Science.gov

Sample records for quark-parton model framework

  1. The description of inclusive characteristics inbar pp interactions at 22.4 GeV/ c in terms of the quark-parton model

    NASA Astrophysics Data System (ADS)

    Batyunya, B. V.; Boguslavsky, I. V.; Gramenitsky, I. M.; Lednický, R.; Levonian, S. V.; Tikhonova, L. A.; Valkárová, A.; Vrba, V.; Zlatanov, Z.; Boos, E. G.; Samoilov, V. V.; Takibaev, Zh. S.; Temiraliev, T.; Lichard, P.; Mašejová, A.; Dumbrajs, S.; Ervanne, J.; Hannula, E.; Villanen, P.; Dementiev, R. K.; Korzhavina, I. A.; Leikin, E. M.; Rud, V. I.; Herynek, I.; Reimer, P.; Řídký, J.; Sedlák, J.; Šimák, V.; Suk, M.; Khudzadze, A. M.; Kuratashvili, G. O.; Topuriya, T. P.; Tzintzadze, V. D.

    1980-03-01

    We compare the inclusive characteristics ofbar pp interactions at 22.4 GeV/ c with quark-parton model predictions in terms of collective variables. The model qualitatively agrees with the data in contradiction to the simple cylindrical phase space and randomized charge model. The ways are proposed of a further development of the quark-parton model.

  2. Semi-inclusive charged-pion electroproduction off protons and deuterons: Cross sections, ratios, and access to the quark-parton model at low energies

    DOE PAGES

    Asaturyan, R.; Ent, R.; Mkrtchyan, H.; ...

    2012-01-01

    A large set of cross sections for semi-inclusive electroproduction of charged pions (π±) from both proton and deuteron targets was measured. The data are in the deep-inelastic scattering region with invariant mass squared W2 > 4 GeV2 and range in four-momentum transfer squared 2 < Q2 < 4 (GeV/c)2, and cover a range in the Bjorken scaling variable 0.2 < x < 0.6. The fractional energy of the pions spans a range 0.3 < z < 1, with small transverse momenta with respect to the virtual-photon direction, Pt2 < 0.2 (GeV/c)2. The invariant mass that goes undetected, Mx or W',more » is in the nucleon resonance region, W' < 2 GeV. The new data conclusively show the onset of quark-hadron duality in this process, and the relation of this phenomenon to the high-energy factorization ansatz of electron-quark scattering and subsequent quark → pion production mechanisms. The x, z and Pt2 dependences of several ratios (the ratios of favored-unfavored fragmentation functions, charged pion ratios, deuteron-hydrogen and aluminum-deuteron ratios for π+ and π-) have been studied. The ratios are found to be in good agreement with expectations based upon a high-energy quark-parton model description. We find the azimuthal dependences to be small, as compared to exclusive pion electroproduction, and consistent with theoretical expectations based on tree-level factorization in terms of transverse-momentum-dependent parton distribution and fragmentation functions. In the context of a simple model, the initial transverse momenta of d quarks are found to be slightly smaller than for u quarks, while the transverse momentum width of the favored fragmentation function is about the same as for the unfavored one, and both fragmentation widths are larger than the quark widths.« less

  3. Semi-inclusive charged-pion electroproduction off protons and deuterons: Cross sections, ratios, and access to the quark-parton model at low energies

    SciTech Connect

    Asaturyan, R.; Ent, R.; Mkrtchyan, H.; Navasardyan, T.; Tadevosyan, V.; Adams, G. S.; Ahmidouch, A.; Angelescu, T.; Arrington, J.; Asaturyan, A.; Baker, O. K.; Benmouna, N.; Bertoncini, C.; Blok, H. P.; Boeglin, W. U.; Bosted, P. E.; Breuer, H.; Christy, M. E.; Connell, S. H.; Cui, Y.; Dalton, M. M.; Danagoulian, S.; Day, D.; Dunne, J. A.; Dutta, D.; El Khayari, N.; Fenker, H. C.; Frolov, V. V.; Gan, L.; Gaskell, D.; Hafidi, K.; Hinton, W.; Holt, R. J.; Horn, T.; Huber, G. M.; Hungerford, E.; Jiang, X.; Jones, M.; Joo, K.; Kalantarians, N.; Kelly, J. J.; Keppel, C. E.; Kubarovsky, V.; Li, Y.; Liang, Y.; Mack, D.; Malace, S. P.; Markowitz, P.; McGrath, E.; McKee, P.; Meekins, D. G.; Mkrtchyan, A.; Moziak, B.; Niculescu, G.; Niculescu, I.; Opper, A. K.; Ostapenko, T.; Reimer, P. E.; Reinhold, J.; Roche, J.; Rock, S. E.; Schulte, E.; Segbefia, E.; Smith, C.; Smith, G. R.; Stoler, P.; Tang, L.; Ungaro, M.; Uzzle, A.; Vidakovic, S.; Villano, A.; Vulcan, W. F.; Wang, M.; Warren, G.; Wesselmann, F. R.; Wojtsekhowski, B.; Wood, S. A.; Xu, C.; Yuan, L.; Zheng, X.

    2012-01-01

    A large set of cross sections for semi-inclusive electroproduction of charged pions (π±) from both proton and deuteron targets was measured. The data are in the deep-inelastic scattering region with invariant mass squared W2 > 4 GeV2 and range in four-momentum transfer squared 2 < Q2 < 4 (GeV/c)2, and cover a range in the Bjorken scaling variable 0.2 < x < 0.6. The fractional energy of the pions spans a range 0.3 < z < 1, with small transverse momenta with respect to the virtual-photon direction, Pt2 < 0.2 (GeV/c)2. The invariant mass that goes undetected, Mx or W', is in the nucleon resonance region, W' < 2 GeV. The new data conclusively show the onset of quark-hadron duality in this process, and the relation of this phenomenon to the high-energy factorization ansatz of electron-quark scattering and subsequent quark → pion production mechanisms. The x, z and Pt2 dependences of several ratios (the ratios of favored-unfavored fragmentation functions, charged pion ratios, deuteron-hydrogen and aluminum-deuteron ratios for π+ and π-) have been studied. The ratios are found to be in good agreement with expectations based upon a high-energy quark-parton model description. We find the azimuthal dependences to be small, as compared to exclusive pion electroproduction, and consistent with theoretical expectations based on tree-level factorization in terms of transverse-momentum-dependent parton distribution and fragmentation functions. In the context of a simple model, the initial transverse momenta of d quarks are found to be slightly smaller than for u quarks, while the transverse momentum width of the favored fragmentation function is about the same as for the unfavored one, and both fragmentation widths are larger than the quark widths.

  4. Pion and kaon valence-quark parton distribution functions.

    SciTech Connect

    Nguyen, T.; Bashir, A.; Roberts, C. D.; Tandy, P. C.

    2011-06-16

    A rainbow-ladder truncation of QCD's Dyson-Schwinger equations, constrained by existing applications to hadron physics, is employed to compute the valence-quark parton distribution functions of the pion and kaon. Comparison is made to {pi}-N Drell-Yan data for the pion's u-quark distribution and to Drell-Yan data for the ratio u{sub K}(x)/u{sub {pi}}(x): the environmental influence of this quantity is a parameter-free prediction, which agrees well with existing data. Our analysis unifies the computation of distribution functions with that of numerous other properties of pseudoscalar mesons.

  5. Pion and kaon valence-quark parton distribution functions

    SciTech Connect

    Nguyen, Trang; Bashir, Adnan; Roberts, Craig D.; Tandy, Peter C.

    2011-06-15

    A rainbow-ladder truncation of QCD's Dyson-Schwinger equations, constrained by existing applications to hadron physics, is employed to compute the valence-quark parton distribution functions of the pion and kaon. Comparison is made to {pi}-N Drell-Yan data for the pion's u-quark distribution and to Drell-Yan data for the ratio u{sub K}(x)/u{sub {pi}}(x): the environmental influence of this quantity is a parameter-free prediction, which agrees well with existing data. Our analysis unifies the computation of distribution functions with that of numerous other properties of pseudoscalar mesons.

  6. Strange quark parton distribution functions and implications for Drell-Yan boson production at the LHC

    NASA Astrophysics Data System (ADS)

    Kusina, A.; Stavreva, T.; Berge, S.; Olness, F. I.; Schienbein, I.; Kovařík, K.; Ježo, T.; Yu, J. Y.; Park, K.

    2012-05-01

    Global analyses of parton distribution functions (PDFs) have provided incisive constraints on the up and down quark components of the proton, but constraining the other flavor degrees of freedom is more challenging. Higher-order theory predictions and new data sets have contributed to recent improvements. Despite these efforts, the strange quark parton distribution function has a sizable uncertainty, particularly in the small x region. We examine the constraints from experiment and theory, and investigate the impact of this uncertainty on LHC observables. In particular, we study W/Z production to see how the s quark uncertainty propagates to these observables, and examine the extent to which precise measurements at the LHC can provide additional information on the proton flavor structure.

  7. EPA'S NEW EMISSIONS MODELING FRAMEWORK

    EPA Science Inventory

    EPA's Office of Air Quality Planning and Standards is building a new Emissions Modeling Framework that will solve many of the long-standing difficulties of emissions modeling. The goals of the Framework are to (1) prevent bottlenecks and errors caused by emissions modeling activi...

  8. Dicyanometallates as Model Extended Frameworks

    PubMed Central

    2016-01-01

    We report the structures of eight new dicyanometallate frameworks containing molecular extra-framework cations. These systems include a number of hybrid inorganic–organic analogues of conventional ceramics, such as Ruddlesden–Popper phases and perovskites. The structure types adopted are rationalized in the broader context of all known dicyanometallate framework structures. We show that the structural diversity of this family can be understood in terms of (i) the charge and coordination preferences of the particular metal cation acting as framework node, and (ii) the size, shape, and extent of incorporation of extra-framework cations. In this way, we suggest that dicyanometallates form a particularly attractive model family of extended frameworks in which to explore the interplay between molecular degrees of freedom, framework topology, and supramolecular interactions. PMID:27057759

  9. Dicyanometallates as Model Extended Frameworks.

    PubMed

    Hill, Joshua A; Thompson, Amber L; Goodwin, Andrew L

    2016-05-11

    We report the structures of eight new dicyanometallate frameworks containing molecular extra-framework cations. These systems include a number of hybrid inorganic-organic analogues of conventional ceramics, such as Ruddlesden-Popper phases and perovskites. The structure types adopted are rationalized in the broader context of all known dicyanometallate framework structures. We show that the structural diversity of this family can be understood in terms of (i) the charge and coordination preferences of the particular metal cation acting as framework node, and (ii) the size, shape, and extent of incorporation of extra-framework cations. In this way, we suggest that dicyanometallates form a particularly attractive model family of extended frameworks in which to explore the interplay between molecular degrees of freedom, framework topology, and supramolecular interactions.

  10. Geologic Framework Model (GFM2000)

    SciTech Connect

    T. Vogt

    2004-08-26

    The purpose of this report is to document the geologic framework model, version GFM2000 with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, and the differences between GFM2000 and previous versions. The version number of this model reflects the year during which the model was constructed. This model supersedes the previous model version, documented in Geologic Framework Model (GFM 3.1) (CRWMS M&O 2000 [DIRS 138860]). The geologic framework model represents a three-dimensional interpretation of the geology surrounding the location of the monitored geologic repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain. The geologic framework model encompasses and is limited to an area of 65 square miles (168 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the geologic framework model (shown in Figure 1-1) were chosen to encompass the exploratory boreholes and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The upper surface of the model is made up of the surface topography and the depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The geologic framework model was constructed from geologic map and borehole data. Additional information from measured stratigraphic sections, gravity profiles, and seismic profiles was also considered. The intended use of the geologic framework model is to provide a geologic framework over the area of interest consistent with the level of detailed needed for hydrologic flow and radionuclide transport modeling through the UZ and for repository design. The model is limited by the availability of data and relative amount of geologic complexity found in an area. The geologic framework model is inherently limited by scale and content. The grid spacing used in the

  11. Environmental modeling framework invasiveness: analysis and implications

    USDA-ARS?s Scientific Manuscript database

    Environmental modeling frameworks support scientific model development by providing an Application Programming Interface (API) which model developers use to implement models. This paper presents results of an investigation on the framework invasiveness of environmental modeling frameworks. Invasiv...

  12. Environmental modeling framework invasiveness: analysis and implications

    USDA-ARS?s Scientific Manuscript database

    Environmental modeling frameworks support scientific model development by providing an Application Programming Interface (API) which model developers use to implement models. This paper presents results of an investigation on the framework invasiveness of environmental modeling frameworks. Invasiven...

  13. Sequentially Executed Model Evaluation Framework

    SciTech Connect

    2014-02-14

    Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and 1/0 through the time domain (or other discrete domain), and sample 1/0 drivers. This is a Framework library framework, and does not, itself, solve any problems or execute any modelling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Ha) applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed

  14. Sequentially Executed Model Evaluation Framework

    SciTech Connect

    2014-02-14

    Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and 1/0 through the time domain (or other discrete domain), and sample 1/0 drivers. This is a Framework library framework, and does not, itself, solve any problems or execute any modelling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Ha) applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed

  15. CMAQ Model Evaluation Framework

    EPA Pesticide Factsheets

    CMAQ is tested to establish the modeling system’s credibility in predicting pollutants such as ozone and particulate matter. Evaluation of CMAQ has been designed to assess the model’s performance for specific time periods and for specific uses.

  16. Sequentially Executed Model Evaluation Framework

    SciTech Connect

    2015-10-20

    Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and I/O through the time domain (or other discrete domain), and sample I/O drivers. This is a library framework, and does not, itself, solve any problems or execute any modeling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Has applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed for anomalies.

  17. Sequentially Executed Model Evaluation Framework

    SciTech Connect

    2015-10-20

    Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and I/O through the time domain (or other discrete domain), and sample I/O drivers. This is a library framework, and does not, itself, solve any problems or execute any modeling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Has applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed for anomalies.

  18. Framework for Modeling the Cognitive Process

    DTIC Science & Technology

    2005-06-16

    Yaworsky Air Force Research Laboratory/IFSB Rome, NY Keywords: Cognitive Process Modeling, Cognition, Conceptual Framework , Information...center of our conceptual framework and will distinguish our use of terms within the context of this framework. 3. A Conceptual Framework for...Modeling the Cognitive Process We will describe our conceptual framework using graphical examples to help illustrate main points. We form the two

  19. Geologic Framework Model Analysis Model Report

    SciTech Connect

    R. Clayton

    2000-12-19

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M&O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and the

  20. Deriving Framework Usages Based on Behavioral Models

    NASA Astrophysics Data System (ADS)

    Zenmyo, Teruyoshi; Kobayashi, Takashi; Saeki, Motoshi

    One of the critical issue in framework-based software development is a huge introduction cost caused by technical gap between developers and users of frameworks. This paper proposes a technique for deriving framework usages to implement a given requirements specification. By using the derived usages, the users can use the frameworks without understanding the framework in detail. Requirements specifications which describe definite behavioral requirements cannot be related to frameworks in as-is since the frameworks do not have definite control structure so that the users can customize them to suit given requirements specifications. To cope with this issue, a new technique based on satisfiability problems (SAT) is employed to derive the control structures of the framework model. In the proposed technique, requirements specifications and frameworks are modeled based on Labeled Transition Systems (LTSs) with branch conditions represented by predicates. Truth assignments of the branch conditions in the framework models are not given initially for representing the customizable control structure. The derivation of truth assignments of the branch conditions is regarded as the SAT by assuming relations between termination states of the requirements specification model and ones of the framework model. This derivation technique is incorporated into a technique we have proposed previously for relating actions of requirements specifications to ones of frameworks. Furthermore, this paper discuss a case study of typical use cases in e-commerce systems.

  1. A UML profile for framework modeling.

    PubMed

    Xu, Xiao-liang; Wang, Le-yu; Zhou, Hong

    2004-01-01

    The current standard Unified Modeling Language(UML) could not model framework flexibility and extendability adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.

  2. Reducing the invasiveness of modelling frameworks

    NASA Astrophysics Data System (ADS)

    Donchyts, G.; Baart, F.

