H. Nelson, personal communication (2007)

  6. A data fusion based approach for damage detection in linear systems

    Directory of Open Access Journals (Sweden)

    Ernesto Grande

    2014-07-01

    Full Text Available The aim of the present paper is to propose innovative approaches able to improve the capability of classical damage indicators in detecting the damage position in linear systems. In particular, starting from classical indicators based on the change of the flexibility matrix and on the change of the modal strain energy, the proposed approaches consider two data fusion procedures both based on the Dempster-Shafer theory. Numerical applications are reported in the paper in order to assess the reliability of the proposed approaches considering different damage scenarios, different sets of modes of vibration and the presence of errors affecting the accounted modes of vibrations.

  7. Discrimination of Medicine Radix Astragali from Different Geographic Origins Using Multiple Spectroscopies Combined with Data Fusion Methods

    Science.gov (United States)

    Wang, Hai-Yan; Song, Chao; Sha, Min; Liu, Jun; Li, Li-Ping; Zhang, Zheng-Yong

    2018-05-01

    Raman spectra and ultraviolet-visible absorption spectra of four different geographic origins of Radix Astragali were collected. These data were analyzed using kernel principal component analysis combined with sparse representation classification. The results showed that the recognition rate reached 70.44% using Raman spectra for data input and 90.34% using ultraviolet-visible absorption spectra for data input. A new fusion method based on Raman combined with ultraviolet-visible data was investigated and the recognition rate was increased to 96.43%. The experimental results suggested that the proposed data fusion method effectively improved the utilization rate of the original data.

  8. Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

    Science.gov (United States)

    Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

    2017-12-01

    Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was

  9. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

    Science.gov (United States)

    LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

  10. Remotely sensed data fusion for offshore wind energy resource mapping; Fusion de donnees satellitaires pour la cartographie du potentiel eolien offshore

    Energy Technology Data Exchange (ETDEWEB)

    Ben Ticha, M.B

    2007-11-15

    Wind energy is a component of an energy policy contributing to a sustainable development. Last years, offshore wind parks have been installed offshore. These parks benefit from higher wind speeds and lower turbulence than onshore. To sit a wind park, it is necessary to have a mapping of wind resource. These maps are needed at high spatial resolution to show wind energy resource variations at the scale of a wind park. Wind resource mapping is achieved through the description of the spatial variations of statistical parameters characterizing wind climatology. For a precise estimation of these statistical parameters, high temporal resolution wind speed and direction measurements are needed. However, presently, there is no data source allying high spatial resolution and high temporal resolution. We propose a data fusion method taking advantage of the high spatial resolution of some remote sensing instruments (synthetic aperture radars) and the high temporal resolution of other remote sensing instruments (scatterometers). The data fusion method is applied to a case study and the results quality is assessed. The results show the pertinence of data fusion for the mapping of wind energy resource offshore. (author)

  11. A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tengyue Zou

    2017-11-01

    Full Text Available Wireless sensor networks are widely used to acquire environmental parameters to support agricultural production. However, data variation and noise caused by actuators often produce complex measurement conditions. These factors can lead to nonconformity in reporting samples from different nodes and cause errors when making a final decision. Data fusion is well suited to reduce the influence of actuator-based noise and improve automation accuracy. A key step is to identify the sensor nodes disturbed by actuator noise and reduce their degree of participation in the data fusion results. A smoothing value is introduced and a searching method based on Prim’s algorithm is designed to help obtain stable sensing data. A voting mechanism with dynamic weights is then proposed to obtain the data fusion result. The dynamic weighting process can sharply reduce the influence of actuator noise in data fusion and gradually condition the data to normal levels over time. To shorten the data fusion time in large networks, an acceleration method with prediction is also presented to reduce the data collection time. A real-time system is implemented on STMicroelectronics STM32F103 and NORDIC nRF24L01 platforms and the experimental results verify the improvement provided by these new algorithms.

  12. Utilizing cloud storage architecture for long-pulse fusion experiment data storage

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ming; Liu, Qiang [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan, Hubei (China); School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei (China); Zheng, Wei, E-mail: zhenghaku@gmail.com [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan, Hubei (China); School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei (China); Wan, Kuanhong; Hu, Feiran; Yu, Kexun [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan, Hubei (China); School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei (China)

    2016-11-15

    Scientific data storage plays a significant role in research facility. The explosion of data in recent years was always going to make data access, acquiring and management more difficult especially in fusion research field. For future long-pulse experiment like ITER, the extremely large data will be generated continuously for a long time, putting much pressure on both the write performance and the scalability. And traditional database has some defects such as inconvenience of management, hard to scale architecture. Hence a new data storage system is very essential. J-TEXTDB is a data storage and management system based on an application cluster and a storage cluster. J-TEXTDB is designed for big data storage and access, aiming at improving read–write speed, optimizing data system structure. The application cluster of J-TEXTDB is used to provide data manage functions and handles data read and write operations from the users. The storage cluster is used to provide the storage services. Both clusters are composed with general servers. By simply adding server to the cluster can improve the read–write performance, the storage space and redundancy, making whole data system highly scalable and available. In this paper, we propose a data system architecture and data model to manage data more efficient. Benchmarks of J-TEXTDB performance including read and write operations are given.

  13. Utilizing cloud storage architecture for long-pulse fusion experiment data storage

    International Nuclear Information System (INIS)

    Zhang, Ming; Liu, Qiang; Zheng, Wei; Wan, Kuanhong; Hu, Feiran; Yu, Kexun

    2016-01-01

    Scientific data storage plays a significant role in research facility. The explosion of data in recent years was always going to make data access, acquiring and management more difficult especially in fusion research field. For future long-pulse experiment like ITER, the extremely large data will be generated continuously for a long time, putting much pressure on both the write performance and the scalability. And traditional database has some defects such as inconvenience of management, hard to scale architecture. Hence a new data storage system is very essential. J-TEXTDB is a data storage and management system based on an application cluster and a storage cluster. J-TEXTDB is designed for big data storage and access, aiming at improving read–write speed, optimizing data system structure. The application cluster of J-TEXTDB is used to provide data manage functions and handles data read and write operations from the users. The storage cluster is used to provide the storage services. Both clusters are composed with general servers. By simply adding server to the cluster can improve the read–write performance, the storage space and redundancy, making whole data system highly scalable and available. In this paper, we propose a data system architecture and data model to manage data more efficient. Benchmarks of J-TEXTDB performance including read and write operations are given.

  14. Benchmarking of the FENDL-3 Neutron Cross-Section Data Library for Fusion Applications

    International Nuclear Information System (INIS)

    Fischer, U.; Kondo, K.; Angelone, M.; Batistoni, P.; Villari, R.; Bohm, T.; Sawan, M.; Walker, B.; Konno, C.

    2014-03-01

    This report summarizes the benchmark analyses performed in a joint effort of ENEA (Italy), JAEA (Japan), KIT (Germany), and the University of Wisconsin (USA) with the objective to test and qualify the neutron induced general purpose FENDL-3.0 data library for fusion applications. The benchmark approach consisted of two major steps including the analysis of a simple ITER-like computational benchmark, and a series of analyses of benchmark experiments conducted previously at the 14 MeV neutron generator facilities at ENEA Frascati, Italy (FNG) and JAEA, Tokai-mura, Japan (FNS). The computational benchmark revealed a modest increase of the neutron flux levels in the deep penetration regions and a substantial increase of the gas production in steel components. The comparison to experimental results showed good agreement with no substantial differences between FENDL-3.0 and FENDL-2.1 for most of the responses analysed. There is a slight trend, however, for an increase of the fast neutron flux in the shielding experiment and a decrease in the breeder mock-up experiments. The photon flux spectra measured in the bulk shield and the tungsten experiments are significantly better reproduced with FENDL-3.0 data. In general, FENDL-3, as compared to FENDL-2.1, shows an improved performance for fusion neutronics applications. It is thus recommended to ITER to replace FENDL-2.1 as reference data library for neutronics calculation by FENDL-3.0. (author)

  15. A Multiple Data Fusion Approach to Wheel Slip Control for Decentralized Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Dejun Yin

    2017-04-01

    Full Text Available Currently, active safety control methods for cars, i.e., the antilock braking system (ABS, the traction control system (TCS, and electronic stability control (ESC, govern the wheel slip control based on the wheel slip ratio, which relies on the information from non-driven wheels. However, these methods are not applicable in the cases without non-driven wheels, e.g., a four-wheel decentralized electric vehicle. Therefore, this paper proposes a new wheel slip control approach based on a novel data fusion method to ensure good traction performance in any driving condition. Firstly, with the proposed data fusion algorithm, the acceleration estimator makes use of the data measured by the sensor installed near the vehicle center of mass (CM to calculate the reference acceleration of each wheel center. Then, the wheel slip is constrained by controlling the acceleration deviation between the actual wheel and the reference wheel center. By comparison with non-control and model following control (MFC cases in double lane change tests, the simulation results demonstrate that the proposed control method has significant anti-slip effectiveness and stabilizing control performance.

  16. Data Fusion Based on Node Trust Evaluation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhou Jianming

    2014-01-01

    Full Text Available Abnormal behavior detection and trust evaluation mode of traditional sensor node have a single function without considering all the factors, and the trust value algorithm is relatively complicated. To avoid these above disadvantages, a trust evaluation model based on the autonomous behavior of sensor node is proposed in this paper. Each sensor node has the monitoring privilege and obligation. Neighboring sensor nodes can monitor each other. Their direct and indirect trust values can be achieved by using a relatively simple calculation method, the synthesis trust value of which could be got according to the composition rule of D-S evidence theory. Firstly, the cluster head assigns different weighted value for the data from each sensor node, then the weight vector is set according to the synthesis trust value, the data fusion processing is executed, and finally the cluster head sensor node transmits the fused result to the base station. Simulation experiment results demonstrate that the trust evaluation model can rapidly, exactly, and effectively recognize malicious sensor node and avoid malicious sensor node becoming cluster head sensor node. The proposed algorithm can greatly increase the safety and accuracy of data fusion, improve communication efficiency, save energy of sensor node, suit different application fields, and deploy environments.

  17. Application of data fusion techniques and technologies for wearable health monitoring.

    Science.gov (United States)

    King, Rachel C; Villeneuve, Emma; White, Ruth J; Sherratt, R Simon; Holderbaum, William; Harwin, William S

    2017-04-01

    Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market. Copyright © 2017. Published by Elsevier Ltd.

  18. A CNN-Based Fusion Method for Feature Extraction from Sentinel Data

    Directory of Open Access Journals (Sweden)

    Giuseppe Scarpa

    2018-02-01

    Full Text Available Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative is to benefit from weather-insensitive synthetic aperture radar (SAR images. In many real-world applications, critical decisions are made based on some informative optical or radar features related to items such as water, vegetation or soil. Under cloudy conditions, however, optical-based features are not available, and they are commonly reconstructed through linear interpolation between data available at temporally-close time instants. In this work, we propose to estimate missing optical features through data fusion and deep-learning. Several sources of information are taken into account—optical sequences, SAR sequences, digital elevation model—so as to exploit both temporal and cross-sensor dependencies. Based on these data and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI, using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May–November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baseline methods according to all performance indicators.

  19. Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach

    Science.gov (United States)

    Sun, Liang; Anderson, Martha C.; Gao, Feng; Hain, Christopher; Alfieri, Joseph G.; Sharifi, Amirreza; McCarty, Gregory W.; Yang, Yun; Yang, Yang; Kustas, William P.; McKee, Lynn

    2017-07-01

    The health of the Chesapeake Bay ecosystem has been declining for several decades due to high levels of nutrients and sediments largely tied to agricultural production systems. Therefore, monitoring of agricultural water use and hydrologic connections between crop lands and Bay tributaries has received increasing attention. Remote sensing retrievals of actual evapotranspiration (ET) can provide valuable information in support of these hydrologic modeling efforts, spatially and temporally describing consumptive water use by crops and natural vegetation and quantifying response to expansion of irrigated area occurring with Bay watershed. In this study, a multisensor satellite data fusion methodology, combined with a multiscale ET retrieval algorithm, was applied over the Choptank River watershed located within the Lower Chesapeake Bay region on the Eastern Shore of Maryland, USA to produce daily 30 m resolution ET maps. ET estimates directly retrieved on Landsat satellite overpass dates have high accuracy with relative error (RE) of 9%, as evaluated using flux tower measurements. The fused daily ET time series have reasonable errors of 18% at the daily time step - an improvement from 27% errors using standard Landsat-only interpolation techniques. Annual water consumption by different land cover types was assessed, showing reasonable distributions of water use with cover class. Seasonal patterns in modeled crop transpiration and soil evaporation for dominant crop types were analyzed, and agree well with crop phenology at field scale. Additionally, effects of irrigation occurring during a period of rainfall shortage were captured by the fusion program. These results suggest that the ET fusion system will have utility for water management at field and regional scales over the Eastern Shore. Further efforts are underway to integrate these detailed water use data sets into watershed-scale hydrologic models to improve assessments of water quality and inform best

  20. Grassland Npp Monitoring Based on Multi-Source Remote Sensing Data Fusion

    Science.gov (United States)

    Cai, Y. R.; Zheng, J. H.; Du, M. J.; Mu, C.; Peng, J.

    2018-04-01

    Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006-2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

  1. Data acquisition and processing system at the NOVETTE laser-fusion facility

    International Nuclear Information System (INIS)

    Auerbach, J.M.; Severyn, J.R.; Kroepfl, D.J.

    1982-01-01

    The computer hardware and software used for acquisition and processing of data from experiments at the NOVETTE laser fusion facility are described. Nearly two hundred sensors are used to measure the performance of millimeter extent targets irradiated by multi-kilojoule laser pulses. Sensor output is recorded on CAMAC based digitizers, CCD arrays, and film. CAMAC instrument outputs are acquired and collected by a network of LSI-11 microprocessors centrally controlled by a VAX 11/780. The user controls the system through menus presented on color video displays equipped with touch panels. The control VAX collects data from all microprocessors and CCD arrays and stores them in a file for transport to a second VAX 11/780 which is used for processing and final analysis. Transfer is done through a high speed fiber-optic link. Relational data bases are used extensively in the processing and archiving of data

  2. From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

    Science.gov (United States)

    Pires, Ivan Miguel; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco

    2016-01-01

    This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs). PMID:26848664

  3. From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

    Directory of Open Access Journals (Sweden)

    Ivan Miguel Pires

    2016-02-01

    Full Text Available This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs.

  4. A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

    Directory of Open Access Journals (Sweden)

    Neha Joshi

    2016-01-01

    Full Text Available The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

  5. Data fusion of multi-scale representations for structural damage detection

    Science.gov (United States)

    Guo, Tian; Xu, Zili

    2018-01-01

    Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

  6. Knowledge fusion: Time series modeling followed by pattern recognition applied to unusual sections of background data

    International Nuclear Information System (INIS)

    Burr, T.; Doak, J.; Howell, J.A.; Martinez, D.; Strittmatter, R.

    1996-03-01

    This report describes work performed during FY 95 for the Knowledge Fusion Project, which by the Department of Energy, Office of Nonproliferation and National Security. The project team selected satellite sensor data as the one main example to which its analysis algorithms would be applied. The specific sensor-fusion problem has many generic features that make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series in a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. This report describes the implementation and application of this two-step process for separating events from unusual background. As a fortunate by-product of this activity, it is possible to gain a better understanding of the natural background

  7. Knowledge fusion: Time series modeling followed by pattern recognition applied to unusual sections of background data

    Energy Technology Data Exchange (ETDEWEB)

    Burr, T.; Doak, J.; Howell, J.A.; Martinez, D.; Strittmatter, R.

    1996-03-01

    This report describes work performed during FY 95 for the Knowledge Fusion Project, which by the Department of Energy, Office of Nonproliferation and National Security. The project team selected satellite sensor data as the one main example to which its analysis algorithms would be applied. The specific sensor-fusion problem has many generic features that make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series in a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. This report describes the implementation and application of this two-step process for separating events from unusual background. As a fortunate by-product of this activity, it is possible to gain a better understanding of the natural background.

  8. Data fusion methodologies for food and beverage authentication and quality assessment - a review.

    Science.gov (United States)

    Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Busto, Olga

    2015-09-03

    The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. A Weighted Combination Method for Conflicting Evidence in Multi-Sensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2018-05-01

    Full Text Available Dempster–Shafer evidence theory is widely applied in various fields related to information fusion. However, how to avoid the counter-intuitive results is an open issue when combining highly conflicting pieces of evidence. In order to handle such a problem, a weighted combination method for conflicting pieces of evidence in multi-sensor data fusion is proposed by considering both the interplay between the pieces of evidence and the impacts of the pieces of evidence themselves. First, the degree of credibility of the evidence is determined on the basis of the modified cosine similarity measure of basic probability assignment. Then, the degree of credibility of the evidence is adjusted by leveraging the belief entropy function to measure the information volume of the evidence. Finally, the final weight of each piece of evidence generated from the above steps is obtained and adopted to modify the bodies of evidence before using Dempster’s combination rule. A numerical example is provided to illustrate that the proposed method is reasonable and efficient in handling the conflicting pieces of evidence. In addition, applications in data classification and motor rotor fault diagnosis validate the practicability of the proposed method with better accuracy.

  10. Multisensor data fusion for enhanced respiratory rate estimation in thermal videos.

    Science.gov (United States)

    Pereira, Carina B; Xinchi Yu; Blazek, Vladimir; Venema, Boudewijn; Leonhardt, Steffen

    2016-08-01

    Scientific studies have demonstrated that an atypical respiratory rate (RR) is frequently one of the earliest and major indicators of physiological distress. However, it is also described in the literature as "the neglected vital parameter", mainly due to shortcomings of clinical available monitoring techniques, which require attachment of sensors to the patient's body. The current paper introduces a novel approach that uses multisensor data fusion for an enhanced RR estimation in thermal videos. It considers not only the temperature variation around nostrils and mouth, but the upward and downward movement of both shoulders. In order to analyze the performance of our approach, two experiments were carried out on five healthy candidates. While during phase A, the subjects breathed normally, during phase B they simulated different breathing patterns. Thoracic effort was the gold standard elected to validate our algorithm. Our results show an excellent agreement between infrared thermography (IRT) and ground truth. While in phase A a mean correlation of 0.983 and a root-mean-square error of 0.240 bpm (breaths per minute) was obtained, in phase B they hovered around 0.995 and 0.890 bpm, respectively. In sum, IRT may be a promising clinical alternative to conventional sensors. Additionally, multisensor data fusion contributes to an enhancement of RR estimation and robustness.

  11. Comparison of different fusion nuclear data libraries using the European INTOR blanket design

    International Nuclear Information System (INIS)

    Pelloni, S.; Stepanek, J.; Dudziak, D.

    1982-12-01

    The European Community International Tokamak Reactor (INTOR-EC) was used to investigate the influence of different cross-section libraries on the tritium breeding ratio. Nucleonic analyses were performed using the discrete-ordinates transport codes ANISN and ONEDANT, and the recently developed Swiss surface-flux code SURCU, for the Li 17 Pb 83 and Li 2 SiO 3 blanket designs. Nuclear data considered were from the DLC-37, VITAMIN-C (DLC-41) and Los Alamos-NJOY fusion libraries. In addition the reaction rates were estimated using the MACKLIB-IV response library. It is shown that very good agreement (within 0.5%) between the breeding ratios obtained using the VITAMIN-C and Los Alamos libraries could be obtained, whereas the corresponding values calculated using VITAMIN-C and MACKLIB-IV data sets collapsed into 25 neutron and 21 gamma groups differ up to 23%. It is found that this large discrepancy is due to the 6 Li(n, α) reaction cross sections in the low energy range between 4 and 0.03 eV. Furthermore, the collapsed DLC-37 library is not adequate for fusion blankets with a soft spectrum. It is important that greater care be given to preparation of broad group cross section sets, especially in the thermal energy region for blankets containing highly moderating materials. (Auth.)

  12. Feature level fusion for enhanced geological mapping of ophiolile complex using ASTER and Landsat TM data

    International Nuclear Information System (INIS)

    Pournamdari, M; Hashim, M

    2014-01-01

    Chromite ore deposit occurrence is related to ophiolite complexes as a part of the oceanic crust and provides a good opportunity for lithological mapping using remote sensing data. The main contribution of this paper is a novel approaches to discriminate different rock units associated with ophiolite complex using the Feature Level Fusion technique on ASTER and Landsat TM satellite data at regional scale. In addition this study has applied spectral transform approaches, consisting of Spectral Angle Mapper (SAM) to distinguish the concentration of high-potential areas of chromite and also for determining the boundary between different rock units. Results indicated both approaches show superior outputs compared to other methods and can produce a geological map for ophiolite complex rock units in the arid and the semi-arid region. The novel technique including feature level fusion and Spectral Angle Mapper (SAM) discriminated ophiolitic rock units and produced detailed geological maps of the study area. As a case study, Sikhoran ophiolite complex located in SE, Iran has been selected for image processing techniques. In conclusion, a suitable approach for lithological mapping of ophiolite complexes is demonstrated, this technique contributes meaningfully towards economic geology in terms of identifying new prospects

  13. Grounding Lines Detecting Using LANDSAT8 Oli and CRYOSAT-2 Data Fusion

    Science.gov (United States)

    Li, F.; Guo, Y.; Zhang, Y.; Zhang, S.