    2010-12-01

    There are several modelling frameworks available that allow for environmental models to exchange data with other models. Many efforts have been made in the past years promoting solutions aimed at integrating different numerical models with each other as well as at simplifying the way to set them up, entering the data, and running them. Meanwhile the development of many modeling frameworks concentrated on the interoperability of different model engines, several standards were introduced such as ESMF, OMS and OpenMI. One of the issues with applying modelling frameworks is the invasessness, the more the model has to know about the framework, the more intrussive it is. Another issue when applying modelling frameworks are that a lot of environmental models are written in procedural and in FORTRAN, which is one of the few languages that doesn't have a proper interface with other programming languages. Most modelling frameworks are written in object oriented languages like java/c# and the modelling framework in FORTRAN ESMF is also objected oriented. In this research we show how the application of domain driven, object oriented development techniques to environmental models can reduce the invasiveness of modelling frameworks. Our approach is based on four different steps: 1) application of OO techniques and reflection to the existing model to allow introspection. 2) programming language interoperability, between model written in a procedural programming language and modeling framework written in an object oriented programming language. 3) Domain mapping between data types used by model and other components being integrated 4) Connecting models using framework (wrapper) We compare coupling of an existing model as it was to the same model adapted using the four step approach. We connect both versions of the models using two different integrated modelling frameworks. As an example of a model we use the coastal morphological model XBeach. By adapting this model it allows for

  3. The Generalized DINA Model Framework

    ERIC Educational Resources Information Center

    de la Torre, Jimmy

    2011-01-01

    The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…

  4. The Generalized DINA Model Framework

    ERIC Educational Resources Information Center

    de la Torre, Jimmy

    2011-01-01

    The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…

  5. Knowledge Encapsulation Framework for Collaborative Social Modeling

    SciTech Connect

    Cowell, Andrew J.; Gregory, Michelle L.; Marshall, Eric J.; McGrath, Liam R.

    2009-03-24

    This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable knowledge inputs (relevant, domain-specific facts) to modeling and simulation projects, as well as other domains that require effective collaborative workspaces for knowledge-based task. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.

  6. Rethinking modeling framework design: object modeling system 3.0

    USDA-ARS?s Scientific Manuscript database

    The Object Modeling System (OMS) is a framework for environmental model development, data provisioning, testing, validation, and deployment. It provides a bridge for transferring technology from the research organization to the program delivery agency. The framework provides a consistent and efficie...

  7. A Framework to Manage Information Models

    NASA Astrophysics Data System (ADS)

    Hughes, J. S.; King, T.; Crichton, D.; Walker, R.; Roberts, A.; Thieman, J.

    2008-05-01

    The Information Model is the foundation on which an Information System is built. It defines the entities to be processed, their attributes, and the relationships that add meaning. The development and subsequent management of the Information Model is the single most significant factor for the development of a successful information system. A framework of tools has been developed that supports the management of an information model with the rigor typically afforded to software development. This framework provides for evolutionary and collaborative development independent of system implementation choices. Once captured, the modeling information can be exported to common languages for the generation of documentation, application databases, and software code that supports both traditional and semantic web applications. This framework is being successfully used for several science information modeling projects including those for the Planetary Data System (PDS), the International Planetary Data Alliance (IPDA), the National Cancer Institute's Early Detection Research Network (EDRN), and several Consultative Committee for Space Data Systems (CCSDS) projects. The objective of the Space Physics Archive Search and Exchange (SPASE) program is to promote collaboration and coordination of archiving activity for the Space Plasma Physics community and ensure the compatibility of the architectures used for a global distributed system and the individual data centers. Over the past several years, the SPASE data model working group has made great progress in developing the SPASE Data Model and supporting artifacts including a data dictionary, XML Schema, and two ontologies. The authors have captured the SPASE Information Model in this framework. This allows the generation of documentation that presents the SPASE Information Model in object-oriented notation including UML class diagrams and class hierarchies. The modeling information can also be exported to semantic web languages such

  8. Modelling Diffusion of a Personalized Learning Framework

    ERIC Educational Resources Information Center

    Karmeshu; Raman, Raghu; Nedungadi, Prema

    2012-01-01

    A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis,…

  9. Modelling Diffusion of a Personalized Learning Framework

    ERIC Educational Resources Information Center

    Karmeshu; Raman, Raghu; Nedungadi, Prema

    2012-01-01

    A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis,…

  10. Multiple Mentor Model: A Conceptual Framework.

    ERIC Educational Resources Information Center

    Burlew, Larry D.

    1991-01-01

    Focuses on developing a conceptual framework for the mentoring process. The model is based on the premise that mentoring is not a single event in the life of a worker but rather several events with several different levels of mentoring. (Author)

  11. CAN A MODEL TRANSFERABILITY FRAMEWORK IMPROVE ...

    EPA Pesticide Factsheets

    Budget constraints and policies that limit primary data collection have fueled a practice of transferring estimates (or models to generate estimates) of ecological endpoints from sites where primary data exists to sites where little to no primary data were collected. Whereas benefit transfer has been well studied; there is no comparable framework for evaluating whether model transfer between sites is justifiable. We developed and applied a transferability assessment framework to a case study involving forest carbon sequestration for soils in Tillamook Bay, Oregon. The carbon sequestration capacity of forested watersheds is an important ecosystem service in the effort to reduce atmospheric greenhouse gas emissions. We used our framework, incorporating three basic steps (model selection, defining context variables, assessing logistical constraints) for evaluating model transferability, to compare estimates of carbon storage capacity derived from two models, COMET-Farm and Yasso. We applied each model to Tillamook Bay and compared results to data extracted from the Soil Survey Geographic Database (SSURGO) using ArcGIS. Context variables considered were: geographic proximity to Tillamook, dominant tree species, climate and soil type. Preliminary analyses showed that estimates from COMET-Farm were more similar to SSURGO data, likely because model context variables (e.g. proximity to Tillamook and dominant tree species) were identical to those in Tillamook. In contras

  12. An Extensible Model and Analysis Framework

    DTIC Science & Technology

    2010-11-01

    of a pre-existing, open-source modeling and analysis framework known as Ptolemy II (http://ptolemy.org). The University of California, Berkeley...worked with the Air Force Research Laboratory, Rome Research Site on adapting Ptolemy II for modeling and simulation of large scale dynamics of Political...capabilities were prototyped in Ptolemy II and delivered via version control and software releases. Each of these capabilities specifically supports one or

  13. Overarching framework for data-based modelling

    NASA Astrophysics Data System (ADS)

    Schelter, Björn; Mader, Malenka; Mader, Wolfgang; Sommerlade, Linda; Platt, Bettina; Lai, Ying-Cheng; Grebogi, Celso; Thiel, Marco

    2014-02-01

    One of the main modelling paradigms for complex physical systems are networks. When estimating the network structure from measured signals, typically several assumptions such as stationarity are made in the estimation process. Violating these assumptions renders standard analysis techniques fruitless. We here propose a framework to estimate the network structure from measurements of arbitrary non-linear, non-stationary, stochastic processes. To this end, we propose a rigorous mathematical theory that underlies this framework. Based on this theory, we present a highly efficient algorithm and the corresponding statistics that are immediately sensibly applicable to measured signals. We demonstrate its performance in a simulation study. In experiments of transitions between vigilance stages in rodents, we infer small network structures with complex, time-dependent interactions; this suggests biomarkers for such transitions, the key to understand and diagnose numerous diseases such as dementia. We argue that the suggested framework combines features that other approaches followed so far lack.

  14. An evaluation framework for participatory modelling

    NASA Astrophysics Data System (ADS)

    Krueger, T.; Inman, A.; Chilvers, J.

    2012-04-01

    Strong arguments for participatory modelling in hydrology can be made on substantive, instrumental and normative grounds. These arguments have led to increasingly diverse groups of stakeholders (here anyone affecting or affected by an issue) getting involved in hydrological research and the management of water resources. In fact, participation has become a requirement of many research grants, programs, plans and policies. However, evidence of beneficial outcomes of participation as suggested by the arguments is difficult to generate and therefore rare. This is because outcomes are diverse, distributed, often tacit, and take time to emerge. In this paper we develop an evaluation framework for participatory modelling focussed on learning outcomes. Learning encompasses many of the potential benefits of participation, such as better models through diversity of knowledge and scrutiny, stakeholder empowerment, greater trust in models and ownership of subsequent decisions, individual moral development, reflexivity, relationships, social capital, institutional change, resilience and sustainability. Based on the theories of experiential, transformative and social learning, complemented by practitioner experience our framework examines if, when and how learning has occurred. Special emphasis is placed on the role of models as learning catalysts. We map the distribution of learning between stakeholders, scientists (as a subgroup of stakeholders) and models. And we analyse what type of learning has occurred: instrumental learning (broadly cognitive enhancement) and/or communicative learning (change in interpreting meanings, intentions and values associated with actions and activities; group dynamics). We demonstrate how our framework can be translated into a questionnaire-based survey conducted with stakeholders and scientists at key stages of the participatory process, and show preliminary insights from applying the framework within a rural pollution management situation in

  15. Improvements in the Space Weather Modeling Framework

    NASA Astrophysics Data System (ADS)

    Ridley, A. J.; Liemohn, M.; Dezeeuw, D.; Ilie, R.; Sokolov, I.; Toth, G.; Yu, Y.

    2008-12-01

    The magnetosphere within the Space Weather Modeling Framework (SWMF) has been represented by a global magnetosphere model (BATSRUS), an inner magnetosphere model (the Rice Convection Model) and a model of the ionospheric electrodynamics. We present significant improvements in the SWMF: (1) We have implemented a spherical grid within BATSRUS and have utilized this for modeling the magnetosphere; (2) We have significantly improved the physics of the auroral oval within the ionospheric electrodynamics code, modeling a self-consistent diffuse and discrete auroral oval; (3) We utilize the multifluid MHD code within BATSRUS to allow for more accurate specification and differentiation of the density within the magnetosphere; and (4) we have incorporated the Hot Electron and Ion Drift Integrator (HEIDI) ring current code within the SWMF. We will present these improvements and show the quantitative differences within the model results when comparing to a suite of measurements for a number of different intervals.

  16. Talking Cure Models: A Framework of Analysis

    PubMed Central

    Marx, Christopher; Benecke, Cord; Gumz, Antje

    2017-01-01

    Psychotherapy is commonly described as a “talking cure,” a treatment method that operates through linguistic action and interaction. The operative specifics of therapeutic language use, however, are insufficiently understood, mainly due to a multitude of disparate approaches that advance different notions of what “talking” means and what “cure” implies in the respective context. Accordingly, a clarification of the basic theoretical structure of “talking cure models,” i.e., models that describe therapeutic processes with a focus on language use, is a desideratum of language-oriented psychotherapy research. Against this background the present paper suggests a theoretical framework of analysis which distinguishes four basic components of “talking cure models”: (1) a foundational theory (which suggests how linguistic activity can affect and transform human experience), (2) an experiential problem state (which defines the problem or pathology of the patient), (3) a curative linguistic activity (which defines linguistic activities that are supposed to effectuate a curative transformation of the experiential problem state), and (4) a change mechanism (which defines the processes and effects involved in such transformations). The purpose of the framework is to establish a terminological foundation that allows for systematically reconstructing basic properties and operative mechanisms of “talking cure models.” To demonstrate the applicability and utility of the framework, five distinct “talking cure models” which spell out the details of curative “talking” processes in terms of (1) catharsis, (2) symbolization, (3) narrative, (4) metaphor, and (5) neurocognitive inhibition are introduced and discussed in terms of the framework components. In summary, we hope that our framework will prove useful for the objective of clarifying the theoretical underpinnings of language-oriented psychotherapy research and help to establish a more comprehensive

  17. A framework for benchmarking land models

    SciTech Connect

    Luo, Yiqi; Randerson, J.; Abramowitz, G.; Bacour, C.; Blyth, E.; Carvalhais, N.; Ciais, Philippe; Dalmonech, D.; Fisher, J.B.; Fisher, R.; Friedlingstein, P.; Hibbard, Kathleen A.; Hoffman, F. M.; Huntzinger, Deborah; Jones, C.; Koven, C.; Lawrence, David M.; Li, D.J.; Mahecha, M.; Niu, S.L.; Norby, Richard J.; Piao, S.L.; Qi, X.; Peylin, P.; Prentice, I.C.; Riley, William; Reichstein, M.; Schwalm, C.; Wang, Y.; Xia, J. Y.; Zaehle, S.; Zhou, X. H.

    2012-10-09

    Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models

  18. A framework for benchmarking land models

    SciTech Connect

    Luo, Yiqi; Randerson, James T.; Hoffman, Forrest; Norby, Richard J

    2012-01-01

    Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models

  19. An entropic framework for modeling economies

    NASA Astrophysics Data System (ADS)

    Caticha, Ariel; Golan, Amos

    2014-08-01

    We develop an information-theoretic framework for economic modeling. This framework is based on principles of entropic inference that are designed for reasoning on the basis of incomplete information. We take the point of view of an external observer who has access to limited information about broad macroscopic economic features. We view this framework as complementary to more traditional methods. The economy is modeled as a collection of agents about whom we make no assumptions of rationality (in the sense of maximizing utility or profit). States of statistical equilibrium are introduced as those macrostates that maximize entropy subject to the relevant information codified into constraints. The basic assumption is that this information refers to supply and demand and is expressed in the form of the expected values of certain quantities (such as inputs, resources, goods, production functions, utility functions and budgets). The notion of economic entropy is introduced. It provides a measure of the uniformity of the distribution of goods and resources. It captures both the welfare state of the economy as well as the characteristics of the market (say, monopolistic, concentrated or competitive). Prices, which turn out to be the Lagrange multipliers, are endogenously generated by the economy. Further studies include the equilibrium between two economies and the conditions for stability. As an example, the case of the nonlinear economy that arises from linear production and utility functions is treated in some detail.

  20. Architecting a Simulation Framework for Model Rehosting

    NASA Technical Reports Server (NTRS)

    Madden, Michael M.

    2004-01-01

    The utility of vehicle math models extends beyond human-in-the-loop simulation. It is desirable to deploy a given model across a multitude of applications that target design, analysis, and research. However, the vehicle model alone represents an incomplete simulation. One must also replicate the environment models (e.g., atmosphere, gravity, terrain) to achieve identical vehicle behavior across all applications. Environment models are increasing in complexity and represent a substantial investment to re-engineer for a new application. A software component that can be rehosted in each application is one solution to the deployment problem. The component must encapsulate both the vehicle and environment models. The component must have a well-defined interface that abstracts the bulk of the logic to operate the models. This paper examines the characteristics of a rehostable modeling component from the perspective of a human-in-the-loop simulation framework. The Langley Standard Real-Time Simulation in C++ (LaSRS++) is used as an example. LaSRS++ was recently redesigned to transform its modeling package into a rehostable component.

  1. A framework for multi-scale modelling

    PubMed Central

    Chopard, B.; Borgdorff, Joris; Hoekstra, A. G.

    2014-01-01

    We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology. PMID:24982249

  2. Translation from UML to Markov Model: A Performance Modeling Framework

    NASA Astrophysics Data System (ADS)

    Khan, Razib Hayat; Heegaard, Poul E.

    Performance engineering focuses on the quantitative investigation of the behavior of a system during the early phase of the system development life cycle. Bearing this on mind, we delineate a performance modeling framework of the application for communication system that proposes a translation process from high level UML notation to Continuous Time Markov Chain model (CTMC) and solves the model for relevant performance metrics. The framework utilizes UML collaborations, activity diagrams and deployment diagrams to be used for generating performance model for a communication system. The system dynamics will be captured by UML collaboration and activity diagram as reusable specification building blocks, while deployment diagram highlights the components of the system. The collaboration and activity show how reusable building blocks in the form of collaboration can compose together the service components through input and output pin by highlighting the behavior of the components and later a mapping between collaboration and system component identified by deployment diagram will be delineated. Moreover the UML models are annotated to associate performance related quality of service (QoS) information which is necessary for solving the performance model for relevant performance metrics through our proposed framework. The applicability of our proposed performance modeling framework in performance evaluation is delineated in the context of modeling a communication system.

  3. Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

    ERIC Educational Resources Information Center

    Berman, Jeanette; Smyth, Robyn

    2015-01-01

    This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…

  4. Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

    ERIC Educational Resources Information Center

    Berman, Jeanette; Smyth, Robyn

    2015-01-01

    This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…

  5. A Smallholder Socio-hydrological Modelling Framework

    NASA Astrophysics Data System (ADS)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  6. Comparison and Contrast of Two General Functional Regression Modeling Frameworks

    PubMed Central

    Morris, Jeffrey S.

    2017-01-01

    In this article, Greven and Scheipl describe an impressively general framework for performing functional regression that builds upon the generalized additive modeling framework. Over the past number of years, my collaborators and I have also been developing a general framework for functional regression, functional mixed models, which shares many similarities with this framework, but has many differences as well. In this discussion, I compare and contrast these two frameworks, to hopefully illuminate characteristics of each, highlighting their respecitve strengths and weaknesses, and providing recommendations regarding the settings in which each approach might be preferable. PMID:28736502

  7. The Aircraft Availability Model: Conceptual Framework and Mathematics

    DTIC Science & Technology

    1983-06-01

    THE AIRCRAFT AVAILABILITY MODEL: CONCEPTUAL FRAMEWORK AND MATHEMATICS June 1983 T. J. O’Malley Prepared pursuant to Department of Defense Contract No...OF REPORT & PERIOD COVERED The Aircraft Availability Model: Model Documentation Conceptual Framework and Mathematics 6. PERFORMING ORG. REPORT NUMBER

  8. Business model framework applications in health care: A systematic review.

    PubMed

    Fredriksson, Jens Jacob; Mazzocato, Pamela; Muhammed, Rafiq; Savage, Carl

    2017-01-01

    It has proven to be a challenge for health care organizations to achieve the Triple Aim. In the business literature, business model frameworks have been used to understand how organizations are aligned to achieve their goals. We conducted a systematic literature review with an explanatory synthesis approach to understand how business model frameworks have been applied in health care. We found a large increase in applications of business model frameworks during the last decade. E-health was the most common context of application. We identified six applications of business model frameworks: business model description, financial assessment, classification based on pre-defined typologies, business model analysis, development, and evaluation. Our synthesis suggests that the choice of business model framework and constituent elements should be informed by the intent and context of application. We see a need for harmonization in the choice of elements in order to increase generalizability, simplify application, and help organizations realize the Triple Aim.

  9. Improving the physics models in the Space Weather Modeling Framework

    NASA Astrophysics Data System (ADS)

    Toth, G.; Fang, F.; Frazin, R. A.; Gombosi, T. I.; Ilie, R.; Liemohn, M. W.; Manchester, W. B.; Meng, X.; Pawlowski, D. J.; Ridley, A. J.; Sokolov, I.; van der Holst, B.; Vichare, G.; Yigit, E.; Yu, Y.; Buzulukova, N.; Fok, M. H.; Glocer, A.; Jordanova, V. K.; Welling, D. T.; Zaharia, S. G.

    2010-12-01

    The success of physics based space weather forecasting depends on several factors: we need sufficient amount and quality of timely observational data, we have to understand the physics of the Sun-Earth system well enough, we need sophisticated computational models, and the models have to run faster than real time on the available computational resources. This presentation will focus on a single ingredient, the recent improvements of the mathematical and numerical models in the Space Weather Modeling Framework. We have developed a new physics based CME initiation code using flux emergence from the convection zone solving the equations of radiative magnetohydrodynamics (MHD). Our new lower corona and solar corona models use electron heat conduction, Alfven wave heating, and boundary conditions based on solar tomography. We can obtain a physically consistent solar wind model from the surface of the Sun all the way to the L1 point without artificially changing the polytropic index. The global magnetosphere model can now solve the multi-ion MHD equations and take into account the oxygen outflow from the polar wind model. We have also added the options of solving for Hall MHD and anisotropic pressure. Several new inner magnetosphere models have been added to the framework: CRCM, HEIDI and RAM-SCB. These new models resolve the pitch angle distribution of the trapped particles. The upper atmosphere model GITM has been improved by including a self-consistent equatorial electrodynamics and the effects of solar flares. This presentation will very briefly describe the developments and highlight some results obtained with the improved and new models.

  10. Towards a hierarchical optimization modeling framework for ...

    EPA Pesticide Factsheets

    Background:Bilevel optimization has been recognized as a 2-player Stackelberg game where players are represented as leaders and followers and each pursue their own set of objectives. Hierarchical optimization problems, which are a generalization of bilevel, are especially difficult because the optimization is nested, meaning that the objectives of one level depend on solutions to the other levels. We introduce a hierarchical optimization framework for spatially targeting multiobjective green infrastructure (GI) incentive policies under uncertainties related to policy budget, compliance, and GI effectiveness. We demonstrate the utility of the framework using a hypothetical urban watershed, where the levels are characterized by multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities), and objectives include minimization of policy cost, implementation cost, and risk; reduction of combined sewer overflow (CSO) events; and improvement in environmental benefits such as reduced nutrient run-off and water availability. Conclusions: While computationally expensive, this hierarchical optimization framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urba

  11. Critical Thinking: Frameworks and Models for Teaching

    ERIC Educational Resources Information Center

    Fahim, Mansoor; Eslamdoost, Samaneh

    2014-01-01

    Developing critical thinking since the educational revolution gave rise to flourishing movements toward embedding critical thinking (CT henceforth) stimulating classroom activities in educational settings. Nevertheless the process faced with complications such as teachability potentiality, lack of practical frameworks concerning actualization of…

  12. A Simulation and Modeling Framework for Space Situational Awareness

    SciTech Connect

    Olivier, S S

    2008-09-15

    This paper describes the development and initial demonstration of a new, integrated modeling and simulation framework, encompassing the space situational awareness enterprise, for quantitatively assessing the benefit of specific sensor systems, technologies and data analysis techniques. The framework is based on a flexible, scalable architecture to enable efficient, physics-based simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel computer systems available, for example, at Lawrence Livermore National Laboratory. The details of the modeling and simulation framework are described, including hydrodynamic models of satellite intercept and debris generation, orbital propagation algorithms, radar cross section calculations, optical brightness calculations, generic radar system models, generic optical system models, specific Space Surveillance Network models, object detection algorithms, orbit determination algorithms, and visualization tools. The use of this integrated simulation and modeling framework on a specific scenario involving space debris is demonstrated.

  13. A framework for modeling uncertainty in regional climate change

    EPA Science Inventory

    In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework ...

  14. A framework for modeling uncertainty in regional climate change

    EPA Science Inventory

    In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework ...

  15. Mid-Career Counseling--A Model Framework.

    ERIC Educational Resources Information Center

    College Placement Council, Bethlehem, PA.

    This model framework consists of client-centered strategies that can help the mid-career changer explore options. The framework presented in this document integrates theoretical and practical applications and can be adapted for use by a variety of campuses to meet the needs of the campus' adult population through individual or group counseling.…

  16. A Framework for Dimensionality Assessment for Multidimensional Item Response Models

    ERIC Educational Resources Information Center

    Svetina, Dubravka; Levy, Roy

    2014-01-01

    A framework is introduced for considering dimensionality assessment procedures for multidimensional item response models. The framework characterizes procedures in terms of their confirmatory or exploratory approach, parametric or nonparametric assumptions, and applicability to dichotomous, polytomous, and missing data. Popular and emerging…

  17. A Framework for Dimensionality Assessment for Multidimensional Item Response Models

    ERIC Educational Resources Information Center

    Svetina, Dubravka; Levy, Roy

    2014-01-01

    A framework is introduced for considering dimensionality assessment procedures for multidimensional item response models. The framework characterizes procedures in terms of their confirmatory or exploratory approach, parametric or nonparametric assumptions, and applicability to dichotomous, polytomous, and missing data. Popular and emerging…

  18. Coastal Ecosystem Integrated Compartment Model (ICM): Modeling Framework

    NASA Astrophysics Data System (ADS)

    Meselhe, E. A.; White, E. D.; Reed, D.

    2015-12-01

    The Integrated Compartment Model (ICM) was developed as part of the 2017 Coastal Master Plan modeling effort. It is a comprehensive and numerical hydrodynamic model coupled to various geophysical process models. Simplifying assumptions related to some of the flow dynamics are applied to increase the computational efficiency of the model. The model can be used to provide insights about coastal ecosystems and evaluate restoration strategies. It builds on existing tools where possible and incorporates newly developed tools where necessary. It can perform decadal simulations (~ 50 years) across the entire Louisiana coast. It includes several improvements over the approach used to support the 2012 Master Plan, such as: additional processes in the hydrology, vegetation, wetland and barrier island morphology subroutines, increased spatial resolution, and integration of previously disparate models into a single modeling framework. The ICM includes habitat suitability indices (HSIs) to predict broad spatial patterns of habitat change, and it provides an additional integration to a dynamic fish and shellfish community model which quantitatively predicts potential changes in important fishery resources. It can be used to estimate the individual and cumulative effects of restoration and protection projects on the landscape, including a general estimate of water levels associated with flooding. The ICM is also used to examine possible impacts of climate change and future environmental scenarios (e.g. precipitation, Eustatic sea level rise, subsidence, tropical storms, etc.) on the landscape and on the effectiveness of restoration projects. The ICM code is publically accessible, and coastal restoration and protection groups interested in planning-level modeling are encouraged to explore its utility as a computationally efficient tool to examine ecosystem response to future physical or ecological changes, including the implementation of restoration and protection strategies.

  19. Modeling QCD for Hadron Physics

    SciTech Connect

    Tandy, P. C.

    2011-10-24

    We review the approach to modeling soft hadron physics observables based on the Dyson-Schwinger equations of QCD. The focus is on light quark mesons and in particular the pseudoscalar and vector ground states, their decays and electromagnetic couplings. We detail the wide variety of observables that can be correlated by a ladder-rainbow kernel with one infrared parameter fixed to the chiral quark condensate. A recently proposed novel perspective in which the quark condensate is contained within hadrons and not the vacuum is mentioned. The valence quark parton distributions, in the pion and kaon, as measured in the Drell Yan process, are investigated with the same ladder-rainbow truncation of the Dyson-Schwinger and Bethe-Salpeter equations.

  20. Applying a causal framework to system modeling.

    PubMed

    Lieu, C A; Elliston, K O

    2007-01-01

    The emerging field of systems biology represents a revolution in our ability to understand biology. Perhaps for the first time in history we have the capacity to pursue biological understanding using a computer-aided integrative approach in conjunction with classical reductionist approaches. Technology has given us not only the ability to identify and measure the individual molecules of life and the way they change, but also the power to study these molecules and their changes in the context of a big picture. It is through the creation of a computer-aided framework for human understanding that we can begin to comprehend how these collections of molecules act as integrated biological systems, and to utilize this knowledge to rationally engineer the future of science and medicine.

  1. A clothing modeling framework for uniform and armor system design

    NASA Astrophysics Data System (ADS)

    Man, Xiaolin; Swan, Colby C.; Rahmatalla, Salam

    2006-05-01

    In the analysis and design of military uniforms and body armor systems it is helpful to quantify the effects of the clothing/armor system on a wearer's physical performance capabilities. Toward this end, a clothing modeling framework for quantifying the mechanical interactions between a given uniform or body armor system design and a specific wearer performing defined physical tasks is proposed. The modeling framework consists of three interacting modules: (1) a macroscale fabric mechanics/dynamics model; (2) a collision detection and contact correction module; and (3) a human motion module. In the proposed framework, the macroscopic fabric model is based on a rigorous large deformation continuum-degenerated shell theory representation. The collision and contact module enforces non-penetration constraints between the fabric and human body and computes the associated contact forces between the two. The human body is represented in the current framework, as an assemblage of overlapping ellipsoids that undergo rigid body motions consistent with human motions while performing actions such as walking, running, or jumping. The transient rigid body motions of each ellipsoidal body segment in time are determined using motion capture technology. The integrated modeling framework is then exercised to quantify the resistance that the clothing exerts on the wearer during the specific activities under consideration. Current results from the framework are presented and its intended applications are discussed along with some of the key challenges remaining in clothing system modeling.

  2. Making sense of implementation theories, models and frameworks.

    PubMed

    Nilsen, Per

    2015-04-21

    Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers. Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited "how-to" support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.

  3. Landscape development modeling based on statistical framework

    NASA Astrophysics Data System (ADS)

    Pohjola, Jari; Turunen, Jari; Lipping, Tarmo; Ikonen, Ari T. K.

    2014-01-01

    Future biosphere modeling has an essential role in assessing the safety of a proposed nuclear fuel repository. In Finland the basic inputs needed for future biosphere modeling are the digital elevation model and the land uplift model because the surface of the ground is still rising due to the download stress caused by the last ice age. The future site-scale land uplift is extrapolated by fitting mathematical expressions to known data from past shoreline positions. In this paper, the parameters of this fitting have been refined based on information about lake and mire basin isolation and archaeological findings. Also, an alternative eustatic model is used in parameter refinement. Both datasets involve uncertainties so Monte Carlo simulation is used to acquire several realizations of the model parameters. The two statistical models, the digital elevation model and the refined land uplift model, were used as inputs to a GIS-based toolbox where the characteristics of lake projections for the future Olkiluoto nuclear fuel repository site were estimated. The focus of the study was on surface water bodies since they are the major transport channels for radionuclides in containment failure scenarios. The results of the study show that the different land uplift modeling schemes relying on alternative eustatic models, Moho map versions and function fitting techniques yield largely similar landscape development tracks. However, the results also point out some more improbable realizations, which deviate significantly from the main development tracks.

  4. An Ising model for metal-organic frameworks

    NASA Astrophysics Data System (ADS)

    Höft, Nicolas; Horbach, Jürgen; Martín-Mayor, Victor; Seoane, Beatriz

    2017-08-01

    We present a three-dimensional Ising model where lines of equal spins are frozen such that they form an ordered framework structure. The frame spins impose an external field on the rest of the spins (active spins). We demonstrate that this "porous Ising model" can be seen as a minimal model for condensation transitions of gas molecules in metal-organic frameworks. Using Monte Carlo simulation techniques, we compare the phase behavior of a porous Ising model with that of a particle-based model for the condensation of methane (CH4) in the isoreticular metal-organic framework IRMOF-16. For both models, we find a line of first-order phase transitions that end in a critical point. We show that the critical behavior in both cases belongs to the 3D Ising universality class, in contrast to other phase transitions in confinement such as capillary condensation.

  5. Mediation Analysis in a Latent Growth Curve Modeling Framework

    ERIC Educational Resources Information Center

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  6. Mediation Analysis in a Latent Growth Curve Modeling Framework

    ERIC Educational Resources Information Center

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  7. A Computational Framework for Realistic Retina Modeling.

    PubMed

    Martínez-Cañada, Pablo; Morillas, Christian; Pino, Begoña; Ros, Eduardo; Pelayo, Francisco

    2016-11-01

    Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

  8. GeoFramework: Coupling multiple models of mantle convection within a computational framework

    NASA Astrophysics Data System (ADS)

    Tan, E.; Choi, E.; Thoutireddy, P.; Gurnis, M.; Aivazis, M.

    2004-12-01

    Geological processes usually encompass a broad spectrum of length and time scales. Traditionally, a modeling code (solver) is developed for a problem of specific length and time scales, but the utility of the solver beyond the designated purpose is usually limited. As we have come to recognize that geological processes often result from the dynamic coupling of deformation across a wide range of time and spatial scales, more robust methods are needed. One means to address this need is through the integration of complementary modeling codes, while attempting to reuse existing software as much as possible. The GeoFramework project addresses this by developing a suite of reusable and combinable tools for the Earth science community. GeoFramework is based on and extends Pyre, a Python-based modeling framework, developed to link solid (Lagrangian) and fluid (Eulerian) solvers, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. Under the framework, a solver is aware of the presence of other solvers and can interact with each other via exchanging information across adjacent mesh boundary. We will show an example of linking two instances of the CitcomS finite element solver within GeoFramework. A high-resolution regional mantle convection model is linked with a global mantle convection model. The global solver has a resolution of ˜180 km horizontally and 35-100 km (with mesh refinement) vertically. The fine mesh has a resolution of ˜40 km horizontally and vertically. The fine mesh is center on the Hawaii hotspot. A vertical plume is used as an initial condition. Time-varying plate velocity models are imposed since 80 Ma and we have investigated how the plume conduit is deflected by the global circulation patterns as a function of mantle viscosity, plume flux, and plate motion.