    2018-04-01

    The grounding zone is the region where ice transitions from grounded ice sheet to freely floating ice shelf, grounding lines are actually more of a zone, typically over several kilometers. The mass loss from Antarctica is strongly linked to changes in the ice shelves and their grounding lines, since the variation in the grounding line can result in very rapid changes in glacier and ice-shelf behavior. Based on remote sensing observations, five global Antarctic grounding line products have been released internationally, including MOA, ASAID, ICESat, MEaSUREs, and Synthesized grounding lines. However, the five products could not provide the annual grounding line products of the whole Antarctic, even some products have stopped updating, which limits the time series analysis of Antarctic material balance to a certain extent. Besides, the accurate of single remote-sensing data based grounding line products is far from satisficed. Therefore, we use algorithms to extract grounding lines with SAR and Cryosat-2 data respectively, and combine the results of two kinds of grounding lines to obtain new products, we obtain a mature grounding line extraction algorithm process, so that we can realize the extraction of grounding line of the Antarctic each year in the future. The comparison between fusion results and the MOA product results indicate that there is a maximum deviation of 188.67 meters between the MOA product and the fusion result.

  14. An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis.

    Science.gov (United States)

    Tang, Yongchuan; Zhou, Deyun; Zhuang, Miaoyan; Fang, Xueyi; Xie, Chunhe

    2017-09-18

    As an important tool of information fusion, Dempster-Shafer evidence theory is widely applied in handling the uncertain information in fault diagnosis. However, an incorrect result may be obtained if the combined evidence is highly conflicting, which may leads to failure in locating the fault. To deal with the problem, an improved evidential-Induced Ordered Weighted Averaging (IOWA) sensor data fusion approach is proposed in the frame of Dempster-Shafer evidence theory. In the new method, the IOWA operator is used to determine the weight of different sensor data source, while determining the parameter of the IOWA, both the distance of evidence and the belief entropy are taken into consideration. First, based on the global distance of evidence and the global belief entropy, the α value of IOWA is obtained. Simultaneously, a weight vector is given based on the maximum entropy method model. Then, according to IOWA operator, the evidence are modified before applying the Dempster's combination rule. The proposed method has a better performance in conflict management and fault diagnosis due to the fact that the information volume of each evidence is taken into consideration. A numerical example and a case study in fault diagnosis are presented to show the rationality and efficiency of the proposed method.

  15. Automatic data-acquisition and communications computer network for fusion experiments

    International Nuclear Information System (INIS)

    Kemper, C.O.

    1981-01-01

    A network of more than twenty computers serves the data acquisition, archiving, and analysis requirements of the ISX, EBT, and beam-line test facilities at the Fusion Division of Oak Ridge National Laboratory. The network includes PDP-8, PDP-12, PDP-11, PDP-10, and Interdata 8-32 processors, and is unified by a variety of high-speed serial and parallel communications channels. While some processors are dedicated to experimental data acquisition, and others are dedicated to later analysis and theoretical work, many processors perform a combination of acquisition, real-time analysis and display, and archiving and communications functions. A network software system has been developed which runs in each processor and automatically transports data files from point of acquisition to point or points of analysis, display, and storage, providing conversion and formatting functions are required

  16. Human Factors and Data Fusion as Part of Control Systems Resilience

    Energy Technology Data Exchange (ETDEWEB)

    David I. Gertman

    2009-05-01

    Human performance and human decision making is counted upon as a crucial aspect of overall system resilience. Advanced control systems have the potential to provide operators and asset owners a wide range of data, deployed at different levels that can be used to support operator situation awareness. However, the sheer amount of data available can make it challenging for operators to assimilate information and respond appropriately. This paper reviews some of the challenges and issues associated with providing operators with actionable state awareness and argues for the over arching importance of integrating human factors as part of intelligent control systems design and implementation. It is argued that system resilience is improved by implementing human factors in operations and maintenance. This paper also introduces issues associated with resilience and data fusion and highlights areas in which human factors including field studies hold promise.

  17. ZZ FENDL-2, Evaluated Nuclear Data Library for Fusion Neutronics Applications

    International Nuclear Information System (INIS)

    2005-01-01

    Description: FENDL: Fusion Evaluated Nuclear Data Library. Materials/nuclides: H 1 , H 2 , H 3 , He 3 , He 4 , Li 6 , Li 7 , Be 9 , B 10 , B 11 , C 12 , N 14 , N 15 , O 16 , F 19 , Na 23 , Mg nat , Al 27 , Si 28 , Si 29 , Si 30 , P 31 , S nat , Cl 35 , Cl 37 , K nat , Ca nat , Ti 46 , Ti 47 , Ti 48 , Ti 49 , Ti 50 , V nat , Cr 50 , Cr 52 , Cr 53 , Cr 54 , Mn 55 , Fe 54 , Fe 56 , Fe 57 , Fe 58 , Co 59 , Ni 58 , Ni 60 , Ni 61 , Ni 62 , Ni 64 , Cu 63 , Cu 65 , Ga nat , Zr nat , Nb 93 , Mo 92 , Mo 94 , Mo 95 , Mo 96 , Mo 97 , Mo 98 , Mo 100 , Sn nat , Ta 181 , W 182 , W 183 , W 184 , W 186 , Au 197 , Pb 206 , Pb 207 , Pb 208 , Bi 209 . Photo-atomic data. IAEA1364/02: FENDL version 2.0 consists of the following sub-libraries: - ACTIVATION (FENDL/A-2.0)- neutron activation cross sections for 13006 reactions on 739 targets ranging from 1-H up to 248-Cm at incident energies up to 20 MeV. Pointwise and processed data in different formats are included. Plots are available. - DECAY (FENDL/D-2.0) - decay properties (decay type, decay energy, and half life) for 1867 nuclides and isomers. FENDL/D-2.0 sub-library is complementary to the activation sub-library. Pointwise and processed data are included. - DOSIMETRY (FENDL/DS-2.0) - neutron cross sections to be used for reactor neutron dosimetry by foil activation, radiation damage cross-sections, and benchmark neutron spectra. This sub-library is identical to the International Reactor Dosimetry File (IRDF-90). Pointwise and processed data are included. - FUSION (FENDL/C-2.0) - charged-particle cross sections for the following fusion reactions: 1-H 2 (d,n)2-He 3 , 1-H 2 (d,p)1-H 3 , 2-He 3 (d,p)2-He 4 , 1-H-3(t,2n)2-He 4 , and 1-H 3 (d,n)2-He 4 . Pointwise and processed data are included. - TRANSPORT - validated basic nuclear data (neutron-nucleus interaction including photon production, and photon-atom interaction cross sections) for 57 nuclides relevant for fusion. In addition to the pointwise data (FENDL/E-2.0), the sub

  18. Assessment of ion-atom collision data for magnetic fusion plasma edge modelling

    International Nuclear Information System (INIS)

    Phaneuf, R.A.

    1990-01-01

    Cross-section data for ion-atom collision processes which play important roles in the edge plasma of magnetically-confined fusion devices are surveyed and reviewed. The species considered include H, He, Li, Be, C, O, Ne, Al, Si, Ar, Ti, Cr, Fe, Ni, Cu, Mo, W and their ions. The most important ion-atom collision processes occurring in the edge plasma are charge-exchange reactions. Excitation and ionization processes are also considered. The scope is limited to atomic species and to collision velocities corresponding to plasma ion temperatures in the 2-200 eV range. Sources of evaluated or recommended data are presented where possible, and deficiencies in the data base are indicated. 42 refs., 1 fig., 4 tabs

  19. Materials data base as an interface between fusion reactor designs and materials development

    International Nuclear Information System (INIS)

    Ishino, S.; Iwata, S.

    1983-01-01

    The materials data base is an integrated information system of experimental and/or calculated data of materials being compiled to meet the broad needs for materials data by taking advantage of the data base management systems. In this paper the objective of such computerized data base is described from the viewpoint of materials engineers and fusion system designers. Materials data spread themselves widely from the field that relates fundamental understanding of the behaviors of electrons, atoms, vacancies, dislocations and so on to the performance of components, devices, machines and systems. In our approach this information is described as ''relations'' by a set of tables which comprise related variables, for example, a set of values about essential properties for materials selection. This approach based on the relational model enables relational operations, i.e. SELECTION, PROJECTION, JOIN and so on, to select suitable materials, to set trade-off parameters for system designers and to establish design criteria. Stored data comprise (i) fundamental properties for all elements and potential structural materials, (ii) low cycle fatigue, irradiation creep and swelling data for type 316 stainless steels. These data have been selected and evaluated from critical reviews of existing data base of about 2 mega bytes data, some examples of materials selections and extraction of trade-off parameters are shown as a subject of critical issue concerning how to bridge the large gap between materials developments and system designs. (author)

  20. Fusion of product and process data: Batch-mode and real-time streaming

    Energy Technology Data Exchange (ETDEWEB)

    Vincent De Sapio; Spike Leonard

    1999-12-01

    In today's DP product realization enterprise it is imperative to reduce the design-to-fabrication cycle time and cost while improving the quality of DP parts (reducing defects). Much of this challenge resides in the inherent gap between the product and process worlds. The lack of seamless, bi-directional flow of information prevents true concurrency in the product realization world. This report addresses a framework for product-process data fusion to help achieve next generation product realization. A fundamental objective is to create an open environment for multichannel observation of process date, and subsequent mapping of that data onto product geometry. In addition to the sensor-based observation of manufacturing processes, model-based process data provides an important complement to empirically acquired data. Two basic groups of manufacturing models are process physics, and machine kinematics and dynamics. Process physics addresses analytical models that describe the physical phenomena of the process itself. Machine kinematic and dynamic models address the mechanical behavior of the processing equipment. As a secondary objective, an attempt has been made in this report to address part of the model-based realm through the development of an open object-oriented library and toolkit for machine kinematics and dynamics. Ultimately, it is desirable to integrate design definition, with all types of process data; both sensor-based and model-based. Collectively, the goal is to allow all disciplines within the product realization enterprise to have a centralized medium for the fusion of product and process data.

  1. Determination of atomic data pertinent to the Magnetic Fusion Program: Technical progress report, 15 May 1986-30 September 1987

    International Nuclear Information System (INIS)

    Wiese, W.L.