  9. Aero-thermal modeling framework for TMT

    NASA Astrophysics Data System (ADS)

    Vogiatzis, Konstantinos

    2011-09-01

    The Performance Error Budget of the Thirty Meter Telescope (TMT) suggests that nearly one third of the total image degradation is due to aero-thermal disturbances (mirror and dome seeing, dynamic wind loading and thermal deformations of the optics, telescope structure and enclosure). An update of the current status of aero-thermal modeling and Computational Fluid-Solid Dynamics (CFSD) simulations for TMT is presented. A fast three-dimensional transient conduction-convection-radiation bulk-air-volume model has also been developed for the enclosure and selected telescope components in order to track the temperature variations of the surfaces, structure and interstitial air over a period of three years using measured environmental conditions. It is used for Observatory Heat Budget analysis and also provides estimates of thermal boundary conditions required by the CFD/FEA models and guidance to the design. Detailed transient CFSD conjugate heat transfer simulations of the mirror support assemblies determine the direction of heat flow from important heat sources and provide guidance to the design. Finally, improved CFD modeling is used to calculate wind forces and temperature fields. Wind loading simulations are demonstrated through TMT aperture deflector forcing. Temperature fields are transformed into refractive index ones and the resulting Optical Path Differences (OPDs) are fed into an updated thermal seeing model to estimate seeing performance metrics. Keck II simulations are the demonstrator for the latter type of modeling.

  10. Entity-Centric Abstraction and Modeling Framework for Transportation Architectures

    NASA Technical Reports Server (NTRS)

    Lewe, Jung-Ho; DeLaurentis, Daniel A.; Mavris, Dimitri N.; Schrage, Daniel P.

    2007-01-01

    A comprehensive framework for representing transpportation architectures is presented. After discussing a series of preceding perspectives and formulations, the intellectual underpinning of the novel framework using an entity-centric abstraction of transportation is described. The entities include endogenous and exogenous factors and functional expressions are offered that relate these and their evolution. The end result is a Transportation Architecture Field which permits analysis of future concepts under the holistic perspective. A simulation model which stems from the framework is presented and exercised producing results which quantify improvements in air transportation due to advanced aircraft technologies. Finally, a modeling hypothesis and its accompanying criteria are proposed to test further use of the framework for evaluating new transportation solutions.

  11. A Modeling Framework for Improved Agricultural Water Supply Forecasting

    NASA Astrophysics Data System (ADS)

    Leavesley, G. H.; David, O.; Garen, D. C.; Lea, J.; Marron, J. K.; Pagano, T. C.; Perkins, T. R.; Strobel, M. L.

    2008-12-01

    The National Water and Climate Center (NWCC) of the USDA Natural Resources Conservation Service is moving to augment seasonal, regression-equation based water supply forecasts with distributed-parameter, physical process models enabling daily, weekly, and seasonal forecasting using an Ensemble Streamflow Prediction (ESP) methodology. This effort involves the development and implementation of a modeling framework, and associated models and tools, to provide timely forecasts for use by the agricultural community in the western United States where snowmelt is a major source of water supply. The framework selected to support this integration is the USDA Object Modeling System (OMS). OMS is a Java-based modular modeling framework for model development, testing, and deployment. It consists of a library of stand-alone science, control, and database components (modules), and a means to assemble selected components into a modeling package that is customized to the problem, data constraints, and scale of application. The framework is supported by utility modules that provide a variety of data management, land unit delineation and parameterization, sensitivity analysis, calibration, statistical analysis, and visualization capabilities. OMS uses an open source software approach to enable all members of the scientific community to collaboratively work on addressing the many complex issues associated with the design, development, and application of distributed hydrological and environmental models. A long-term goal in the development of these water-supply forecasting capabilities is the implementation of an ensemble modeling approach. This would provide forecasts using the results of multiple hydrologic models run on each basin.

  12. Fisher information framework for time series modeling

    NASA Astrophysics Data System (ADS)

    Venkatesan, R. C.; Plastino, A.

    2017-08-01

    A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

  13. Multi-Fidelity Framework for Modeling Combustion Instability

    DTIC Science & Technology

    2016-07-27

    Therefore, to allow more flexibility and generality in the multi-fidelity framework, an alternative single -ROM approach based on utilizing the full...of periodic forcing on a reduced domain using Galerkin’s method to reduce the high-order PDEs to a lower-order ODE system via POD eigen- bases ...generated from the reduced-domain dataset. Evaluations of the framework are performed based on simplified test problems for a model rocket combustor showing

  14. Fire risk analysis: general conceptual framework for describing models.

    PubMed

    Hall, J R; Sekizawa, A

    1991-02-01

    A general conceptual framework has been developed as an aid to discussions of alternative approaches to fire risk analysis. The purpose is to show how each alternative seeks to address a few common concerns. Basic concepts and key elements--notably scenario structures, appropriate probability functions, and security and outcome measures--are defined and discussed, as are types of modeling approaches. A number of diverse examples are then presented using the framework to illustrate its value in making comparisons.

  15. Multicriteria framework for selecting a process modelling language

    NASA Astrophysics Data System (ADS)

    Scanavachi Moreira Campos, Ana Carolina; Teixeira de Almeida, Adiel

    2016-01-01

    The choice of process modelling language can affect business process management (BPM) since each modelling language shows different features of a given process and may limit the ways in which a process can be described and analysed. However, choosing the appropriate modelling language for process modelling has become a difficult task because of the availability of a large number modelling languages and also due to the lack of guidelines on evaluating, and comparing languages so as to assist in selecting the most appropriate one. This paper proposes a framework for selecting a modelling language in accordance with the purposes of modelling. This framework is based on the semiotic quality framework (SEQUAL) for evaluating process modelling languages and a multicriteria decision aid (MCDA) approach in order to select the most appropriate language for BPM. This study does not attempt to set out new forms of assessment and evaluation criteria, but does attempt to demonstrate how two existing approaches can be combined so as to solve the problem of selection of modelling language. The framework is described in this paper and then demonstrated by means of an example. Finally, the advantages and disadvantages of using SEQUAL and MCDA in an integrated manner are discussed.

  16. Evolutionary Framework for Lepidoptera Model Systems

    USDA-ARS?s Scientific Manuscript database

    Model systems” are specific organisms upon which detailed studies have been conducted examining a fundamental biological question. If the studies are robust, their results can be extrapolated among an array of organisms that possess features in common with the subject organism. The true power of...

  17. First-Order Frameworks for Managing Models in Engineering Optimization

    NASA Technical Reports Server (NTRS)

    Alexandrov, Natlia M.; Lewis, Robert Michael

    2000-01-01

    Approximation/model management optimization (AMMO) is a rigorous methodology for attaining solutions of high-fidelity optimization problems with minimal expense in high- fidelity function and derivative evaluation. First-order AMMO frameworks allow for a wide variety of models and underlying optimization algorithms. Recent demonstrations with aerodynamic optimization achieved three-fold savings in terms of high- fidelity function and derivative evaluation in the case of variable-resolution models and five-fold savings in the case of variable-fidelity physics models. The savings are problem dependent but certain trends are beginning to emerge. We give an overview of the first-order frameworks, current computational results, and an idea of the scope of the first-order framework applicability.

  18. Theoretical Tinnitus Framework: A Neurofunctional Model

    PubMed Central

    Ghodratitoostani, Iman; Zana, Yossi; Delbem, Alexandre C. B.; Sani, Siamak S.; Ekhtiari, Hamed; Sanchez, Tanit G.

    2016-01-01

    Subjective tinnitus is the conscious (attended) awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. Earlier literature establishes three distinct states of conscious perception as unattended, attended, and attended awareness conscious perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional Tinnitus Model to indicate that the conscious (attended) awareness perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional Tinnitus Model includes the peripheral auditory system, the thalamus, the limbic system, brainstem, basal ganglia, striatum, and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the “sourceless” sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be

  19. Theoretical Tinnitus Framework: A Neurofunctional Model.

    PubMed

    Ghodratitoostani, Iman; Zana, Yossi; Delbem, Alexandre C B; Sani, Siamak S; Ekhtiari, Hamed; Sanchez, Tanit G

    2016-01-01

    Subjective tinnitus is the conscious (attended) awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. Earlier literature establishes three distinct states of conscious perception as unattended, attended, and attended awareness conscious perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional Tinnitus Model to indicate that the conscious (attended) awareness perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional Tinnitus Model includes the peripheral auditory system, the thalamus, the limbic system, brainstem, basal ganglia, striatum, and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the "sourceless" sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be

  20. Frameworks for Assessing the Quality of Modeling and Simulation Capabilities

    NASA Astrophysics Data System (ADS)

    Rider, W. J.

    2012-12-01

    The importance of assuring quality in modeling and simulation has spawned several frameworks for structuring the examination of quality. The format and content of these frameworks provides an emphasis, completeness and flow to assessment activities. I will examine four frameworks that have been developed and describe how they can be improved and applied to a broader set of high consequence applications. Perhaps the first of these frameworks was known as CSAU [Boyack] (code scaling, applicability and uncertainty) used for nuclear reactor safety and endorsed the United States' Nuclear Regulatory Commission (USNRC). This framework was shaped by nuclear safety practice, and the practical structure needed after the Three Mile Island accident. It incorporated the dominant experimental program, the dominant analysis approach, and concerns about the quality of modeling. The USNRC gave it the force of law that made the nuclear industry take it seriously. After the cessation of nuclear weapons' testing the United States began a program of examining the reliability of these weapons without testing. This program utilizes science including theory, modeling, simulation and experimentation to replace the underground testing. The emphasis on modeling and simulation necessitated attention on the quality of these simulations. Sandia developed the PCMM (predictive capability maturity model) to structure this attention [Oberkampf]. PCMM divides simulation into six core activities to be examined and graded relative to the needs of the modeling activity. NASA [NASA] has built yet another framework in response to the tragedy of the space shuttle accidents. Finally, Ben-Haim and Hemez focus upon modeling robustness and predictive fidelity in another approach. These frameworks are similar, and applied in a similar fashion. The adoption of these frameworks at Sandia and NASA has been slow and arduous because the force of law has not assisted acceptance. All existing frameworks are

  1. A Model Framework for Course Materials Construction. Third Edition.

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    A model framework for course materials construction is presented as an aid to Coast Guard course writers and coordinators, curriculum developers, and instructors who must modify a course or draft a new one. The model assumes that the instructor or other designated person has: (1) completed a task analysis which identifies the competencies, skills…

  2. Characteristics and Conceptual Framework of the Easy-Play Model

    ERIC Educational Resources Information Center

    Lu, Chunlei; Steele, Kyle

    2014-01-01

    The Easy-Play Model offers a defined framework to organize games that promote an inclusive and enjoyable sport experience. The model can be implemented by participants playing sports in educational, recreational or social contexts with the goal of achieving an active lifestyle in an inclusive, cooperative and enjoyable environment. The Easy-Play…

  3. Industrial Sector Energy Efficiency Modeling (ISEEM) Framework Documentation

    SciTech Connect

    Karali, Nihan; Xu, Tengfang; Sathaye, Jayant

    2012-12-12

    The goal of this study is to develop a new bottom-up industry sector energy-modeling framework with an agenda of addressing least cost regional and global carbon reduction strategies, improving the capabilities and limitations of the existing models that allows trading across regions and countries as an alternative.

  4. A Model Framework for Course Materials Construction. Third Edition.

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    A model framework for course materials construction is presented as an aid to Coast Guard course writers and coordinators, curriculum developers, and instructors who must modify a course or draft a new one. The model assumes that the instructor or other designated person has: (1) completed a task analysis which identifies the competencies, skills…

  5. Characteristics and Conceptual Framework of the Easy-Play Model

    ERIC Educational Resources Information Center

    Lu, Chunlei; Steele, Kyle

    2014-01-01

    The Easy-Play Model offers a defined framework to organize games that promote an inclusive and enjoyable sport experience. The model can be implemented by participants playing sports in educational, recreational or social contexts with the goal of achieving an active lifestyle in an inclusive, cooperative and enjoyable environment. The Easy-Play…

  6. Argumentation in Science Education: A Model-Based Framework

    ERIC Educational Resources Information Center

    Bottcher, Florian; Meisert, Anke

    2011-01-01

    The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons…

  7. A Philosophical Framework for Integrating Systems Pharmacology Models Into Pharmacometrics

    PubMed Central

    2016-01-01

    The framework for systems pharmacology style models does not naturally sit with the usual scientific dogma of parsimony and falsifiability based on deductive reasoning. This does not invalidate the importance or need for overarching models based on pharmacology to describe and understand complicated biological systems. However, it does require some consideration on how systems pharmacology fits into the overall scientific approach. PMID:27863137

  8. A National Modeling Framework for Water Management Decisions

    NASA Astrophysics Data System (ADS)

    Bales, J. D.; Cline, D. W.; Pietrowsky, R.

    2013-12-01

    The National Weather Service (NWS), the U.S. Army Corps of Engineers (USACE), and the U.S. Geological Survey (USGS), all Federal agencies with complementary water-resources activities, entered into an Interagency Memorandum of Understanding (MOU) "Collaborative Science Services and Tools to Support Integrated and Adaptive Water Resources Management" to collaborate in activities that are supportive to their respective missions. One of the interagency activities is the development of a highly integrated national water modeling framework and information services framework. Together these frameworks establish a common operating picture, improve modeling and synthesis, support the sharing of data and products among agencies, and provide a platform for incorporation of new scientific understanding. Each of the agencies has existing operational systems to assist in carrying out their respective missions. The systems generally are designed, developed, tested, fielded, and supported by specialized teams. A broader, shared approach is envisioned and would include community modeling, wherein multiple independent investigators or teams develop and contribute new modeling capabilities based on science advances; modern technology in coupling model components and visualizing results; and a coupled atmospheric - hydrologic model construct such that the framework could be used in real-time water-resources decision making or for long-term management decisions. The framework also is being developed to account for organizational structures of the three partners such that, for example, national data sets can move down to the regional scale, and vice versa. We envision the national water modeling framework to be an important element of North American Water Program, to contribute to goals of the Program, and to be informed by the science and approaches developed as a part of the Program.

  9. A software engineering perspective on environmental modeling framework design: The object modeling system

    USDA-ARS?s Scientific Manuscript database

    The environmental modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data provisioning and transformation, etc.). Environmental modeling frameworks (EMFs) have been developed to...

  10. 3-D HYDRODYNAMIC MODELING IN A GEOSPATIAL FRAMEWORK

    SciTech Connect

    Bollinger, J; Alfred Garrett, A; Larry Koffman, L; David Hayes, D

    2006-08-24

    3-D hydrodynamic models are used by the Savannah River National Laboratory (SRNL) to simulate the transport of thermal and radionuclide discharges in coastal estuary systems. Development of such models requires accurate bathymetry, coastline, and boundary condition data in conjunction with the ability to rapidly discretize model domains and interpolate the required geospatial data onto the domain. To facilitate rapid and accurate hydrodynamic model development, SRNL has developed a pre- and post-processor application in a geospatial framework to automate the creation of models using existing data. This automated capability allows development of very detailed models to maximize exploitation of available surface water radionuclide sample data and thermal imagery.

  11. A unified framework for Schelling's model of segregation

    NASA Astrophysics Data System (ADS)

    Rogers, Tim; McKane, Alan J.

    2011-07-01

    Schelling's model of segregation is one of the first and most influential models in the field of social simulation. There are many variations of the model which have been proposed and simulated over the last forty years, though the present state of the literature on the subject is somewhat fragmented and lacking comprehensive analytical treatments. In this paper a unified mathematical framework for Schelling's model and its many variants is developed. This methodology is useful in two regards: firstly, it provides a tool with which to understand the differences observed between models; secondly, phenomena which appear in several model variations may be understood in more depth through analytic studies of simpler versions.

  12. Argumentation in Science Education: A Model-based Framework

    NASA Astrophysics Data System (ADS)

    Böttcher, Florian; Meisert, Anke

    2011-02-01

    The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.

  13. Modeling of ultrasonic processes utilizing a generic software framework

    NASA Astrophysics Data System (ADS)

    Bruns, P.; Twiefel, J.; Wallaschek, J.

    2017-06-01

    Modeling of ultrasonic processes is typically characterized by a high degree of complexity. Different domains and size scales must be regarded, so that it is rather difficult to build up a single detailed overall model. Developing partial models is a common approach to overcome this difficulty. In this paper a generic but simple software framework is presented which allows to coupe arbitrary partial models by slave modules with well-defined interfaces and a master module for coordination. Two examples are given to present the developed framework. The first one is the parameterization of a load model for ultrasonically-induced cavitation. The piezoelectric oscillator, its mounting, and the process load are described individually by partial models. These partial models then are coupled using the framework. The load model is composed of spring-damper-elements which are parameterized by experimental results. In the second example, the ideal mounting position for an oscillator utilized in ultrasonic assisted machining of stone is determined. Partial models for the ultrasonic oscillator, its mounting, the simplified contact process, and the workpiece’s material characteristics are presented. For both applications input and output variables are defined to meet the requirements of the framework’s interface.