    1987-01-01

    Dielectronic recombination and excitation rates, electron-impact excitation and ionization cross sections, and wavelengths and energy levels of prominent spectral lines are experimentally and theoretically determined. Wavelengths for both electric and magnetic dipole transitions and atomic energy level data are also critically evaluated, compiled, and tabulated. Theoretical methods use both relativistic and nonrelativistic formulations. The work concentrated on ions of materials commonly used in current fusion devices, such as titanium, iron, and nickel, as well as heavier elements expected to be introduced into next-generation fusion devices for diagnostic purposes, such as krypton and xenon. The range of ions is extended to include very highly charged species in anticipation of needs in very high-temperature fusion devices such as TFTR and its successors. Work described also represents collaboration with major fusion laboratories such as Oak Ridge National Laboratory, Princeton Plasma Physics Laboratory, and GA Technologies

  2. 14th meeting of the IFRC Subcommittee on Atomic and Molecular Data for Fusion. Summary report of IAEA technical meeting

    International Nuclear Information System (INIS)

    Clark, R.E.H.; Peacock, N.J.

    2006-01-01

    The 14th Meeting of the Subcommittee on Atomic and Molecular Data for Fusion of the International Fusion Research Council was held on 24-25 June 2004, at the IAEA Headquarters in Vienna, Austria. Subcommittee members reviewed the work of the Atomic and Molecular Data Unit over the two-year period from June 2002 to June 2004, and made recommendations that covered the 2005-2006 budget cycle. The proceedings, conclusions and recommendations of the meeting are briefly described in this report, along with a short summary of the activities of the IAEA Atomic and Molecular Data Unit of the Nuclear Data Section from June 2002 to June 2004. (author)

  3. IAEA activities on atomic, molecular and plasma-material interaction data for fusion

    Science.gov (United States)

    Braams, Bastiaan J.; Chung, Hyun-Kyung

    2013-09-01

    The IAEA Atomic and Molecular Data Unit (http://www-amdis.iaea.org/) aims to provide internationally evaluated and recommended data for atomic, molecular and plasma-material interaction (A+M+PMI) processes in fusion research. The Unit organizes technical meetings and coordinates an A+M Data Centre Network (DCN) and a Code Centre Network (CCN). In addition the Unit organizes Coordinated Research Projects (CRPs), for which the objectives are mixed between development of new data and evaluation and recommendation of existing data. In the area of A+M data we are placing new emphasis in our meeting schedule on data evaluation and especially on uncertainties in calculated cross section data and the propagation of uncertainties through structure data and fundamental cross sections to effective rate coefficients. Following a recent meeting of the CCN it is intended to use electron scattering on Be, Ne and N2 as exemplars for study of uncertainties and uncertainty propagation in calculated data; this will be discussed further at the presentation. Please see http://www-amdis.iaea.org/CRP/ for more on our active and planned CRPs, which are concerned with atomic processes in core and edge plasma and with plasma interaction with beryllium-based surfaces and with irradiated tungsten.

  4. Third Meeting of the IFRC Subcommittee on Atomic and Molecular (A+M) Data for Fusion. Summary Report

    Energy Technology Data Exchange (ETDEWEB)

    Lorenz, A.; Hughes, J. [International Atomic Energy Agency, Nuclear Data Section, Vienna (Austria)

    1984-11-15

    The Subcommittee reaffirmed its earlier position that the primary function of the IAEA A+M Data Unit is to assemble a file of evaluated atomic collision data which had been recommended by atomic physicists and disseminate these data to the fusion research community.

  5. Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

    Directory of Open Access Journals (Sweden)

    Chunxue Wu

    2017-11-01

    Full Text Available Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications.

  6. Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents.

    Science.gov (United States)

    Wu, Chunxue; Wu, Wenliang; Wan, Caihua; Bekkering, Ernst; Xiong, Naixue

    2017-11-03

    Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications.

  7. Data fusion for target tracking and classification with wireless sensor network

    Science.gov (United States)

    Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

    2016-10-01

    In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

  8. Data compilation for radiation effects on hydrogen recycle in fusion reactor materials

    International Nuclear Information System (INIS)

    Ozawa, Kunio; Fukushima, Kimichika; Ebisawa, Katsuyuki.

    1984-05-01

    Irradiation tests of materials by hydrogen isotopes are under way, to investigate the hydrogen recycling process where exchange of fuel particles takes place between plasma and the wall of the nuclear fusion reactor. In the report, data on hydrogen irradiation are collected and reviewed from the view point of irradiation effects. Data are classified into, (1) Re-emmission, (2) Retention, (Retained hydrogen isotopes, Depth profile in the materials and Thermal desorption spectroscopy), (3) Permeation and (4) Ion impact desorption. Research activities in each area are arranged according to the date of publication, research institutes, materials investigated, so that overview of present status can be made. Then, institute, author and reference are shown for each classification with tables. The list of literature is also attached. (author)

  9. Data Fusion Modeling for an RT3102 and Dewetron System Application in Hybrid Vehicle Stability Testing

    Directory of Open Access Journals (Sweden)

    Zhibin Miao

    2015-08-01

    Full Text Available More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

  10. Data fusion of ultrasound and GPR signals for analysis of historic walls

    International Nuclear Information System (INIS)

    Salazar, A; Gosalbez, J; Safont, G; Vergara, L

    2012-01-01

    This paper presents an application of ultrasounds and ground-penetrating radar (GPR) for analysis of historic walls. The objectives are to characterize the deformation of a historic wall under different levels of load weights and to obtain an enhanced image of the wall. A new method that fuses data from ultrasound and GPR traces is proposed which is based on order statistics digital filters. Application results are presented for non destructive testing (NDT) of two replicates of historic ashlars' masonry walls: the first one homogeneous and the second one containing controlled defects such as cracks and nooks. The walls are measured separately using ultrasounds and GPR at different load steps. Time and frequency parameters extracted from the signals and different B-Scans for each of the NDT techniques are obtained. After this, a new fused representation is obtained, which results demonstrate the improvement of characterization and defect detection in historic walls using data fusion.

  11. A study on multi-data source fusion method for petroleum pipeline leak detection

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Wei; Zhang, Laibin [Research Center of Oil and Gas Safety Engineering Technology, China University of Petroleum, Beijing, (China)

    2010-07-01

    The detection of leaks on petroleum pipeline is a very important safety issue. Several studies were commissioned to develop new monitoring procedures for leakage detection. This paper sets out a new leak detection process. The approach developed took into consideration steady and transient states. The study investigated leak diagnosis problems in product pipelines using multi-sensor measurements (pressure, flux, density and temperature). The information collected from each sensor was considered as pieces of evidence that describe the operational conditions of the pipeline. The Dempster-Shafer (D-S) theory is used to associate multi-sensor data to pipe health indices. Experimental pressure and flow rate data were recorded using a Pipeline Leak Detection System (PLDS) acquisition card and used to verify the accuracy and reliability of this new detection method. The results showed that the degree of credibility was a high as 0.877. It was also found that multi-feature information fusion improves recognition of pipeline conditions.

  12. Optimal preprocessing of serum and urine metabolomic data fusion for staging prostate cancer through design of experiment

    International Nuclear Information System (INIS)

    Zheng, Hong; Cai, Aimin; Zhou, Qi; Xu, Pengtao; Zhao, Liangcai; Li, Chen; Dong, Baijun; Gao, Hongchang

    2017-01-01

    Accurate classification of cancer stages will achieve precision treatment for cancer. Metabolomics presents biological phenotypes at the metabolite level and holds a great potential for cancer classification. Since metabolomic data can be obtained from different samples or analytical techniques, data fusion has been applied to improve classification accuracy. Data preprocessing is an essential step during metabolomic data analysis. Therefore, we developed an innovative optimization method to select a proper data preprocessing strategy for metabolomic data fusion using a design of experiment approach for improving the classification of prostate cancer (PCa) stages. In this study, urine and serum samples were collected from participants at five phases of PCa and analyzed using a 1 H NMR-based metabolomic approach. Partial least squares-discriminant analysis (PLS-DA) was used as a classification model and its performance was assessed by goodness of fit (R 2 ) and predictive ability (Q 2 ). Results show that data preprocessing significantly affect classification performance and depends on data properties. Using the fused metabolomic data from urine and serum, PLS-DA model with the optimal data preprocessing (R 2  = 0.729, Q 2  = 0.504, P < 0.0001) can effectively improve model performance and achieve a better classification result for PCa stages as compared with that without data preprocessing (R 2  = 0.139, Q 2  = 0.006, P = 0.450). Therefore, we propose that metabolomic data fusion integrated with an optimal data preprocessing strategy can significantly improve the classification of cancer stages for precision treatment. - Highlights: • NMR metabolomic analysis of body fluids can be used for staging prostate cancer. • Data preprocessing is an essential step for metabolomic analysis. • Data fusion improves information recovery for cancer classification. • Design of experiment achieves optimal preprocessing of metabolomic data fusion.

  13. Application of Numerical Integration and Data Fusion in Unit Vector Method

    Science.gov (United States)

    Zhang, J.

    2012-01-01

    The Unit Vector Method (UVM) is a series of orbit determination methods which are designed by Purple Mountain Observatory (PMO) and have been applied extensively. It gets the conditional equations for different kinds of data by projecting the basic equation to different unit vectors, and it suits for weighted process for different kinds of data. The high-precision data can play a major role in orbit determination, and accuracy of orbit determination is improved obviously. The improved UVM (PUVM2) promoted the UVM from initial orbit determination to orbit improvement, and unified the initial orbit determination and orbit improvement dynamically. The precision and efficiency are improved further. In this thesis, further research work has been done based on the UVM: Firstly, for the improvement of methods and techniques for observation, the types and decision of the observational data are improved substantially, it is also asked to improve the decision of orbit determination. The analytical perturbation can not meet the requirement. So, the numerical integration for calculating the perturbation has been introduced into the UVM. The accuracy of dynamical model suits for the accuracy of the real data, and the condition equations of UVM are modified accordingly. The accuracy of orbit determination is improved further. Secondly, data fusion method has been introduced into the UVM. The convergence mechanism and the defect of weighted strategy have been made clear in original UVM. The problem has been solved in this method, the calculation of approximate state transition matrix is simplified and the weighted strategy has been improved for the data with different dimension and different precision. Results of orbit determination of simulation and real data show that the work of this thesis is effective: (1) After the numerical integration has been introduced into the UVM, the accuracy of orbit determination is improved obviously, and it suits for the high-accuracy data of

  14. Summary report of IAEA technical meeting: 15. meeting of the IFRC Subcommittee on Atomic and Molecular Data for Fusion

    International Nuclear Information System (INIS)

    Clark, R.E.H.; Peacock, N.J.

    2007-02-01

    The 15th Meeting of the Subcommittee on Atomic and Molecular Data for Fusion of the International Fusion Research Council was held on 20-21 April 2006, at the IAEA Headquarters in Vienna, Austria. Work of the Atomic and Molecular Data Unit for the period 2004-2006 was reviewed, and recommendations were made for the 2008-2009 budget cycle. The proceedings, conclusions and recommendations of the Subcommittee meeting are briefly described in this report. Specific recommendations of the Subcommittee from this meeting, as well as the report on the activities of the IAEA Atomic and Molecular Data Unit for the period June 2004 - March 2006, are also included. (author)

  15. Towards a new generation of control and data acquisition systems for thermonuclear fusion research

    International Nuclear Information System (INIS)

    Van Haren, P.C.

    1993-01-01

    Because of the complexity of thermonuclear fusion test reactors, control systems are indispensable. The physical properties of the reactor medium, i.e. the plasma, are still not well understood. Therefore, many diagnostic techniques are applied to investigate the plasma and to discover its properties. As a consequence, data acquisition systems play an important role in thermonuclear fusion research. This thesis reports on three projects that were carried out in the field of control and data acquisition. The target experiment is the Rijnhuizen Tokamak Project (RTP), a medium-sized experiment dedicated to studies of transport in the reactor medium. One of the projects is aimed at the development of a new Plasma Position and Current Control feedback System (PPCCS). This system evaluates signals of a large (about 20) number of sensors, computes the actual state of the plasma from these signals and generates command signals for the power supplies that govern the plasma position. The most ambitious project described in this thesis is the development of a data acquisition system, called TRAMP (Transient Recorders and Amoeba Multi Processor), that aims to be a testbed for smart data acquisition strategies. TRAMP attempts to acquire and store temporarily all possible data at a high sampling frequency from a single RTP pulse, and accommodates for a resampling in software prior to transferring the data to a mass storage facility. The software resampling frequency can be tuned by analysis of the acquired data and, in that way, only interesting data will be stored. In the course of the development of both the above-mentioned systems it turned out that the existing database format applied for managing experimental data provided many hurdles in the realization of efficient solutions. Consequently, a new database format was developed together with software to deal with it. This new database, called DOM4 (Data Organization and Management), is now applied at all data acquisition

  16. Fusion Canada issue 28

    International Nuclear Information System (INIS)

    1995-06-01

    A short bulletin from the National Fusion Program highlighting in this issue the Canada - US fusion meeting in Montreal, fusion breeder work in Chile, new management at CFFTP, fast electrons in tokamaks: new data from TdeV, a program review of CCFM and Velikhov to address Montreal fusion meeting. 1 fig

  17. Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

    Science.gov (United States)

    Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

    2017-12-01

    Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

  18. Stochastic fusion of dynamic hydrological and geophysical data for estimating hydraulic conductivities: insights and observations (Invited)

    Science.gov (United States)

    Irving, J. D.; Singha, K.

    2010-12-01

    Traditionally, hydrological measurements have been used to estimate subsurface properties controlling groundwater flow and contaminant transport. However, such measurements are limited by their support volume and expense. A considerable benefit of geophysical measurements is that they provide a degree of spatial coverage and resolution that are unattainable with other methods, and the data can be acquired in a cost-effective manner. In particular, dynamic geophysical data allow us to indirectly observe changes in hydrological state variables as flow and transport processes occur, and can thus provide a link to hydrological properties when coupled with a process-based model. Stochastic fusion of these two data types offers the potential to provide not only estimates of subsurface hydrological properties, but also a quantification of their uncertainty. This information is critical when considering the end use of the data, which may be for groundwater remediation and management decision making. Here, we examine a number of key issues in the stochastic fusion of dynamic hydrogeophysical data. We focus our attention on the specific problem of integrating time-lapse crosshole electrical resistivity measurements and saline tracer-test concentration data in order to estimate the spatial distribution of hydraulic conductivity (K). To assimilate the geophysical and hydrological measurements in a stochastic manner, we use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology. This provides multiple realizations of the subsurface K field that are consistent with the measured data and assumptions regarding model structure and data errors. To account for incomplete petrophysical knowledge, the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration following the general form of Archie’s law. To make the spatially distributed, fully stochastic inverse problem computationally tractable, we take

  19. Compendium of structure and collision data in the first 12 issues of the international bulletin on atomic and molecular data for fusion

    International Nuclear Information System (INIS)

    Katsonis, K.; Rumble, J. Jr.

    1980-06-01

    This document is a compendium of the structure, spectra and collision data in the first 12 issues of the International Bulletin on Atomic and Molecular Data for Fusion. The Bulletin is issued quarterly by the International Atomic Energy Agency to assist the development of fusion research and technology. Not included in this compendium are those parts of the Bulletin concerned with Surface Effects, Work in Progress, Contributed Numerical Data, and Data Requests. Where necessary, corrections have been made to the data previously published to make the compendium as accurate as possible. The editors would appreciate any information on errors, duplications or omissions which would make future compendia more accurate and useful. (author)

  20. Atomic Data for Fusion: Volume 6, Spectroscopic data for titanium, chromium, and nickel

    International Nuclear Information System (INIS)

    Wiese, W.L.; Musgrove, A.

    1989-09-01

    Comprehensive spectroscopic data tables are presented for all ionization stages of chromium. Tables of ionization potentials, spectral lines, energy levels, and transition probabilities are presented. These tables contain data which have been excerpted from general critical compilations prepared under the sponsorship of the National Standard Reference Data System (NSRDS)

  1. Atomic Data for Fusion: Volume 6, Spectroscopic data for titanium, chromium, and nickel

    Energy Technology Data Exchange (ETDEWEB)

    Wiese, W.L.; Musgrove, A. (eds.) (National Inst. of Standards and Technology, Gaithersburg, MD (USA))

    1989-09-01

    Comprehensive spectroscopic data tables are presented for all ionization stages of chromium. Tables of ionization potentials, spectral lines, energy levels, and transition probabilities are presented. These tables contain data which have been excerpted from general critical compilations prepared under the sponsorship of the National Standard Reference Data System (NSRDS).

  2. Fusion of Terrestrial and Airborne Laser Data for 3D modeling Applications

    Science.gov (United States)

    Mohammed, Hani Mahmoud

    This thesis deals with the 3D modeling phase of the as-built large BIM projects. Among several means of BIM data capturing, such as photogrammetric or range tools, laser scanners have been one of the most efficient and practical tool for a long time. They can generate point clouds with high resolution for 3D models that meet nowadays' market demands. The current 3D modeling projects of as-built BIMs are mainly focused on using one type of laser scanner data, such as Airborne or Terrestrial. According to the literatures, no significant (few) efforts were made towards the fusion of heterogeneous laser scanner data despite its importance. The importance of the fusion of heterogeneous data arises from the fact that no single type of laser data can provide all the information about BIM, especially for large BIM projects that are existing on a large area, such as university buildings, or Heritage places. Terrestrial laser scanners are able to map facades of buildings and other terrestrial objects. However, they lack the ability to map roofs or higher parts in the BIM project. Airborne laser scanner on the other hand, can map roofs of the buildings efficiently and can map only small part of the facades. Short range laser scanners can map the interiors of the BIM projects, while long range scanners are used for mapping wide exterior areas in BIM projects. In this thesis the long range laser scanner data obtained in the Stop-and-Go mapping mode, the short range laser scanner data, obtained in a fully static mapping mode, and the airborne laser data are all fused together to bring a complete effective solution for a large BIM project. Working towards the 3D modeling of BIM projects, the thesis framework starts with the registration of the data, where a new fast automatic registration algorithm were developed. The next step is to recognize the different objects in the BIM project (classification), and obtain 3D models for the buildings. The last step is the development of an

  3. An Extension to Deng's Entropy in the Open World Assumption with an Application in Sensor Data Fusion.

    Science.gov (United States)

    Tang, Yongchuan; Zhou, Deyun; Chan, Felix T S

    2018-06-11

    Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belief entropy is still an open issue, even a blank field for the open world assumption. Currently, the existed uncertainty measures in the DST framework are limited to the closed world where the frame of discernment (FOD) is assumed to be complete. To address this issue, this paper focuses on extending a belief entropy to the open world by considering the uncertain information represented as the FOD and the nonzero mass function of the empty set simultaneously. An extension to Deng’s entropy in the open world assumption (EDEOW) is proposed as a generalization of the Deng’s entropy and it can be degenerated to the Deng entropy in the closed world wherever necessary. In order to test the reasonability and effectiveness of the extended belief entropy, an EDEOW-based information fusion approach is proposed and applied to sensor data fusion under uncertainty circumstance. The experimental results verify the usefulness and applicability of the extended measure as well as the modified sensor data fusion method. In addition, a few open issues still exist in the current work: the necessary properties for a belief entropy in the open world assumption, whether there exists a belief entropy that satisfies all the existed properties, and what is the most proper fusion frame for sensor data fusion under uncertainty.

  4. An Extension to Deng’s Entropy in the Open World Assumption with an Application in Sensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Yongchuan Tang

    2018-06-01

    Full Text Available Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST framework with belief entropy is still an open issue, even a blank field for the open world assumption. Currently, the existed uncertainty measures in the DST framework are limited to the closed world where the frame of discernment (FOD is assumed to be complete. To address this issue, this paper focuses on extending a belief entropy to the open world by considering the uncertain information represented as the FOD and the nonzero mass function of the empty set simultaneously. An extension to Deng’s entropy in the open world assumption (EDEOW is proposed as a generalization of the Deng’s entropy and it can be degenerated to the Deng entropy in the closed world wherever necessary. In order to test the reasonability and effectiveness of the extended belief entropy, an EDEOW-based information fusion approach is proposed and applied to sensor data fusion under uncertainty circumstance. The experimental results verify the usefulness and applicability of the extended measure as well as the modified sensor data fusion method. In addition, a few open issues still exist in the current work: the necessary properties for a belief entropy in the open world assumption, whether there exists a belief entropy that satisfies all the existed properties, and what is the most proper fusion frame for sensor data fusion under uncertainty.

  5. 1st IAEA research co-ordination meeting on charge exchange cross section data for fusion plasma studies. Summary report

    International Nuclear Information System (INIS)

    Janev, R.K.

    1999-02-01

    A brief description of the proceedings and the conclusions of the 1st Research Coordination Meeting on 'Charge Exchange Cross Section Data for Fusion Plasma Studies', held on September 24-25, 1999, at the IAEA Headquarters in Vienna, Austria, is provided. The conclusions of the Meeting regarding the data collection, assessment and generation priorities are also included in the report. (author)

  6. Olive oil sensory defects classification with data fusion of instrumental techniques and multivariate analysis (PLS-DA).