  14. Framework for scalable adsorbate–adsorbate interaction models

    DOE PAGES

    Hoffmann, Max J.; Medford, Andrew J.; Bligaard, Thomas

    2016-06-02

    Here, we present a framework for physically motivated models of adsorbate–adsorbate interaction between small molecules on transition and coinage metals based on modifications to the substrate electronic structure due to adsorption. We use this framework to develop one model for transition and one for coinage metal surfaces. The models for transition metals are based on the d-band center position, and the models for coinage metals are based on partial charges. The models require no empirical parameters, only two first-principles calculations per adsorbate as input, and therefore scale linearly with the number of reaction intermediates. By theory to theory comparison withmore » explicit density functional theory calculations over a wide range of adsorbates and surfaces, we show that the root-mean-squared error for differential adsorption energies is less than 0.2 eV for up to 1 ML coverage.« less

  15. Framework for scalable adsorbate–adsorbate interaction models

    SciTech Connect

    Hoffmann, Max J.; Medford, Andrew J.; Bligaard, Thomas

    2016-06-02

    Here, we present a framework for physically motivated models of adsorbate–adsorbate interaction between small molecules on transition and coinage metals based on modifications to the substrate electronic structure due to adsorption. We use this framework to develop one model for transition and one for coinage metal surfaces. The models for transition metals are based on the d-band center position, and the models for coinage metals are based on partial charges. The models require no empirical parameters, only two first-principles calculations per adsorbate as input, and therefore scale linearly with the number of reaction intermediates. By theory to theory comparison with explicit density functional theory calculations over a wide range of adsorbates and surfaces, we show that the root-mean-squared error for differential adsorption energies is less than 0.2 eV for up to 1 ML coverage.

  16. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    PubMed

    Sluka, James P; Fu, Xiao; Swat, Maciej; Belmonte, Julio M; Cosmanescu, Alin; Clendenon, Sherry G; Wambaugh, John F; Glazier, James A

    2016-01-01

    We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

  17. A Liver-Centric Multiscale Modeling Framework for Xenobiotics

    PubMed Central

    Swat, Maciej; Cosmanescu, Alin; Clendenon, Sherry G.; Wambaugh, John F.; Glazier, James A.

    2016-01-01

    We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. PMID:27636091

  18. New framework for standardized notation in wastewater treatment modelling.

    PubMed

    Corominas, L L; Rieger, L; Takács, I; Ekama, G; Hauduc, H; Vanrolleghem, P A; Oehmen, A; Gernaey, K V; van Loosdrecht, M C M; Comeau, Y

    2010-01-01

    Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new notational framework which allows unique and systematic naming of state variables and parameters of biokinetic models in the wastewater treatment field. The symbols are based on one main letter that gives a general description of the state variable or parameter and several subscript levels that provide greater specification. Only those levels that make the name unique within the model context are needed in creating the symbol. The paper describes specific problems encountered with the currently used notation, presents the proposed framework and provides additional practical examples. The overall result is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper is to establish a consistent set of rules that can be applied to existing and most importantly, future models. Applying the proposed notation should make it easier for everyone active in the wastewater treatment field to read, write and review documents describing modelling projects.

  19. A computational framework for a database of terrestrial biosphere models

    NASA Astrophysics Data System (ADS)

    Metzler, Holger; Müller, Markus; Ceballos-Núñez, Verónika; Sierra, Carlos A.

    2016-04-01

    Most terrestrial biosphere models consist of a set of coupled ordinary first order differential equations. Each equation represents a pool containing carbon with a certain turnover rate. Although such models share some basic mathematical structures, they can have very different properties such as number of pools, cycling rates, and internal fluxes. We present a computational framework that helps analyze the structure and behavior of terrestrial biosphere models using as an example the process of soil organic matter decomposition. The same framework can also be used for other sub-processes such as carbon fixation or allocation. First, the models have to be fed into a database consisting of simple text files with a common structure. Then they are read in using Python and transformed into an internal 'Model Class' that can be used to automatically create an overview stating the model's structure, state variables, internal and external fluxes. SymPy, a Python library for symbolic mathematics, helps to also calculate the Jacobian matrix at possibly given steady states and the eigenvalues of this matrix. If complete parameter sets are available, the model can also be run using R to simulate its behavior under certain conditions and to support a deeper stability analysis. In this case, the framework is also able to provide phase-plane plots if appropriate. Furthermore, an overview of all the models in the database can be given to help identify their similarities and differences.

  20. The BMW Model: A New Framework for Teaching Monetary Economics

    ERIC Educational Resources Information Center

    Bofinger, Peter; Mayer, Eric; Wollmershauser, Timo

    2006-01-01

    Although the IS/LM-AS/AD model is still the central tool of macroeconomic teaching in most macroeconomic textbooks, it has been criticized by several economists. Colander (1995) demonstrated that the framework is logically inconsistent, Romer (2000) showed that it is unable to deal with a monetary policy that uses the interest rate as its…

  1. The BMW Model: A New Framework for Teaching Monetary Economics

    ERIC Educational Resources Information Center

    Bofinger, Peter; Mayer, Eric; Wollmershauser, Timo

    2006-01-01

    Although the IS/LM-AS/AD model is still the central tool of macroeconomic teaching in most macroeconomic textbooks, it has been criticized by several economists. Colander (1995) demonstrated that the framework is logically inconsistent, Romer (2000) showed that it is unable to deal with a monetary policy that uses the interest rate as its…

  2. A Liver-centric Multiscale Modeling Framework for Xenobiotics

    EPA Science Inventory

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

  3. A Liver-centric Multiscale Modeling Framework for Xenobiotics

    EPA Science Inventory

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

  4. A Theoretical Framework for Physics Education Research: Modeling Student Thinking

    ERIC Educational Resources Information Center

    Redish, Edward F.

    2004-01-01

    Education is a goal-oriented field. But if we want to treat education scientifically so we can accumulate, evaluate, and refine what we learn, then we must develop a theoretical framework that is strongly rooted in objective observations and through which different theoretical models of student thinking can be compared. Much that is known in the…

  5. Language Arts Curriculum Framework: Sample Curriculum Model, Grade 8.

    ERIC Educational Resources Information Center

    Arkansas State Dept. of Education, Little Rock.

    Based on the 1998 Arkansas English Language Arts Curriculum Frameworks, this sample curriculum model for grade eight language arts is divided into sections focusing on writing; reading; and listening, speaking, and viewing. The writing section's stated goals are to help students employ a wide range of strategies as they write; use different…

  6. Language Arts Curriculum Framework: Sample Curriculum Model, Grade 5.

    ERIC Educational Resources Information Center

    Arkansas State Dept. of Education, Little Rock.

    Based on the 1998 Arkansas English Language Arts Curriculum Frameworks, this sample curriculum model for grade five language arts is divided into sections focusing on writing; reading; and listening, speaking, and viewing. The writing section's stated goals are to help students employ a wide range of strategies as they write; use different writing…

  7. Language Arts Curriculum Framework: Sample Curriculum Model, Grade 7.

    ERIC Educational Resources Information Center

    Arkansas State Dept. of Education, Little Rock.

    Based on the 1998 Arkansas English Language Arts Curriculum Frameworks, this sample curriculum model for grade seven language arts is divided into sections focusing on writing; reading; and listening, speaking, and viewing. The writing section's stated goals are to help students employ a wide range of strategies as they write; use different…

  8. Language Arts Curriculum Framework: Sample Curriculum Model, Grade 6.

    ERIC Educational Resources Information Center

    Arkansas State Dept. of Education, Little Rock.

    Based on the 1998 Arkansas English Language Arts Curriculum Frameworks, this sample curriculum model for grade six language arts is divided into sections focusing on writing; reading; and listening, speaking, and viewing. The writing section's stated goals are to help students employ a wide range of strategies as they write; use different writing…

  9. Framework for Understanding Structural Errors (FUSE): a modular framework to diagnose differences between hydrological models

    USGS Publications Warehouse

    Clark, Martyn P.; Slater, Andrew G.; Rupp, David E.; Woods, Ross A.; Vrugt, Jasper A.; Gupta, Hoshin V.; Wagener, Thorsten; Hay, Lauren E.

    2008-01-01

    The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding research challenges for the discipline of hydrology. Progress on these problems requires understanding of the nature of differences between models. This paper presents a methodology to diagnose differences in hydrological model structures: the Framework for Understanding Structural Errors (FUSE). FUSE was used to construct 79 unique model structures by combining components of 4 existing hydrological models. These new models were used to simulate streamflow in two of the basins used in the Model Parameter Estimation Experiment (MOPEX): the Guadalupe River (Texas) and the French Broad River (North Carolina). Results show that the new models produced simulations of streamflow that were at least as good as the simulations produced by the models that participated in the MOPEX experiment. Our initial application of the FUSE method for the Guadalupe River exposed relationships between model structure and model performance, suggesting that the choice of model structure is just as important as the choice of model parameters. However, further work is needed to evaluate model simulations using multiple criteria to diagnose the relative importance of model structural differences in various climate regimes and to assess the amount of independent information in each of the models. This work will be crucial to both identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure. To facilitate research on these problems, the FORTRAN-90 source code for FUSE is available upon request from the lead author.

  10. Composable Framework Support for Software-FMEA Through Model Execution

    NASA Astrophysics Data System (ADS)

    Kocsis, Imre; Patricia, Andras; Brancati, Francesco; Rossi, Francesco

    2016-08-01

    Performing Failure Modes and Effect Analysis (FMEA) during software architecture design is becoming a basic requirement in an increasing number of domains; however, due to the lack of standardized early design phase model execution, classic SW-FMEA approaches carry significant risks and are human effort-intensive even in processes that use Model-Driven Engineering.Recently, modelling languages with standardized executable semantics have emerged. Building on earlier results, this paper describes framework support for generating executable error propagation models from such models during software architecture design. The approach carries the promise of increased precision, decreased risk and more automated execution for SW-FMEA during dependability- critical system development.

  11. A Framework for Understanding Physics Students' Computational Modeling Practices

    NASA Astrophysics Data System (ADS)

    Lunk, Brandon Robert

    With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by

  12. A numerical framework for modelling floating wind turbines

    NASA Astrophysics Data System (ADS)

    Vire, Axelle; Xiang, Jiansheng; Piggott, Matthew; Latham, John-Paul; Pain, Christopher

    2012-11-01

    This work couples a fluid/ocean- and a solid- dynamics model in order to numerically study fluid-structure interactions. The fully non-linear Navier-Stokes and solid-dynamics equations are solved on two distinct finite-element and unstructured grids. The interplay between fluid and solid is represented through a penalty force in the momentum balances of each material. The present algorithm is novel in that it spatially conserves the discrete penalty force, when exchanging it between both models, independently of the mesh resolution and of the shape-function orders in each model. This numerical framework targets the modelling of offshore floating wind turbines. Results will be shown for the flow past a moving pile and an actuator-disk representation of a turbine. This research is supported by the European Union Seventh Framework Programme (grant agreement PIEF-GA-2010-272437).

  13. Stoichiometric modeling of carbon diagenesis within a coral reef framework

    NASA Astrophysics Data System (ADS)

    Tribble, Gordon W.; Sansone, Francis J.; Smith, Stephen V.

    1990-09-01

    Water sampled from the interior framework of Checker Reef, Oahu, Hawaii, indicates that the aerobic and anaerobic oxidation of organic matter dominates diagenesis within the reef framework. Reef interstitial water chemistry shows clear deviations from surface seawater: oxygen is depleted while dissolved inorganic carbon, H +, inorganic nutrients, sulfide and methane concentrations are elevated. Dissolved calcium is also elevated in most interstitial waters, indicating net dissolution of calcium carbonates. A mass-balance model used to determine the extent to which major biogeochemical reactions occur reveals that sulfate reduction is the predominant anaerobic process.

  14. Theoretical models and operational frameworks in public health ethics.

    PubMed

    Petrini, Carlo

    2010-01-01

    The article is divided into three sections: (i) an overview of the main ethical models in public health (theoretical foundations); (ii) a summary of several published frameworks for public health ethics (practical frameworks); and (iii) a few general remarks. Rather than maintaining the superiority of one position over the others, the main aim of the article is to summarize the basic approaches proposed thus far concerning the development of public health ethics by describing and comparing the various ideas in the literature. With this in mind, an extensive list of references is provided.

  15. Theoretical Models and Operational Frameworks in Public Health Ethics

    PubMed Central

    Petrini, Carlo

    2010-01-01

    The article is divided into three sections: (i) an overview of the main ethical models in public health (theoretical foundations); (ii) a summary of several published frameworks for public health ethics (practical frameworks); and (iii) a few general remarks. Rather than maintaining the superiority of one position over the others, the main aim of the article is to summarize the basic approaches proposed thus far concerning the development of public health ethics by describing and comparing the various ideas in the literature. With this in mind, an extensive list of references is provided. PMID:20195441

  16. A High Performance Bayesian Computing Framework for Spatiotemporal Uncertainty Modeling

    NASA Astrophysics Data System (ADS)

    Cao, G.

    2015-12-01

    All types of spatiotemporal measurements are subject to uncertainty. With spatiotemporal data becomes increasingly involved in scientific research and decision making, it is important to appropriately model the impact of uncertainty. Quantitatively modeling spatiotemporal uncertainty, however, is a challenging problem considering the complex dependence and dataheterogeneities.State-space models provide a unifying and intuitive framework for dynamic systems modeling. In this paper, we aim to extend the conventional state-space models for uncertainty modeling in space-time contexts while accounting for spatiotemporal effects and data heterogeneities. Gaussian Markov Random Field (GMRF) models, also known as conditional autoregressive models, are arguably the most commonly used methods for modeling of spatially dependent data. GMRF models basically assume that a geo-referenced variable primarily depends on its neighborhood (Markov property), and the spatial dependence structure is described via a precision matrix. Recent study has shown that GMRFs are efficient approximation to the commonly used Gaussian fields (e.g., Kriging), and compared with Gaussian fields, GMRFs enjoy a series of appealing features, such as fast computation and easily accounting for heterogeneities in spatial data (e.g, point and areal). This paper represents each spatial dataset as a GMRF and integrates them into a state-space form to statistically model the temporal dynamics. Different types of spatial measurements (e.g., categorical, count or continuous), can be accounted for by according link functions. A fast alternative to MCMC framework, so-called Integrated Nested Laplace Approximation (INLA), was adopted for model inference.Preliminary case studies will be conducted to showcase the advantages of the described framework. In the first case, we apply the proposed method for modeling the water table elevation of Ogallala aquifer over the past decades. In the second case, we analyze the

  17. A Practical Ontology Framework for Static Model Analysis

    DTIC Science & Technology

    2011-04-26

    throughout the model. We implement our analysis framework on top of Ptolemy II [3], an extensible open source model-based design tool written in Java...While Ptolemy II makes a good testbed for im- plementing and experimenting with new analyses, we also feel that the techniques we present here are...broadly use- ful. For this reason, we aim to make our analysis frame- work orthogonal to the execution semantics of Ptolemy II, allowing it to be

  18. Possibilities: A framework for modeling students' deductive reasoning in physics

    NASA Astrophysics Data System (ADS)

    Gaffney, Jonathan David Housley

    Students often make errors when trying to solve qualitative or conceptual physics problems, and while many successful instructional interventions have been generated to prevent such errors, the process of deduction that students use when solving physics problems has not been thoroughly studied. In an effort to better understand that reasoning process, I have developed a new framework, which is based on the mental models framework in psychology championed by P. N. Johnson-Laird. My new framework models how students search possibility space when thinking about conceptual physics problems and suggests that errors arise from failing to flesh out all possibilities. It further suggests that instructional interventions should focus on making apparent those possibilities, as well as all physical consequences those possibilities would incur. The possibilities framework emerged from the analysis of data from a unique research project specifically invented for the purpose of understanding how students use deductive reasoning. In the selection task, participants were given a physics problem along with three written possible solutions with the goal of identifying which one of the three possible solutions was correct. Each participant was also asked to identify the errors in the incorrect solutions. For the study presented in this dissertation, participants not only performed the selection task individually on four problems, but they were also placed into groups of two or three and asked to discuss with each other the reasoning they used in making their choices and attempt to reach a consensus about which solution was correct. Finally, those groups were asked to work together to perform the selection task on three new problems. The possibilities framework appropriately models the reasoning that students use, and it makes useful predictions about potentially helpful instructional interventions. The study reported in this dissertation emphasizes the useful insight the

  19. An enhanced BSIM modeling framework for selfheating aware circuit design

    NASA Astrophysics Data System (ADS)

    Schleyer, M.; Leuschner, S.; Baumgartner, P.; Mueller, J.-E.; Klar, H.