    Science.gov (United States)

    Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

    2016-07-15

    Three instrumental techniques, headspace-mass spectrometry (HS-MS), mid-infrared spectroscopy (MIR) and UV-visible spectrophotometry (UV-vis), have been combined to classify virgin olive oil samples based on the presence or absence of sensory defects. The reference sensory values were provided by an official taste panel. Different data fusion strategies were studied to improve the discrimination capability compared to using each instrumental technique individually. A general model was applied to discriminate high-quality non-defective olive oils (extra-virgin) and the lowest-quality olive oils considered non-edible (lampante). A specific identification of key off-flavours, such as musty, winey, fusty and rancid, was also studied. The data fusion of the three techniques improved the classification results in most of the cases. Low-level data fusion was the best strategy to discriminate musty, winey and fusty defects, using HS-MS, MIR and UV-vis, and the rancid defect using only HS-MS and MIR. The mid-level data fusion approach using partial least squares-discriminant analysis (PLS-DA) scores was found to be the best strategy for defective vs non-defective and edible vs non-edible oil discrimination. However, the data fusion did not sufficiently improve the results obtained by a single technique (HS-MS) to classify non-defective classes. These results indicate that instrumental data fusion can be useful for the identification of sensory defects in virgin olive oils. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

    Directory of Open Access Journals (Sweden)

    Karim Salahshoor

    2014-07-01

    Full Text Available This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT and extended Kalman filter (EKF. Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter for the final state estimation. The recent data are recursively utilized to apply wavelet transform and extract the variance of the updated data, which makes it suitable to be applied to both static and dynamic systems corrupted by noisy environments. The method has suitable performance in state estimation in comparison with the other alternative algorithms. A three-tank benchmark system has been adopted to comparatively demonstrate the performance merits of the method compared to a known algorithm in terms of efficiently satisfying signal-tonoise (SNR and minimum square error (MSE criteria.

  8. Efficient Error Detection in Soft Data Fusion for Cooperative Spectrum Sensing

    KAUST Repository

    Saqib Bhatti, Dost Muhammad

    2018-03-18

    The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.

  9. A data fusion approach for progressive damage quantification in reinforced concrete masonry walls

    International Nuclear Information System (INIS)

    Vanniamparambil, Prashanth Abraham; Carmi, Rami; Kontsos, Antonios; Bolhassani, Mohammad; Khan, Fuad; Bartoli, Ivan; Moon, Franklin L; Hamid, Ahmad

    2014-01-01

    This paper presents a data fusion approach based on digital image correlation (DIC) and acoustic emission (AE) to detect, monitor and quantify progressive damage development in reinforced concrete masonry walls (CMW) with varying types of reinforcements. CMW were tested to evaluate their structural behavior under cyclic loading. The combination of DIC with AE provided a framework for the cross-correlation of full field strain maps on the surface of CMW with volume-inspecting acoustic activity. AE allowed in situ monitoring of damage progression which was correlated with the DIC through quantification of strain concentrations and by tracking crack evolution, visually verified. The presented results further demonstrate the relationships between the onset and development of cracking with changes in energy dissipation at each loading cycle, measured principal strains and computed AE energy, providing a promising paradigm for structural health monitoring applications on full-scale concrete masonry buildings. (paper)

  10. Data Fusion Based on Optical Technology for Observation of Human Manipulation

    Science.gov (United States)

    Falco, Pietro; De Maria, Giuseppe; Natale, Ciro; Pirozzi, Salvatore

    2012-01-01

    The adoption of human observation is becoming more and more frequent within imitation learning and programming by demonstration approaches (PbD) to robot programming. For robotic systems equipped with anthropomorphic hands, the observation phase is very challenging and no ultimate solution exists. This work proposes a novel mechatronic approach to the observation of human hand motion during manipulation tasks. The strategy is based on the combined use of an optical motion capture system and a low-cost data glove equipped with novel joint angle sensors, based on optoelectronic technology. The combination of the two information sources is obtained through a sensor fusion algorithm based on the extended Kalman filter (EKF) suitably modified to tackle the problem of marker occlusions, typical of optical motion capture systems. This approach requires a kinematic model of the human hand. Another key contribution of this work is a new method to calibrate this model.

  11. Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

    Directory of Open Access Journals (Sweden)

    Rüdiger Dillmann

    2007-01-01

    Full Text Available Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media in Karlsruhe.

  12. Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

    Science.gov (United States)

    Steinhaus, Peter; Strand, Marcus; Dillmann, Rüdiger

    2007-12-01

    Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO) for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media) in Karlsruhe.

  13. Data Fusion and Visualization with the OpenEarth Framework (OEF)

    Science.gov (United States)

    Nadeau, D. R.; Baru, C.; Fouch, M. J.; Crosby, C. J.

    2010-12-01

    Data fusion is an increasingly important problem to solve as we strive to integrate data from multiple sources and build better models of the complex processes operating at the Earth’s surface and its interior. These data are often large, multi-dimensional, and subject to differing conventions for file formats, data structures, coordinate spaces, units of measure, and metadata organization. When visualized, these data require differing, and often conflicting, conventions for visual representations, dimensionality, icons, color schemes, labeling, and interaction. These issues make the visualization of fused Earth science data particularly difficult. The OpenEarth Framework (OEF) is an open-source data fusion and visualization suite of software being developed at the Supercomputer Center at the University of California, San Diego. Funded by the NSF, the project is leveraging virtual globe technology from NASA’s WorldWind to create interactive 3D visualization tools that combine layered data from a variety of sources to create a holistic view of features at, above, and beneath the Earth’s surface. The OEF architecture is cross-platform, multi-threaded, modular, and based upon Java. The OEF’s modular approach yields a collection of compatible mix-and-match components for assembling custom applications. Available modules support file format handling, web service communications, data management, data filtering, user interaction, and 3D visualization. File parsers handle a variety of formal and de facto standard file formats. Each one imports data into a general-purpose data representation that supports multidimensional grids, topography, points, lines, polygons, images, and more. From there these data then may be manipulated, merged, filtered, reprojected, and visualized. Visualization features support conventional and new visualization techniques for looking at topography, tomography, maps, and feature geometry. 3D grid data such as seismic tomography may be

  14. Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

    Science.gov (United States)

    Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

    2018-05-01

    Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

  15. NNDC [National Nuclear Data Center] support for fusion nuclear data needs

    International Nuclear Information System (INIS)

    Dunford, C.L.

    1988-01-01

    The National Data Center (NNDC) located at Brookhaven National Laboratory is an outgrowth of the Sigma Center founded by D.J. Hughes to compile low energy neutron reaction data in the 1950's. The center has played a lead role in the production of evaluated nuclear data (ENDF/B) for the United States nuclear power program. This data file, now in its sixth version, is produced as a cooperative effort of many DOE funded organizations via the Cross Section Evaluation Working Group (GSEWG). The NNDC's role, in addition to providing the structure and leadership for CSEWG, is to supply compiled bibliographic and experimental data and provide file processing, checking, distribution and documentation services. In the past, the NNDC has also produced nuclear data evaluations.lt. slash

  16. Copper benchmark experiment for the testing of JEFF-3.2 nuclear data for fusion applications

    Directory of Open Access Journals (Sweden)

    Angelone M.

    2017-01-01

    Full Text Available A neutronics benchmark experiment on a pure Copper block (dimensions 60 × 70 × 70 cm3 aimed at testing and validating the recent nuclear data libraries for fusion applications was performed in the frame of the European Fusion Program at the 14 MeV ENEA Frascati Neutron Generator (FNG. Reaction rates, neutron flux spectra and doses were measured using different experimental techniques (e.g. activation foils techniques, NE213 scintillator and thermoluminescent detectors. This paper first summarizes the analyses of the experiment carried-out using the MCNP5 Monte Carlo code and the European JEFF-3.2 library. Large discrepancies between calculation (C and experiment (E were found for the reaction rates both in the high and low neutron energy range. The analysis was complemented by sensitivity/uncertainty analyses (S/U using the deterministic and Monte Carlo SUSD3D and MCSEN codes, respectively. The S/U analyses enabled to identify the cross sections and energy ranges which are mostly affecting the calculated responses. The largest discrepancy among the C/E values was observed for the thermal (capture reactions indicating severe deficiencies in the 63,65Cu capture and elastic cross sections at lower rather than at high energy. Deterministic and MC codes produced similar results. The 14 MeV copper experiment and its analysis thus calls for a revision of the JEFF-3.2 copper cross section and covariance data evaluation. A new analysis of the experiment was performed with the MCNP5 code using the revised JEFF-3.3-T2 library released by NEA and a new, not yet distributed, revised JEFF-3.2 Cu evaluation produced by KIT. A noticeable improvement of the C/E results was obtained with both new libraries.

  17. Copper benchmark experiment for the testing of JEFF-3.2 nuclear data for fusion applications

    Science.gov (United States)

    Angelone, M.; Flammini, D.; Loreti, S.; Moro, F.; Pillon, M.; Villar, R.; Klix, A.; Fischer, U.; Kodeli, I.; Perel, R. L.; Pohorecky, W.

    2017-09-01

    A neutronics benchmark experiment on a pure Copper block (dimensions 60 × 70 × 70 cm3) aimed at testing and validating the recent nuclear data libraries for fusion applications was performed in the frame of the European Fusion Program at the 14 MeV ENEA Frascati Neutron Generator (FNG). Reaction rates, neutron flux spectra and doses were measured using different experimental techniques (e.g. activation foils techniques, NE213 scintillator and thermoluminescent detectors). This paper first summarizes the analyses of the experiment carried-out using the MCNP5 Monte Carlo code and the European JEFF-3.2 library. Large discrepancies between calculation (C) and experiment (E) were found for the reaction rates both in the high and low neutron energy range. The analysis was complemented by sensitivity/uncertainty analyses (S/U) using the deterministic and Monte Carlo SUSD3D and MCSEN codes, respectively. The S/U analyses enabled to identify the cross sections and energy ranges which are mostly affecting the calculated responses. The largest discrepancy among the C/E values was observed for the thermal (capture) reactions indicating severe deficiencies in the 63,65Cu capture and elastic cross sections at lower rather than at high energy. Deterministic and MC codes produced similar results. The 14 MeV copper experiment and its analysis thus calls for a revision of the JEFF-3.2 copper cross section and covariance data evaluation. A new analysis of the experiment was performed with the MCNP5 code using the revised JEFF-3.3-T2 library released by NEA and a new, not yet distributed, revised JEFF-3.2 Cu evaluation produced by KIT. A noticeable improvement of the C/E results was obtained with both new libraries.

  18. Active-passive data fusion algorithms for seafloor imaging and classification from CZMIL data

    Science.gov (United States)

    Park, Joong Yong; Ramnath, Vinod; Feygels, Viktor; Kim, Minsu; Mathur, Abhinav; Aitken, Jennifer; Tuell, Grady

    2010-04-01

    CZMIL will simultaneously acquire lidar and passive spectral data. These data will be fused to produce enhanced seafloor reflectance images from each sensor, and combined at a higher level to achieve seafloor classification. In the DPS software, the lidar data will first be processed to solve for depth, attenuation, and reflectance. The depth measurements will then be used to constrain the spectral optimization of the passive spectral data, and the resulting water column estimates will be used recursively to improve the estimates of seafloor reflectance from the lidar. Finally, the resulting seafloor reflectance cube will be combined with texture metrics estimated from the seafloor topography to produce classifications of the seafloor.