    2014-11-01

    This work proposes a modeling framework to enhance the industry-standard BSIM4 MOSFET models with capabilities for coupled electro-thermal simulations. An automated simulation environment extracts thermal information from model data as provided by the semiconductor foundry. The standard BSIM4 model is enhanced with a Verilog-A based wrapper module, adding thermal nodes which can be connected to a thermal-equivalent RC network. The proposed framework allows a fully automated extraction process based on the netlist of the top-level design and the model library. A numerical analysis tool is used to control the extraction flow and to obtain all required parameters. The framework is used to model self-heating effects on a fully integrated class A/AB power amplifier (PA) designed in a standard 65 nm CMOS process. The PA is driven with +30 dBm output power, leading to an average temperature rise of approximately 40 °C over ambient temperature.

  20. A modeling framework for system restoration from cascading failures.

    PubMed

    Liu, Chaoran; Li, Daqing; Zio, Enrico; Kang, Rui

    2014-01-01

    System restoration from cascading failures is an integral part of the overall defense against catastrophic breakdown in networked critical infrastructures. From the outbreak of cascading failures to the system complete breakdown, actions can be taken to prevent failure propagation through the entire network. While most analysis efforts have been carried out before or after cascading failures, restoration during cascading failures has been rarely studied. In this paper, we present a modeling framework to investigate the effects of in-process restoration, which depends strongly on the timing and strength of the restoration actions. Furthermore, in the model we also consider additional disturbances to the system due to restoration actions themselves. We demonstrate that the effect of restoration is also influenced by the combination of system loading level and restoration disturbance. Our modeling framework will help to provide insights on practical restoration from cascading failures and guide improvements of reliability and resilience of actual network systems.

  1. A Modeling Framework for System Restoration from Cascading Failures

    PubMed Central

    Liu, Chaoran; Li, Daqing; Zio, Enrico; Kang, Rui

    2014-01-01

    System restoration from cascading failures is an integral part of the overall defense against catastrophic breakdown in networked critical infrastructures. From the outbreak of cascading failures to the system complete breakdown, actions can be taken to prevent failure propagation through the entire network. While most analysis efforts have been carried out before or after cascading failures, restoration during cascading failures has been rarely studied. In this paper, we present a modeling framework to investigate the effects of in-process restoration, which depends strongly on the timing and strength of the restoration actions. Furthermore, in the model we also consider additional disturbances to the system due to restoration actions themselves. We demonstrate that the effect of restoration is also influenced by the combination of system loading level and restoration disturbance. Our modeling framework will help to provide insights on practical restoration from cascading failures and guide improvements of reliability and resilience of actual network systems. PMID:25474408

  2. `Dhara': An Open Framework for Critical Zone Modeling

    NASA Astrophysics Data System (ADS)

    Le, P. V.; Kumar, P.

    2016-12-01

    Processes in the Critical Zone, which sustain terrestrial life, are tightly coupled across hydrological, physical, biological, chemical, pedological, geomorphological and ecological domains over both short and long timescales. Observations and quantification of the Earth's surface across these domains using emerging high resolution measurement technologies such as light detection and ranging (lidar) and hyperspectral remote sensing are enabling us to characterize fine scale landscape attributes over large spatial areas. This presents a unique opportunity to develop novel approaches to model the Critical Zone that can capture fine scale intricate dependencies across the different processes in 3D. The development of interdisciplinary tools that transcend individual disciplines and capture new levels of complexity and emergent properties is at the core of Critical Zone science. Here we introduce an open framework for high-performance computing model (`Dhara') for modeling complex processes in the Critical Zone. The framework is designed to be modular in structure with the aim to create uniform and efficient tools to facilitate and leverage process modeling. It also provides flexibility to maintain, collaborate, and co-develop additional components by the scientific community. We show the essential framework that simulates ecohydrologic dynamics, and surface - sub-surface coupling in 3D using hybrid parallel CPU-GPU. We demonstrate that the open framework in Dhara is feasible for detailed, multi-processes, and large-scale modeling of the Critical Zone, which opens up exciting possibilities. We will also present outcomes from a Modeling Summer Institute led by Intensively Managed Critical Zone Observatory (IMLCZO) with representation from several CZOs and international representatives.

  3. Open source data assimilation framework for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

    2013-04-01

    An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

  4. A new framework for an electrophotographic printer model

    NASA Astrophysics Data System (ADS)

    Colon-Lopez, Fermin A.

    Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the

  5. Mechanisms of Soil Aggregation: a biophysical modeling framework

    NASA Astrophysics Data System (ADS)

    Ghezzehei, T. A.; Or, D.

    2016-12-01

    Soil aggregation is one of the main crosscutting concepts in all sub-disciplines and applications of soil science from agriculture to climate regulation. The concept generally refers to adhesion of primary soil particles into distinct units that remain stable when subjected to disruptive forces. It is one of the most sensitive soil qualities that readily respond to disturbances such as cultivation, fire, drought, flooding, and changes in vegetation. These changes are commonly quantified and incorporated in soil models indirectly as alterations in carbon content and type, bulk density, aeration, permeability, as well as water retention characteristics. Soil aggregation that is primarily controlled by organic matter generally exhibits hierarchical organization of soil constituents into stable units that range in size from a few microns to centimeters. However, this conceptual model of soil aggregation as the key unifying mechanism remains poorly quantified and is rarely included in predictive soil models. Here we provide a biophysical framework for quantitative and predictive modeling of soil aggregation and its attendant soil characteristics. The framework treats aggregates as hotspots of biological, chemical and physical processes centered around roots and root residue. We keep track of the life cycle of an individual aggregate from it genesis in the rhizosphere, fueled by rhizodeposition and mediated by vigorous microbial activity, until its disappearance when the root-derived resources are depleted. The framework synthesizes current understanding of microbial life in porous media; water holding and soil binding capacity of biopolymers; and environmental controls on soil organic matter dynamics. The framework paves a way for integration of processes that are presently modeled as disparate or poorly coupled processes, including storage and protection of carbon, microbial activity, greenhouse gas fluxes, movement and storage of water, resistance of soils against

  6. Framework for the Parametric System Modeling of Space Exploration Architectures

    NASA Technical Reports Server (NTRS)

    Komar, David R.; Hoffman, Jim; Olds, Aaron D.; Seal, Mike D., II

    2008-01-01

    This paper presents a methodology for performing architecture definition and assessment prior to, or during, program formulation that utilizes a centralized, integrated architecture modeling framework operated by a small, core team of general space architects. This framework, known as the Exploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), enables: 1) a significantly larger fraction of an architecture trade space to be assessed in a given study timeframe; and 2) the complex element-to-element and element-to-system relationships to be quantitatively explored earlier in the design process. Discussion of the methodology advantages and disadvantages with respect to the distributed study team approach typically used within NASA to perform architecture studies is presented along with an overview of EXAMINE s functional components and tools. An example Mars transportation system architecture model is used to demonstrate EXAMINE s capabilities in this paper. However, the framework is generally applicable for exploration architecture modeling with destinations to any celestial body in the solar system.

  7. A VGI data integration framework based on linked data model

    NASA Astrophysics Data System (ADS)

    Wan, Lin; Ren, Rongrong

    2015-12-01

    This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

  8. An Intercomparison of 2-D Models Within a Common Framework

    NASA Technical Reports Server (NTRS)

    Weisenstein, Debra K.; Ko, Malcolm K. W.; Scott, Courtney J.; Jackman, Charles H.; Fleming, Eric L.; Considine, David B.; Kinnison, Douglas E.; Connell, Peter S.; Rotman, Douglas A.; Bhartia, P. K. (Technical Monitor)

    2002-01-01

    A model intercomparison among the Atmospheric and Environmental Research (AER) 2-D model, the Goddard Space Flight Center (GSFC) 2-D model, and the Lawrence Livermore National Laboratory 2-D model allows us to separate differences due to model transport from those due to the model's chemical formulation. This is accomplished by constructing two hybrid models incorporating the transport parameters of the GSFC and LLNL models within the AER model framework. By comparing the results from the native models (AER and e.g. GSFC) with those from the hybrid model (e.g. AER chemistry with GSFC transport), differences due to chemistry and transport can be identified. For the analysis, we examined an inert tracer whose emission pattern is based on emission from a High Speed Civil Transport (HSCT) fleet; distributions of trace species in the 2015 atmosphere; and the response of stratospheric ozone to an HSCT fleet. Differences in NO(y) in the upper stratosphere are found between models with identical transport, implying different model representations of atmospheric chemical processes. The response of O3 concentration to HSCT aircraft emissions differs in the models from both transport-dominated differences in the HSCT-induced perturbations of H2O and NO(y) as well as from differences in the model represent at ions of O3 chemical processes. The model formulations of cold polar processes are found to be the most significant factor in creating large differences in the calculated ozone perturbations

  9. An Integrated Modeling Framework for Probable Maximum Precipitation and Flood

    NASA Astrophysics Data System (ADS)

    Gangrade, S.; Rastogi, D.; Kao, S. C.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

    2015-12-01

    With the increasing frequency and magnitude of extreme precipitation and flood events projected in the future climate, there is a strong need to enhance our modeling capabilities to assess the potential risks on critical energy-water infrastructures such as major dams and nuclear power plants. In this study, an integrated modeling framework is developed through high performance computing to investigate the climate change effects on probable maximum precipitation (PMP) and probable maximum flood (PMF). Multiple historical storms from 1981-2012 over the Alabama-Coosa-Tallapoosa River Basin near the Atlanta metropolitan area are simulated by the Weather Research and Forecasting (WRF) model using the Climate Forecast System Reanalysis (CFSR) forcings. After further WRF model tuning, these storms are used to simulate PMP through moisture maximization at initial and lateral boundaries. A high resolution hydrological model, Distributed Hydrology-Soil-Vegetation Model, implemented at 90m resolution and calibrated by the U.S. Geological Survey streamflow observations, is then used to simulate the corresponding PMF. In addition to the control simulation that is driven by CFSR, multiple storms from the Community Climate System Model version 4 under the Representative Concentrations Pathway 8.5 emission scenario are used to simulate PMP and PMF in the projected future climate conditions. The multiple PMF scenarios developed through this integrated modeling framework may be utilized to evaluate the vulnerability of existing energy-water infrastructures with various aspects associated PMP and PMF.

  10. A Structural Model Decomposition Framework for Systems Health Management

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

    2013-01-01

    Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

  11. Modelling Framework and Assistive Device for Peripheral Intravenous Injections

    NASA Astrophysics Data System (ADS)

    Kam, Kin F.; Robinson, Martin P.; Gilbert, Mathew A.; Pelah, Adar

    2016-02-01

    Intravenous access for blood sampling or drug administration that requires peripheral venepuncture is perhaps the most common invasive procedure practiced in hospitals, clinics and general practice surgeries.We describe an idealised mathematical framework for modelling the dynamics of the peripheral venepuncture process. Basic assumptions of the model are confirmed through motion analysis of needle trajectories during venepuncture, taken from video recordings of a skilled practitioner injecting into a practice kit. The framework is also applied to the design and construction of a proposed device for accurate needle guidance during venepuncture administration, assessed as consistent and repeatable in application and does not lead to over puncture. The study provides insights into the ubiquitous peripheral venepuncture process and may contribute to applications in training and in the design of new devices, including for use in robotic automation.

  12. A Framework for Modeling and Simulation of the Artificial

    DTIC Science & Technology

    2012-01-01

    style of symphonic, folk, or jazz . A musical performance can also therefore have an ensemble of orches- tra, small group, or soloist. With no...constraint m3 :musical-performance (==> (equale (e@ style) jazz ) (or (equale (e@ ensemble) small-group) (equale (e@ ensemble) orchestra)))) (orv (ifv...equale (e@ style) jazz ) (assert! (orv (equale (e@ ensemble) orchestra) (equale (e@ ensemble) small-group))))) A Framework for Modeling and Simulation of

  13. Cross-Layer Modeling Framework for Energy-Efficient Resilience

    DTIC Science & Technology

    2014-04-01

    ignored in concept-phase definitions of power -aware chip- and system-level (micro)architectural proposals. In this paper, we describe our ongoing...thrust is on developing an analytical modeling framework that enables the study of fundamental power -performance- reliability trade-offs, while...leakage storage-class technologies as appropriate. T4: Ultra-efficient microarchitecture to provide low power resilience solution support at the

  14. Flexible Modeling of Epidemics with an Empirical Bayes Framework.

    PubMed

    Brooks, Logan C; Farrow, David C; Hyun, Sangwon; Tibshirani, Ryan J; Rosenfeld, Roni

    2015-08-01

    Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic's behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the "Predict the Influenza Season Challenge", with the task of predicting key epidemiological measures for the 2013-2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013-2014 U.S. influenza season, and compare the framework's cross-validated prediction error on historical data to that of a

  15. A coupled multi-physics modeling framework for induced seismicity

    NASA Astrophysics Data System (ADS)

    Karra, S.; Dempsey, D. E.

    2015-12-01

    There is compelling evidence that moderate-magnitude seismicity in the central and eastern US is on the rise. Many of these earthquakes are attributable to anthropogenic injection of fluids into deep formations resulting in incidents where state regulators have even intervened. Earthquakes occur when a high-pressure fluid (water or CO2) enters a fault, reducing its resistance to shear failure and causing runaway sliding. However, induced seismicity does not manifest as a solitary event, but rather as a sequence of earthquakes evolving in time and space. Additionally, one needs to consider the changes in the permeability due to slip within a fault and the subsequent effects on fluid transport and pressure build-up. A modeling framework that addresses the complex two-way coupling between seismicity and fluid-flow is thus needed. In this work, a new parallel physics-based coupled framework for induced seismicity that couples the slip in faults and fluid flow is presented. The framework couples the highly parallel subsurface flow code PFLOTRAN (www.pflotran.org) and a fast Fourier transform based earthquake simulator QK3. Stresses in the fault are evaluated using Biot's formulation in PFLOTRAN and is used to calculate slip in QK3. Permeability is updated based on the slip in the fault which in turn influences flow. Application of the framework to synthetic examples and datasets from Colorado and Oklahoma will also be discussed.

  16. Common and Innovative Visuals: A sparsity modeling framework for video.

    PubMed

    Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

    2014-05-02

    Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

  17. A framework for modeling contaminant impacts on reservoir water quality

    NASA Astrophysics Data System (ADS)

    Jeznach, Lillian C.; Jones, Christina; Matthews, Thomas; Tobiason, John E.; Ahlfeld, David P.

    2016-06-01

    This study presents a framework for using hydrodynamic and water quality models to understand the fate and transport of potential contaminants in a reservoir and to develop appropriate emergency response and remedial actions. In the event of an emergency situation, prior detailed modeling efforts and scenario evaluations allow for an understanding of contaminant plume behavior, including maximum concentrations that could occur at the drinking water intake and contaminant travel time to the intake. A case study assessment of the Wachusett Reservoir, a major drinking water supply for metropolitan Boston, MA, provides an example of an application of the framework and how hydrodynamic and water quality models can be used to quantitatively and scientifically guide management in response to varieties of contaminant scenarios. The model CE-QUAL-W2 was used to investigate the water quality impacts of several hypothetical contaminant scenarios, including hypothetical fecal coliform input from a sewage overflow as well as an accidental railway spill of ammonium nitrate. Scenarios investigated the impacts of decay rates, season, and inter-reservoir transfers on contaminant arrival times and concentrations at the drinking water intake. The modeling study highlights the importance of a rapid operational response by managers to contain a contaminant spill in order to minimize the mass of contaminant that enters the water column, based on modeled reservoir hydrodynamics. The development and use of hydrodynamic and water quality models for surface drinking water sources subject to the potential for contaminant entry can provide valuable guidance for making decisions about emergency response and remediation actions.

  18. Population balance models: a useful complementary modelling framework for future WWTP modelling.

    PubMed

    Nopens, Ingmar; Torfs, Elena; Ducoste, Joel; Vanrolleghem, Peter A; Gernaey, Krist V

    2015-01-01

    Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit processes in wastewater treatment plants could potentially benefit from this framework, especially when distributed dynamics have a significant impact on the overall unit process performance. In these cases, current models that rely on average properties cannot sufficiently capture the true behaviour and even lead to completely wrong conclusions. Examples of distributed properties are bubble size, floc size, crystal size or granule size. In these cases, PBMs can be used to develop new knowledge that can be embedded in our current models to improve their predictive capability. Hence, PBMs should be regarded as a complementary modelling framework to biokinetic models. This paper provides an overview of current applications, future potential and limitations of PBMs in the field of wastewater treatment modelling, thereby looking over the fence to other scientific disciplines.

  19. New model framework and structure and the commonality evaluation model. [concerning unmanned spacecraft projects

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The development of a framework and structure for shuttle era unmanned spacecraft projects and the development of a commonality evaluation model is documented. The methodology developed for model utilization in performing cost trades and comparative evaluations for commonality studies is discussed. The model framework consists of categories of activities associated with the spacecraft system's development process. The model structure describes the physical elements to be treated as separate identifiable entities. Cost estimating relationships for subsystem and program-level components were calculated.

  20. An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

    NASA Technical Reports Server (NTRS)

    Kim, Edward J.; Tedesco, Marco

    2006-01-01

    Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

  1. An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

    NASA Technical Reports Server (NTRS)

    Kim, Edward J.; Tedesco, Marco

    2006-01-01

    Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

  2. Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

    PubMed

    El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

    2017-08-29

    Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

  3. Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks.

    PubMed

    Saa, Pedro A; Nielsen, Lars K

    2017-09-12

    Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive capabilities. In this review, we present an overview of the relevant mathematical frameworks for kinetic formulation, construction and analysis. Starting with kinetic formalisms, we next review statistical methods for parameter inference, as well as recent computational frameworks applied to the construction and analysis of kinetic models. Finally, we discuss opportunities and limitations hindering the development of larger kinetic reconstructions. Copyright © 2017. Published by Elsevier Inc.

  4. Health education leadership development: a conceptual model and competency framework.

    PubMed

    Wright, Kathleen; Hann, Neil; McLeroy, Kenneth R; Steckler, Allan; Matulionis, Rose Marie; Auld, M Elaine; Lancaster, Brick; Weber, Diane L

    2003-07-01

    A National Public Health Education Leadership Institute was developed through collaboration among national health education professional organizations, the Centers for Disease Control and Prevention, and a school of public health. The institute provides health educators in leadership positions throughout the country access to a 15-month integrated and sequential professional leadership development program. This article presents a conceptual model and competency framework for that program. The model contains elements considered critical for design of leadership programs in public health and can be used by both professional development and academic programs to shape their design of leadership curricula.

  5. The ontology model of FrontCRM framework

    NASA Astrophysics Data System (ADS)

    Budiardjo, Eko K.; Perdana, Wira; Franshisca, Felicia

    2013-03-01

    Adoption and implementation of Customer Relationship Management (CRM) is not merely a technological installation, but the emphasis is more on the application of customer-centric philosophy and culture as a whole. CRM must begin at the level of business strategy, the only level that thorough organizational changes are possible to be done. Changes agenda can be directed to each departmental plans, and supported by information technology. Work processes related to CRM concept include marketing, sales, and services. FrontCRM is developed as framework to guide in identifying business processes related to CRM in which based on the concept of strategic planning approach. This leads to processes and practices identification in every process area related to marketing, sales, and services. The Ontology model presented on this paper by means serves as tools to avoid framework misunderstanding, to define practices systematically within process area and to find CRM software features related to those practices.

  6. Concepts as Semantic Pointers: A Framework and Computational Model.

    PubMed

    Blouw, Peter; Solodkin, Eugene; Thagard, Paul; Eliasmith, Chris

    2016-07-01

    The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called "semantic pointers." Semantic pointers are symbol-like representations that result from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts.

  7. A General Framework for Multiphysics Modeling Based on Numerical Averaging

    NASA Astrophysics Data System (ADS)

    Lunati, I.; Tomin, P.

    2014-12-01

    In the last years, multiphysics (hybrid) modeling has attracted increasing attention as a tool to bridge the gap between pore-scale processes and a continuum description at the meter-scale (laboratory scale). This approach is particularly appealing for complex nonlinear processes, such as multiphase flow, reactive transport, density-driven instabilities, and geomechanical coupling. We present a general framework that can be applied to all these classes of problems. The method is based on ideas from the Multiscale Finite-Volume method (MsFV), which has been originally developed for Darcy-scale application. Recently, we have reformulated MsFV starting with a local-global splitting, which allows us to retain the original degree of coupling for the local problems and to use spatiotemporal adaptive strategies. The new framework is based on the simple idea that different characteristic temporal scales are inherited from different spatial scales, and the global and the local problems are solved with different temporal resolutions. The global (coarse-scale) problem is constructed based on a numerical volume-averaging paradigm and a continuum (Darcy-scale) description is obtained by introducing additional simplifications (e.g., by assuming that pressure is the only independent variable at the coarse scale, we recover an extended Darcy's law). We demonstrate that it is possible to adaptively and dynamically couple the Darcy-scale and the pore-scale descriptions of multiphase flow in a single conceptual and computational framework. Pore-scale problems are solved only in the active front region where fluid distribution changes with time. In the rest of the domain, only a coarse description is employed. This framework can be applied to other important problems such as reactive transport and crack propagation. As it is based on a numerical upscaling paradigm, our method can be used to explore the limits of validity of macroscopic models and to illuminate the meaning of

  8. PyCatch: catchment modelling in the PCRaster framework

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Lana-Renault, Noemí; Schmitz, Oliver

    2015-04-01

    PCRaster is an open source software framework for the construction and execution of stochastic, spatio-temporal, forward, models. It provides a large number of spatial operations on raster maps, with an emphasis on operations that are capable of transporting material (water, sediment) over a drainage network. These operations have been written in C++ and are provided to the model builder as Python functions. Models are constructed by combining these functions in a Python script. To ease implementation of models that use time steps and Monte Carlo iterations, the software comes with a Python framework providing control flow for temporal modelling and Monte Carlo simulation, including options for Bayesian data assimilation (Ensemble Kalman Filter, Particle Filter). A sophisticated visualization tool is provided capable of visualizing, animating, and exploring stochastic, spatio-temporal input or model output data. PCRaster is used for construction of for instance hydrological models (hillslope to global scale), land use change models, and geomorphological models. It is still being improved upon, for instance by adding under the hood functionality for executing models on multiple CPU cores, and by adding components for agent-based and network simulation. The software runs in MS Windows and Linux and is available at http://www.pcraster.eu. We provide an extensive set of online course materials (partly available free of charge). Using the PCRaster software framework, we recently developed the PyCatch model components for hydrological modelling and land degradation modelling at catchment scale. The PyCatch components run at time steps of seconds to weeks, and grid cell sizes of approximately 1-100 m, which can be selected depending on the case study for which PyCatch is used. Hydrological components currently implemented include classes for simulation of incoming solar radiation, evapotranspiration (Penman-Monteith), surface storage, infiltration (Green and Ampt

  9. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  10. Modeling air pollution in the Tracking and Analysis Framework (TAF)

    SciTech Connect

    Shannon, J.D.

    1998-12-31

    The Tracking and Analysis Framework (TAF) is a set of interactive computer models for integrated assessment of the Acid Rain Provisions (Title IV) of the 1990 Clean Air Act Amendments. TAF is designed to execute in minutes on a personal computer, thereby making it feasible for a researcher or policy analyst to examine quickly the effects of alternate modeling assumptions or policy scenarios. Because the development of TAF involves researchers in many different disciplines, TAF has been given a modular structure. In most cases, the modules contain reduced-form models that are based on more complete models exercised off-line. The structure of TAF as of December 1996 is shown. Both the Atmospheric Pathways Module produce estimates for regional air pollution variables.

  11. Generalized framework for context-specific metabolic model extraction methods

    PubMed Central

    Robaina Estévez, Semidán; Nikoloski, Zoran

    2014-01-01

    Genome-scale metabolic models (GEMs) are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application. PMID:25285097

  12. A logic model framework for community nutrition education.

    PubMed

    Medeiros, Lydia C; Butkus, Sue Nicholson; Chipman, Helen; Cox, Ruby H; Jones, Larry; Little, Deborah

    2005-01-01

    Logic models are a practical method for systematically collecting impact data for community nutrition efforts, such as the Food Stamp Nutrition Education program. This report describes the process used to develop and test the Community Nutrition Education Logic Model and the results of a pilot study to determine whether national evaluation data could be captured without losing flexibility of programming and evaluation at the state level. The objectives were to develop an evaluation framework based on the Logic Model to include dietary quality, food safety, food security, and shopping behavior/food resource management and to develop a training mechanism for use. The portability feature of the model should allow application to a variety of community education programs.

  13. A computational framework for modeling targets as complex adaptive systems

    NASA Astrophysics Data System (ADS)

    Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

    2017-05-01

    Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

  14. Flexible Modeling of Epidemics with an Empirical Bayes Framework

    PubMed Central

    Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon; Tibshirani, Ryan J.; Rosenfeld, Roni

    2015-01-01

    Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to

  15. Archetype Model-Driven Development Framework for EHR Web System

    PubMed Central

    Kimura, Eizen; Ishihara, Ken

    2013-01-01

    Objectives This article describes the Web application framework for Electronic Health Records (EHRs) we have developed to reduce construction costs for EHR sytems. Methods The openEHR project has developed clinical model driven architecture for future-proof interoperable EHR systems. This project provides the specifications to standardize clinical domain model implementations, upon which the ISO/CEN 13606 standards are based. The reference implementation has been formally described in Eiffel. Moreover C# and Java implementations have been developed as reference. While scripting languages had been more popular because of their higher efficiency and faster development in recent years, they had not been involved in the openEHR implementations. From 2007, we have used the Ruby language and Ruby on Rails (RoR) as an agile development platform to implement EHR systems, which is in conformity with the openEHR specifications. Results We implemented almost all of the specifications, the Archetype Definition Language parser, and RoR scaffold generator from archetype. Although some problems have emerged, most of them have been resolved. Conclusions We have provided an agile EHR Web framework, which can build up Web systems from archetype models using RoR. The feasibility of the archetype model to provide semantic interoperability of EHRs has been demonstrated and we have verified that that it is suitable for the construction of EHR systems. PMID:24523991

  16. Operationalizing the Space Weather Modeling Framework: Challenges and Resolutions

    NASA Astrophysics Data System (ADS)

    Welling, D. T.; Gombosi, T. I.; Toth, G.; Singer, H. J.; Millward, G. H.; Balch, C. C.; Cash, M. D.

    2016-12-01

    Predicting ground-based magnetic perturbations is a critical step towards specifying and predicting geomagnetically induced currents (GICs) in high voltage transmission lines. Currently, the Space Weather Modeling Framework (SWMF), a flexible modeling framework for simulating the multi-scale space environment, is being transitioned from research to operational use (R2O) by NOAA's Space Weather Prediction Center. Upon completion of this transition, the SWMF will provide localized time-varying magnetic field (dB/dt) predictions using real-time solar wind observations from L1 and the F10.7 proxy for EUV as model input. This presentation chronicles the challenges encountered during the R2O transition of the SWMF. Because operations relies on frequent calculations of global surface dB/dt, new optimizations were required to keep the model running faster than real time. Additionally, several singular situations arose during the 30-day robustness test that required immediate attention. Solutions and strategies for overcoming these issues will be presented. This includes new failsafe options for code execution, new physics and coupling parameters, and the development of an automated validation suite that allows us to monitor performance with code evolution. Finally, the operations-to-research (O2R) impact on SWMF-related research is presented. The lessons learned from this work are valuable and instructive for the space weather community as further R2O progress is made.

  17. Archetype Model-Driven Development Framework for EHR Web System.

    PubMed

    Kobayashi, Shinji; Kimura, Eizen; Ishihara, Ken

    2013-12-01

    This article describes the Web application framework for Electronic Health Records (EHRs) we have developed to reduce construction costs for EHR sytems. The openEHR project has developed clinical model driven architecture for future-proof interoperable EHR systems. This project provides the specifications to standardize clinical domain model implementations, upon which the ISO/CEN 13606 standards are based. The reference implementation has been formally described in Eiffel. Moreover C# and Java implementations have been developed as reference. While scripting languages had been more popular because of their higher efficiency and faster development in recent years, they had not been involved in the openEHR implementations. From 2007, we have used the Ruby language and Ruby on Rails (RoR) as an agile development platform to implement EHR systems, which is in conformity with the openEHR specifications. We implemented almost all of the specifications, the Archetype Definition Language parser, and RoR scaffold generator from archetype. Although some problems have emerged, most of them have been resolved. We have provided an agile EHR Web framework, which can build up Web systems from archetype models using RoR. The feasibility of the archetype model to provide semantic interoperability of EHRs has been demonstrated and we have verified that that it is suitable for the construction of EHR systems.

  18. Service-Oriented Approach to Coupling Earth System Models and Modeling Frameworks

    NASA Astrophysics Data System (ADS)

    Goodall, J. L.; Saint, K. D.; Ercan, M. B.; Briley, L. J.; Murphy, S.; You, H.; DeLuca, C.; Rood, R. B.

    2012-12-01

    Modeling water systems often requires coupling models across traditional Earth science disciplinary boundaries. While there has been significant effort within various Earth science disciplines (e.g., atmospheric science, hydrology, and Earth surface dynamics) to create models and, more recently, modeling frameworks, there has been less work on methods for coupling across disciplinary-specific models and modeling frameworks. We present work investigating one possible method for coupling across disciplinary-specific Earth system models and modeling frameworks: service-oriented architectures. In a service-oriented architecture, models act as distinct units or components within a system and are designed to pass well defined messages to consumers of the service. While the approach offers the potential to couple heterogeneous computational models by allowing a high degree of autonomy across models of the Earth system, there are significant scientific and technical challenges to be addressed when coupling models designed for different communities and built for different modeling frameworks. We have addressed some of these challenges through a case study where we coupled a hydrologic model compliant with the OpenMI standard with an atmospheric model compliant with the EMSF standard. In this case study, the two models were coupled through data exchanges of boundary conditions enabled by exposing the atmospheric model as a web service. A discussion of the technical and scientific challenges, some that we have addressed and others that remain open, will be presented including differences in computer architectures, data semantics, and spatial scales between the coupled models.

  19. LQCD workflow execution framework: Models, provenance and fault-tolerance

    NASA Astrophysics Data System (ADS)

    Piccoli, Luciano; Dubey, Abhishek; Simone, James N.; Kowalkowlski, James B.

    2010-04-01

    Large computing clusters used for scientific processing suffer from systemic failures when operated over long continuous periods for executing workflows. Diagnosing job problems and faults leading to eventual failures in this complex environment is difficult, specifically when the success of an entire workflow might be affected by a single job failure. In this paper, we introduce a model-based, hierarchical, reliable execution framework that encompass workflow specification, data provenance, execution tracking and online monitoring of each workflow task, also referred to as participants. The sequence of participants is described in an abstract parameterized view, which is translated into a concrete data dependency based sequence of participants with defined arguments. As participants belonging to a workflow are mapped onto machines and executed, periodic and on-demand monitoring of vital health parameters on allocated nodes is enabled according to pre-specified rules. These rules specify conditions that must be true pre-execution, during execution and post-execution. Monitoring information for each participant is propagated upwards through the reflex and healing architecture, which consists of a hierarchical network of decentralized fault management entities, called reflex engines. They are instantiated as state machines or timed automatons that change state and initiate reflexive mitigation action(s) upon occurrence of certain faults. We describe how this cluster reliability framework is combined with the workflow execution framework using formal rules and actions specified within a structure of first order predicate logic that enables a dynamic management design that reduces manual administrative workload, and increases cluster-productivity.