  19. IAEA technical committee meeting: 10th meeting of the IFRC subcommittee on atomic and molecular data for fusion. Summary report

    Energy Technology Data Exchange (ETDEWEB)

    Janev, R K

    1999-01-01

    This report describes briefly the proceedings and the conclusions and recommendations of the 10th Meeting of the Subcommittee on Atomic and Molecular Data for Fusion of the International Fusion Research Council held on May 27-28, 1998 at the IAEA Headquarters in Vienna, Austria. The report includes also the Executive Summary of the Subcommittee from this Meeting which was communicated to the IAEA Director General, and is appended with the Report on Activities of IAEA A+M Data Unit for the period July 1996 - May 1998. (author)

  20. IAEA technical committee meeting: 12th meeting of the IFRC Subcommittee on Atomic and Molecular Data for Fusion. Summary report

    Energy Technology Data Exchange (ETDEWEB)

    Clark, R E.H. [International Atomic Energy Agency, Vienna (Austria)

    2000-12-01

    This report briefly describes the proceedings, conclusions and recommendations of the 12th Meeting of the Subcommittee on Atomic and Molecular Data for Fusion of the International Fusion Research Council held on May 8-9, 2000 at the IAEA Headquarters in Vienna Austria. The report includes the Executive Summary of the Subcommittee from this Meeting which was communicated to the IAEA Director General as well as the report on the activities of the IAEA Atomic and Molecular Data Unit for the period June 1999 - May 2000. (author)

  1. IAEA technical committee meeting: 11th meeting of the IFRC subcommittee on atomic and molecular data for fusion. Summary report

    International Nuclear Information System (INIS)

    Janev, R.K.

    1999-05-01

    Brief description of the proceedings, conclusions and recommendations of the 11th Meeting of the Subcommittee on Atomic, Molecular (A+M) and Plasma-Material Interaction (PMI) Data for Fusion of the IAEA International Fusion Research Council (IFRC), held on May 3-4, 1999, at the IAEA Headquarters in Vienna, Austria, is provided. The report includes also the Executive Summary from the meeting and is appended with the Report on Activities of IAEA A+M/PMI Data Unit for the period May 1998 - May 1999. (author)

  2. Atomic data for heavy element impurities in fusion reactors. Summary report of first IAEA research co-ordination meeting

    International Nuclear Information System (INIS)

    Clark, R.E.H.

    2006-01-01

    Twelve international experts discussed in detail the properties of heavy elements relevant to fusion energy research participated at the first Research Coordination Meeting (RCM) of the Coordinated Research Project (CRP) on 'Atomic data for heavy element impurities in fusion reactors' at IAEA Headquarters on 14-15 November 2005. The participants summarized all recent relevant developments in their research efforts. Detailed discussions took place to formulate specific objectives for the CRP. From a list of data needs and a review of current research capabilities, a detailed work plan was formulated for the first phase of the CRP. The discussions, conclusions and recommendations of the RCM are briefly described in this report. (author)

  3. CDinFusion--submission-ready, on-line integration of sequence and contextual data.

    Directory of Open Access Journals (Sweden)

    Wolfgang Hankeln

    Full Text Available State of the art (DNA sequencing methods applied in "Omics" studies grant insight into the 'blueprints' of organisms from all domains of life. Sequencing is carried out around the globe and the data is submitted to the public repositories of the International Nucleotide Sequence Database Collaboration. However, the context in which these studies are conducted often gets lost, because experimental data, as well as information about the environment are rarely submitted along with the sequence data. If these contextual or metadata are missing, key opportunities of comparison and analysis across studies and habitats are hampered or even impossible. To address this problem, the Genomic Standards Consortium (GSC promotes checklists and standards to better describe our sequence data collection and to promote the capturing, exchange and integration of sequence data with contextual data. In a recent community effort the GSC has developed a series of recommendations for contextual data that should be submitted along with sequence data. To support the scientific community to significantly enhance the quality and quantity of contextual data in the public sequence data repositories, specialized software tools are needed. In this work we present CDinFusion, a web-based tool to integrate contextual and sequence data in (MultiFASTA format prior to submission. The tool is open source and available under the Lesser GNU Public License 3. A public installation is hosted and maintained at the Max Planck Institute for Marine Microbiology at http://www.megx.net/cdinfusion. The tool may also be installed locally using the open source code available at http://code.google.com/p/cdinfusion.

  4. CDinFusion--submission-ready, on-line integration of sequence and contextual data.

    Science.gov (United States)

    Hankeln, Wolfgang; Wendel, Norma Johanna; Gerken, Jan; Waldmann, Jost; Buttigieg, Pier Luigi; Kostadinov, Ivaylo; Kottmann, Renzo; Yilmaz, Pelin; Glöckner, Frank Oliver

    2011-01-01

    State of the art (DNA) sequencing methods applied in "Omics" studies grant insight into the 'blueprints' of organisms from all domains of life. Sequencing is carried out around the globe and the data is submitted to the public repositories of the International Nucleotide Sequence Database Collaboration. However, the context in which these studies are conducted often gets lost, because experimental data, as well as information about the environment are rarely submitted along with the sequence data. If these contextual or metadata are missing, key opportunities of comparison and analysis across studies and habitats are hampered or even impossible. To address this problem, the Genomic Standards Consortium (GSC) promotes checklists and standards to better describe our sequence data collection and to promote the capturing, exchange and integration of sequence data with contextual data. In a recent community effort the GSC has developed a series of recommendations for contextual data that should be submitted along with sequence data. To support the scientific community to significantly enhance the quality and quantity of contextual data in the public sequence data repositories, specialized software tools are needed. In this work we present CDinFusion, a web-based tool to integrate contextual and sequence data in (Multi)FASTA format prior to submission. The tool is open source and available under the Lesser GNU Public License 3. A public installation is hosted and maintained at the Max Planck Institute for Marine Microbiology at http://www.megx.net/cdinfusion. The tool may also be installed locally using the open source code available at http://code.google.com/p/cdinfusion.

  5. Reliability of measured data for pH sensor arrays with fault diagnosis and data fusion based on LabVIEW.

    Science.gov (United States)

    Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

    2013-12-13

    Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.

  6. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liao

    2013-12-01

    Full Text Available Fault diagnosis (FD and data fusion (DF technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2 sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.

  7. Data fusion for a vision-aided radiological detection system: Calibration algorithm performance

    Science.gov (United States)

    Stadnikia, Kelsey; Henderson, Kristofer; Martin, Allan; Riley, Phillip; Koppal, Sanjeev; Enqvist, Andreas

    2018-05-01

    In order to improve the ability to detect, locate, track and identify nuclear/radiological threats, the University of Florida nuclear detection community has teamed up with the 3D vision community to collaborate on a low cost data fusion system. The key is to develop an algorithm to fuse the data from multiple radiological and 3D vision sensors as one system. The system under development at the University of Florida is being assessed with various types of radiological detectors and widely available visual sensors. A series of experiments were devised utilizing two EJ-309 liquid organic scintillation detectors (one primary and one secondary), a Microsoft Kinect for Windows v2 sensor and a Velodyne HDL-32E High Definition LiDAR Sensor which is a highly sensitive vision sensor primarily used to generate data for self-driving cars. Each experiment consisted of 27 static measurements of a source arranged in a cube with three different distances in each dimension. The source used was Cf-252. The calibration algorithm developed is utilized to calibrate the relative 3D-location of the two different types of sensors without need to measure it by hand; thus, preventing operator manipulation and human errors. The algorithm can also account for the facility dependent deviation from ideal data fusion correlation. Use of the vision sensor to determine the location of a sensor would also limit the possible locations and it does not allow for room dependence (facility dependent deviation) to generate a detector pseudo-location to be used for data analysis later. Using manually measured source location data, our algorithm-predicted the offset detector location within an average of 20 cm calibration-difference to its actual location. Calibration-difference is the Euclidean distance from the algorithm predicted detector location to the measured detector location. The Kinect vision sensor data produced an average calibration-difference of 35 cm and the HDL-32E produced an average

  8. Atomic data for controlled fusion research. Volume IV. Spectroscopic data for iron

    Energy Technology Data Exchange (ETDEWEB)

    Wiese, W.L. (ed.)

    1985-02-01

    Comprehensive spectroscopic data tables are presented for all ions of Fe. Tables of ionization potentials, wave lengths of spectral lines, atomic energy levels, and transition probabilities are given which were excerpted from general critical compilations. All utilized compilations are less than five years old and include data on electric dipole as well as magnetic dipole transitions.

  9. Atomic data for controlled fusion research. Volume IV. Spectroscopic data for iron

    International Nuclear Information System (INIS)

    Wiese, W.L.

    1985-02-01

    Comprehensive spectroscopic data tables are presented for all ions of Fe. Tables of ionization potentials, wave lengths of spectral lines, atomic energy levels, and transition probabilities are given which were excerpted from general critical compilations. All utilized compilations are less than five years old and include data on electric dipole as well as magnetic dipole transitions

  10. Enhanced computational infrastructure for data analysis at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schissel, D.P.; Peng, Q.; Schachter, J.; Terpstra, T.B.; Casper, T.A.; Freeman, J.; Jong, R.; Keith, K.M.; McHarg, B.B.; Meyer, W.H.; Parker, C.T.

    2000-01-01

    Recently a number of enhancements to the computer hardware infrastructure have been implemented at the DIII-D National Fusion Facility. Utilizing these improvements to the hardware infrastructure, software enhancements are focusing on streamlined analysis, automation, and graphical user interface (GUI) systems to enlarge the user base. The adoption of the load balancing software package LSF Suite by Platform Computing has dramatically increased the availability of CPU cycles and the efficiency of their use. Streamlined analysis has been aided by the adoption of the MDSplus system to provide a unified interface to analyzed DIII-D data. The majority of MDSplus data is made available in between pulses giving the researcher critical information before setting up the next pulse. Work on data viewing and analysis tools focuses on efficient GUI design with object-oriented programming (OOP) for maximum code flexibility. Work to enhance the computational infrastructure at DIII-D has included a significant effort to aid the remote collaborator since the DIII-D National Team consists of scientists from nine national laboratories, 19 foreign laboratories, 16 universities, and five industrial partnerships. As a result of this work, DIII-D data is available on a 24x7 basis from a set of viewing and analysis tools that can be run on either the collaborators' or DIII-D's computer systems. Additionally, a web based data and code documentation system has been created to aid the novice and expert user alike

  11. Semi Automated Land Cover Layer Updating Process Utilizing Spectral Analysis and GIS Data Fusion

    Science.gov (United States)

    Cohen, L.; Keinan, E.; Yaniv, M.; Tal, Y.; Felus, A.; Regev, R.

    2018-04-01

    Technological improvements made in recent years of mass data gathering and analyzing, influenced the traditional methods of updating and forming of the national topographic database. It has brought a significant increase in the number of use cases and detailed geo information demands. Processes which its purpose is to alternate traditional data collection methods developed in many National Mapping and Cadaster Agencies. There has been significant progress in semi-automated methodologies aiming to facilitate updating of a topographic national geodatabase. Implementation of those is expected to allow a considerable reduction of updating costs and operation times. Our previous activity has focused on building automatic extraction (Keinan, Zilberstein et al, 2015). Before semiautomatic updating method, it was common that interpreter identification has to be as detailed as possible to hold most reliable database eventually. When using semi-automatic updating methodologies, the ability to insert human insights based knowledge is limited. Therefore, our motivations were to reduce the created gap by allowing end-users to add their data inputs to the basic geometric database. In this article, we will present a simple Land cover database updating method which combines insights extracted from the analyzed image, and a given spatial data of vector layers. The main stages of the advanced practice are multispectral image segmentation and supervised classification together with given vector data geometric fusion while maintaining the principle of low shape editorial work to be done. All coding was done utilizing open source software components.

  12. Enhanced Computational Infrastructure for Data Analysis at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schissel, D.P.; Peng, Q.; Schachter, J.; Terpstra, T.B.; Casper, T.A.; Freeman, J.; Jong, R.; Keith, K.M.; Meyer, W.H.; Parker, C.T.; McCharg, B.B.

    1999-01-01

    Recently a number of enhancements to the computer hardware infrastructure have been implemented at the DIII-D National Fusion Facility. Utilizing these improvements to the hardware infrastructure, software enhancements are focusing on streamlined analysis, automation, and graphical user interface (GUI) systems to enlarge the user base. The adoption of the load balancing software package LSF Suite by Platform Computing has dramatically increased the availability of CPU cycles and the efficiency of their use. Streamlined analysis has been aided by the adoption of the MDSplus system to provide a unified interface to analyzed DIII-D data. The majority of MDSplus data is made available in between pulses giving the researcher critical information before setting up the next pulse. Work on data viewing and analysis tools focuses on efficient GUI design with object-oriented programming (OOP) for maximum code flexibility. Work to enhance the computational infrastructure at DIII-D has included a significant effort to aid the remote collaborator since the DIII-D National Team consists of scientists from 9 national laboratories, 19 foreign laboratories, 16 universities, and 5 industrial partnerships. As a result of this work, DIII-D data is available on a 24 x 7 basis from a set of viewing and analysis tools that can be run either on the collaborators' or DIII-Ds computer systems. Additionally, a Web based data and code documentation system has been created to aid the novice and expert user alike

  13. ATCA/AXIe compatible board for fast control and data acquisition in nuclear fusion experiments

    International Nuclear Information System (INIS)

    Batista, A.J.N.; Leong, C.; Bexiga, V.; Rodrigues, A.P.; Combo, A.; Carvalho, B.B.; Fortunato, J.; Correia, M.; Teixeira, J.P.; Teixeira, I.C.; Sousa, J.; Gonçalves, B.; Varandas, C.A.F.

    2012-01-01

    Highlights: ► High performance board for fast control and data acquisition. ► Large IO channel number per board with galvanic isolation. ► Optimized for high reliability and availability. ► Targeted for nuclear fusion experiments with long duration discharges. ► To be used on the ITER Fast Plant System Controller prototype. - Abstract: An in-house development of an Advanced Telecommunications Computing Architecture (ATCA) board for fast control and data acquisition, with Input/Output (IO) processing capability, is presented. The architecture, compatible with the ATCA (PICMG 3.4) and ATCA eXtensions for Instrumentation (AXIe) specifications, comprises a passive Rear Transition Module (RTM) for IO connectivity to ease hot-swap maintenance and simultaneously to increase cabling life cycle. The board complies with ITER Fast Plant System Controller (FPSC) guidelines for rear IO connectivity and redundancy, in order to provide high levels of reliability and availability to the control and data acquisition systems of nuclear fusion devices with long duration plasma discharges. Simultaneously digitized data from all Analog to Digital Converters (ADC) of the board can be filtered/decimated in a Field Programmable Gate Array (FPGA), decreasing data throughput, increasing resolution, and sent through Peripheral Component Interconnect (PCI) Express to multi-core processors in the ATCA shelf hub slots. Concurrently the multi-core processors can update the board Digital to Analog Converters (DAC) in real-time. Full-duplex point-to-point communication links between all FPGAs, of peer boards inside the shelf, allow the implementation of distributed algorithms and Multi-Input Multi-Output (MIMO) systems. Support for several timing and synchronization solutions is also provided. Some key features are onboard ADC or DAC modules with galvanic isolation, Xilinx Virtex 6 FPGA, standard Dual Data Rate (DDR) 3 SODIMM memory, standard CompactFLASH memory card, Intelligent

  14. Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology

    Science.gov (United States)

    Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

    2017-01-01

    This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment. PMID:28714884

  15. Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

    Science.gov (United States)

    Hsu, Yu-Liang; Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

    2017-07-15

    This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.

  16. Virtual reality hardware for use in interactive 3D data fusion and visualization

    Science.gov (United States)

    Gourley, Christopher S.; Abidi, Mongi A.

    1997-09-01

    Virtual reality has become a tool for use in many areas of research. We have designed and built a VR system for use in range data fusion and visualization. One major VR tool is the CAVE. This is the ultimate visualization tool, but comes with a large price tag. Our design uses a unique CAVE whose graphics are powered by a desktop computer instead of a larger rack machine making it much less costly. The system consists of a screen eight feet tall by twenty-seven feet wide giving a variable field-of-view currently set at 160 degrees. A silicon graphics Indigo2 MaxImpact with the impact channel option is used for display. This gives the capability to drive three projectors at a resolution of 640 by 480 for use in displaying the virtual environment and one 640 by 480 display for a user control interface. This machine is also the first desktop package which has built-in hardware texture mapping. This feature allows us to quickly fuse the range and intensity data and other multi-sensory data. The final goal is a complete 3D texture mapped model of the environment. A dataglove, magnetic tracker, and spaceball are to be used for manipulation of the data and navigation through the virtual environment. This system gives several users the ability to interactively create 3D models from multiple range images.

  17. CLASSIFICATION OF CROPLANDS THROUGH FUSION OF OPTICAL AND SAR TIME SERIES DATA

    Directory of Open Access Journals (Sweden)

    S. Park

    2016-06-01

    Full Text Available Many satellite sensors including Landsat series have been extensively used for land cover classification. Studies have been conducted to mitigate classification problems associated with the use of single data (e.g., such as cloud contamination through multi-sensor data fusion and the use of time series data. This study investigated two areas with different environment and climate conditions: one in South Korea and the other in US. Cropland classification was conducted by using multi-temporal Landsat 5, Radarsat-1 and digital elevation models (DEM based on two machine learning approaches (i.e., random forest and support vector machines. Seven classification scenarios were examined and evaluated through accuracy assessment. Results show that SVM produced the best performance (overall accuracy of 93.87% when using all temporal and spectral data as input variables. Normalized Difference Water Index (NDWI, SAR backscattering, and Normalized Difference Vegetation Index (NDVI were identified as more contributing variables than the others for cropland classification.

  18. A data fusion framework for floodplain analysis using GIS and remotely sensed data

    Science.gov (United States)

    Necsoiu, Dorel Marius

    Throughout history floods have been part of the human experience. They are recurring phenomena that form a necessary and enduring feature of all river basin and lowland coastal systems. In an average year, they benefit millions of people who depend on them. In the more developed countries, major floods can be the largest cause of economic losses from natural disasters, and are also a major cause of disaster-related deaths in the less developed countries. Flood disaster mitigation research was conducted to determine how remotely sensed data can effectively be used to produce accurate flood plain maps (FPMs), and to identify/quantify the sources of error associated with such data. Differences were analyzed between flood maps produced by an automated remote sensing analysis tailored to the available satellite remote sensing datasets (rFPM), the 100-year flooded areas "predicted" by the Flood Insurance Rate Maps, and FPMs based on DEM and hydrological data (aFPM). Landuse/landcover was also examined to determine its influence on rFPM errors. These errors were identified and the results were integrated in a GIS to minimize landuse/landcover effects. Two substantial flood events were analyzed. These events were selected because of their similar characteristics (i.e., the existence of FIRM or Q3 data; flood data which included flood peaks, rating curves, and flood profiles; and DEM and remote sensing imagery). Automatic feature extraction was determined to be an important component for successful flood analysis. A process network, in conjunction with domain specific information, was used to map raw remotely sensed data onto a representation that is more compatible with a GIS data model. From a practical point of view, rFPM provides a way to automatically match existing data models to the type of remote sensing data available for each event under investigation. Overall, results showed how remote sensing could contribute to the complex problem of flood management by

  19. Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach

    Science.gov (United States)

    Kou, Leilei; Wang, Zhuihui; Xu, Fen

    2018-03-01

    The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite (TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar (GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network (NN)-based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method; interpolation of reflectivity data that are below PR's sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data: data with the NN method, data below PR's sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.

  20. Fusion of radar and optical data for mapping and monitoring of water bodies

    Science.gov (United States)

    Jenerowicz, Agnieszka; Siok, Katarzyn

    2017-10-01

    Remote sensing techniques owe their great popularity to the possibility to obtain of rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. The main areas of interest for remote sensing research had always been concerned with environmental studies, especially water bodies monitoring. Many methods that are using visible and near- an infrared band of the electromagnetic spectrum had been already developed to detect surface water reservoirs. Moreover, the usage of an image obtained in visible and infrared spectrum allows quality monitoring of water bodies. Nevertheless, retrieval of water boundaries and mapping surface water reservoirs with optical sensors is still quite demanding. Therefore, the microwave data could be the perfect complement to data obtained with passive optical sensors to detect and monitor aquatic environment especially surface water bodies. This research presents the methodology to detect water bodies with open- source satellite imagery acquired with both optical and microwave sensors. The SAR Sentinel- 1 and multispectral Sentinel- 2 imagery were used to detect and monitor chosen reservoirs in Poland. In the research Level, 1 Sentinel- 2 data and Level 1 SAR images were used. SAR data were mainly used for mapping water bodies. Next, the results of water boundaries extraction with Sentinel-1 data were compared to results obtained after application of modified spectral indices for Sentinel- 2 data. The multispectral optical data can be used in the future for the evaluation of the quality of the reservoirs. Preliminary results obtained in the research had shown, that the fusion of data obtained with optical and microwave sensors allow for the complex detection of water bodies and could be used in the future quality monitoring of water reservoirs.