  20. A modular Human Exposure Model (HEM) framework to ...

    EPA Pesticide Factsheets

    Life Cycle Impact Analysis (LCIA) has proven to be a valuable tool for systematically comparing processes and products, and has been proposed for use in Chemical Alternatives Analysis (CAA). The exposure assessment portion of the human health impact scores of LCIA has historically focused on far-field sources (environmentally mediated exposures) while research has shown that use related exposures, (near-field exposures) typically dominate population exposure. Characterizing the human health impacts of chemicals in consumer products over the life cycle of these products requires an evaluation of both near-field as well far-field sources. Assessing the impacts of the near-field exposures requires bridging the scientific and technical gaps that currently prevent the harmonious use of the best available methods and tools from the fields of LCIA and human health exposure and risk assessment. The U.S. EPA’s Chemical Safety and Sustainability LC-HEM project is developing the Human Exposure Model (HEM) to assess near-field exposures to chemicals that occur to various populations over the life cycle of a commercial product. The HEM will be a publically available, web-based, modular system which will allow for the evaluation of chemical/product impacts in a LCIA framework to support CAA. We present here an overview of the framework for the modular HEM system. The framework includes a data flow diagram of in-progress and future planned modules, the definition of each mod

  1. A modular Human Exposure Model (HEM) framework to ...

    EPA Pesticide Factsheets

    Life Cycle Impact Analysis (LCIA) has proven to be a valuable tool for systematically comparing processes and products, and has been proposed for use in Chemical Alternatives Analysis (CAA). The exposure assessment portion of the human health impact scores of LCIA has historically focused on far-field sources (environmentally mediated exposures) while research has shown that use related exposures, (near-field exposures) typically dominate population exposure. Characterizing the human health impacts of chemicals in consumer products over the life cycle of these products requires an evaluation of both near-field as well far-field sources. Assessing the impacts of the near-field exposures requires bridging the scientific and technical gaps that currently prevent the harmonious use of the best available methods and tools from the fields of LCIA and human health exposure and risk assessment. The U.S. EPA’s Chemical Safety and Sustainability LC-HEM project is developing the Human Exposure Model (HEM) to assess near-field exposures to chemicals that occur to various populations over the life cycle of a commercial product. The HEM will be a publically available, web-based, modular system which will allow for the evaluation of chemical/product impacts in a LCIA framework to support CAA. We present here an overview of the framework for the modular HEM system. The framework includes a data flow diagram of in-progress and future planned modules, the definition of each mod

  2. ASSESSING MULTIMEDIA/MULTIPATHWAY EXPOSURE TO ARSENIC USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

    EPA Science Inventory

    A series of case studies is presented focusing on multimedia/multipathway population exposures to arsenic, employing the Population Based Modeling approach of the MENTOR (Modeling Environment for Total Risks) framework. This framework considers currently five exposure routes: i...

  3. ASSESSING MULTIMEDIA/MULTIPATHWAY EXPOSURE TO ARSENIC USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

    EPA Science Inventory

    A series of case studies is presented focusing on multimedia/multipathway population exposures to arsenic, employing the Population Based Modeling approach of the MENTOR (Modeling Environment for Total Risks) framework. This framework considers currently five exposure routes: i...

  4. Deep inelastic phenomena

    SciTech Connect

    Prescott, C.Y.

    1980-10-01

    Nucleon structure as seen in the context of deep inelastic scattering is discussed. The lectures begin with consideration of the quark-parton model. The model forms the basis of understanding lepton-nucleon inelastic scattering. As improved data in lepton-nucleon scattering at high energies became available, the quark-parton model failed to explain some crucial features of these data. At approximately the same time a candidate theory of strong interactions based on a SU(3) gauge theory of color was being discussed in the literature, and new ideas on the explanation of inelastic scattering data became popular. A new theory of strong interactions, now called quantum chromodynamics provides a new framework for understanding the data, with a much stronger theoretical foundation, and seems to explain well the features of the data. The lectures conclude with a look at some recent experiments which provide new data at very high energies. These lectures are concerned primarily with charged lepton inelastic scattering and to a lesser extent with neutrino results. Furthermore, due to time and space limitations, topics such as final state hadron studies, and multi-muon production are omitted here. The lectures concentrate on the more central issues: the quark-parton model and concepts of scaling, scale breaking and the ideas of quantum chromodynamics, the Q/sup 2/ dependence of structure function, moments, and the important parameter R.

  5. A Robust Control Design Framework for Substructure Models

    NASA Technical Reports Server (NTRS)

    Lim, Kyong B.

    1994-01-01

    A framework for designing control systems directly from substructure models and uncertainties is proposed. The technique is based on combining a set of substructure robust control problems by an interface stiffness matrix which appears as a constant gain feedback. Variations of uncertainties in the interface stiffness are treated as a parametric uncertainty. It is shown that multivariable robust control can be applied to generate centralized or decentralized controllers that guarantee performance with respect to uncertainties in the interface stiffness, reduced component modes and external disturbances. The technique is particularly suited for large, complex, and weakly coupled flexible structures.

  6. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  7. An Integrated Framework Advancing Membrane Protein Modeling and Design

    PubMed Central

    Weitzner, Brian D.; Duran, Amanda M.; Tilley, Drew C.; Elazar, Assaf; Gray, Jeffrey J.

    2015-01-01

    Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resolution structural refinement; (3) protein-protein docking; and (4) assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design. PMID:26325167

  8. A hybrid parallel framework for the cellular Potts model simulations

    SciTech Connect

    Jiang, Yi; He, Kejing; Dong, Shoubin

    2009-01-01

    The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).

  9. The Application of Architecture Frameworks to Modelling Exploration Operations Costs

    NASA Technical Reports Server (NTRS)

    Shishko, Robert

    2006-01-01

    Developments in architectural frameworks and system-of-systems thinking have provided useful constructs for systems engineering. DoDAF concepts, language, and formalisms, in particular, provide a natural way of conceptualizing an operations cost model applicable to NASA's space exploration vision. Not all DoDAF products have meaning or apply to a DoDAF inspired operations cost model, but this paper describes how such DoDAF concepts as nodes, systems, and operational activities relate to the development of a model to estimate exploration operations costs. The paper discusses the specific implementation to the Mission Operations Directorate (MOD) operational functions/activities currently being developed and presents an overview of how this powerful representation can apply to robotic space missions as well.

  10. CIMS: A FRAMEWORK FOR INFRASTRUCTURE INTERDEPENDENCY MODELING AND ANALYSIS

    SciTech Connect

    Donald D. Dudenhoeffer; May R. Permann; Milos Manic

    2006-12-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, utilities, telecommunication, and even financial networks. While modeling and simulation tools have provided insight into the behavior of individual infrastructure networks, a far less understood area is that of the interrelationships among multiple infrastructure networks including the potential cascading effects that may result due to these interdependencies. This paper first describes infrastructure interdependencies as well as presenting a formalization of interdependency types. Next the paper describes a modeling and simulation framework called CIMS© and the work that is being conducted at the Idaho National Laboratory (INL) to model and simulate infrastructure interdependencies and the complex behaviors that can result.

  11. A Framework for Modeling Emerging Diseases to Inform Management

    PubMed Central

    Katz, Rachel A.; Richgels, Katherine L.D.; Walsh, Daniel P.; Grant, Evan H.C.

    2017-01-01

    The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge. PMID:27983501

  12. The Application of Architecture Frameworks to Modelling Exploration Operations Costs

    NASA Technical Reports Server (NTRS)

    Shishko, Robert

    2006-01-01

    Developments in architectural frameworks and system-of-systems thinking have provided useful constructs for systems engineering. DoDAF concepts, language, and formalisms, in particular, provide a natural way of conceptualizing an operations cost model applicable to NASA's space exploration vision. Not all DoDAF products have meaning or apply to a DoDAF inspired operations cost model, but this paper describes how such DoDAF concepts as nodes, systems, and operational activities relate to the development of a model to estimate exploration operations costs. The paper discusses the specific implementation to the Mission Operations Directorate (MOD) operational functions/activities currently being developed and presents an overview of how this powerful representation can apply to robotic space missions as well.

  13. An empirical generative framework for computational modeling of language acquisition.

    PubMed

    Waterfall, Heidi R; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

    2010-06-01

    This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of generative grammars from raw CHILDES data and give an account of the generative performance of the acquired grammars. Next, we summarize findings from recent longitudinal and experimental work that suggests how certain statistically prominent structural properties of child-directed speech may facilitate language acquisition. We then present a series of new analyses of CHILDES data indicating that the desired properties are indeed present in realistic child-directed speech corpora. Finally, we suggest how our computational results, behavioral findings, and corpus-based insights can be integrated into a next-generation model aimed at meeting the four requirements of our modeling framework.

  14. A framework for modeling emerging diseases to inform management

    USGS Publications Warehouse

    Russell, Robin E.; Katz, Rachel A.; Richgels, Katherine L.D.; Walsh, Daniel P.; Grant, Evan

    2017-01-01

    The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

  15. A unifying modeling framework for highly multivariate disease mapping.

    PubMed

    Botella-Rocamora, P; Martinez-Beneito, M A; Banerjee, S

    2015-04-30

    Multivariate disease mapping refers to the joint mapping of multiple diseases from regionally aggregated data and continues to be the subject of considerable attention for biostatisticians and spatial epidemiologists. The key issue is to map multiple diseases accounting for any correlations among themselves. Recently, Martinez-Beneito (2013) provided a unifying framework for multivariate disease mapping. While attractive in that it colligates a variety of existing statistical models for mapping multiple diseases, this and other existing approaches are computationally burdensome and preclude the multivariate analysis of moderate to large numbers of diseases. Here, we propose an alternative reformulation that accrues substantial computational benefits enabling the joint mapping of tens of diseases. Furthermore, the approach subsumes almost all existing classes of multivariate disease mapping models and offers substantial insight into the properties of statistical disease mapping models.

  16. Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework

    Treesearch

    Tyler Jon Smith; Lucy Amanda. Marshall

    2010-01-01

    Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are...

  17. A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

    EPA Pesticide Factsheets

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

  18. A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

    EPA Pesticide Factsheets

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

  19. A Hydrological Modeling Framework for Flood Risk Assessment for Japan

    NASA Astrophysics Data System (ADS)

    Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.

    2016-12-01

    Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

  20. A Systems Perspective on Situation Awareness I: Conceptual Framework, Modeling, and Quantitative Measurement

    DTIC Science & Technology

    2003-05-01

    A Systems Perspective on Situation Awareness I: Conceptual Framework , Modeling, and Quantitative Measurement Alex Kirlik (University of...I: Conceptual Framework , Modeling, and Quantitative Measurement 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d...Systems Perspective on Situation Awareness I: Conceptual Framework , Modeling, and Quantitative Measurement ALEX KIRLIK Institute of Aviation

  1. Applying Human Capital Management to Model Manpower Readiness: A Conceptual Framework

    DTIC Science & Technology

    2005-12-01

    CAPITAL MANAGEMENT TO MODEL MANPOWER READINESS: A CONCEPTUAL FRAMEWORK by Pert Chin Ngin December 2005 Associate Advisors: William R...Management to Model Manpower Readiness: A Conceptual Framework 6. AUTHOR(S) Pert Chin Ngin 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S...distribution is unlimited. APPLYING HUMAN CAPITAL MANAGEMENT TO MODEL MANPOWER READINESS: A CONCEPTUAL FRAMEWORK Pert Chin Ngin MAJOR, Republic of

  2. Sol-Terra - AN Operational Space Weather Forecasting Model Framework

    NASA Astrophysics Data System (ADS)

    Bisi, M. M.; Lawrence, G.; Pidgeon, A.; Reid, S.; Hapgood, M. A.; Bogdanova, Y.; Byrne, J.; Marsh, M. S.; Jackson, D.; Gibbs, M.

    2015-12-01

    The SOL-TERRA project is a collaboration between RHEA Tech, the Met Office, and RAL Space funded by the UK Space Agency. The goal of the SOL-TERRA project is to produce a Roadmap for a future coupled Sun-to-Earth operational space weather forecasting system covering domains from the Sun down to the magnetosphere-ionosphere-thermosphere and neutral atmosphere. The first stage of SOL-TERRA is underway and involves reviewing current models that could potentially contribute to such a system. Within a given domain, the various space weather models will be assessed how they could contribute to such a coupled system. This will be done both by reviewing peer reviewed papers, and via direct input from the model developers to provide further insight. Once the models have been reviewed then the optimal set of models for use in support of forecast-based SWE modelling will be selected, and a Roadmap for the implementation of an operational forecast-based SWE modelling framework will be prepared. The Roadmap will address the current modelling capability, knowledge gaps and further work required, and also the implementation and maintenance of the overall architecture and environment that the models will operate within. The SOL-TERRA project will engage with external stakeholders in order to ensure independently that the project remains on track to meet its original objectives. A group of key external stakeholders have been invited to provide their domain-specific expertise in reviewing the SOL-TERRA project at critical stages of Roadmap preparation; namely at the Mid-Term Review, and prior to submission of the Final Report. This stakeholder input will ensure that the SOL-TERRA Roadmap will be enhanced directly through the input of modellers and end-users. The overall goal of the SOL-TERRA project is to develop a Roadmap for an operational forecast-based SWE modelling framework with can be implemented within a larger subsequent activity. The SOL-TERRA project is supported within

  3. An integrated modelling framework for neural circuits with multiple neuromodulators

    PubMed Central

    Vemana, Vinith

    2017-01-01

    Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

  4. An integrated modelling framework for neural circuits with multiple neuromodulators.

    PubMed

    Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

    2017-01-01

    Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

  5. A python framework for environmental model uncertainty analysis

    USGS Publications Warehouse

    White, Jeremy; Fienen, Michael; Doherty, John E.

    2016-01-01

    We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

  6. Modeling of active transmembrane transport in a mixture theory framework.

    PubMed

    Ateshian, Gerard A; Morrison, Barclay; Hung, Clark T

    2010-05-01

    This study formulates governing equations for active transport across semi-permeable membranes within the framework of the theory of mixtures. In mixture theory, which models the interactions of any number of fluid and solid constituents, a supply term appears in the conservation of linear momentum to describe momentum exchanges among the constituents. In past applications, this momentum supply was used to model frictional interactions only, thereby describing passive transport processes. In this study, it is shown that active transport processes, which impart momentum to solutes or solvent, may also be incorporated in this term. By projecting the equation of conservation of linear momentum along the normal to the membrane, a jump condition is formulated for the mechano-electrochemical potential of fluid constituents which is generally applicable to nonequilibrium processes involving active transport. The resulting relations are simple and easy to use, and address an important need in the membrane transport literature.

  7. Modeling the spectral solar irradiance in the SOTERIA Project Framework

    NASA Astrophysics Data System (ADS)

    Vieira, Luis Eduardo; Dudok de Wit, Thierry; Kretzschmar, Matthieu; Cessateur, Gaël

    The evolution of the radiative energy input is a key element to understand the variability of the Earth's neutral and ionized atmospheric components. However, reliable observations are limited to the last decades, when observations realized above the Earth's atmosphere became possible. These observations have provide insights about the variability of the spectral solar irradiance on time scales from days to years, but there is still large uncertainties on the evolu-tion on time scales from decades to centuries. Here we discuss the physics-based modeling of the ultraviolet solar irradiance under development in the Solar-Terrestrial Investigations and Archives (SOTERIA) project framework. In addition, we compare the modeled solar emission with variability observed by LYRA instrument onboard of Proba2 spacecraft.

  8. A Novel Modeling Framework for Heterogeneous Catalyst Design

    NASA Astrophysics Data System (ADS)

    Katare, Santhoji; Bhan, Aditya; Caruthers, James; Delgass, Nicholas; Lauterbach, Jochen; Venkatasubramanian, Venkat

    2002-03-01

    A systems-oriented, integrated knowledge architecture that enables the use of data from High Throughput Experiments (HTE) for catalyst design is being developed. Higher-level critical reasoning is required to extract information efficiently from the increasingly available HTE data and to develop predictive models that can be used for design purposes. Towards this objective, we have developed a framework that aids the catalyst designer in negotiating the data and model complexities. Traditional kinetic and statistical tools have been systematically implemented and novel artificial intelligence tools have been developed and integrated to speed up the process of modeling catalytic reactions. Multiple nonlinear models that describe CO oxidation on supported metals have been screened using qualitative and quantitative features based optimization ideas. Physical constraints of the system have been used to select the optimum model parameters from the multiple solutions to the parameter estimation problem. Preliminary results about the selection of catalyst descriptors that match a target performance and the use of HTE data for refining fundamentals based models will be discussed.

  9. A framework for quantifying net benefits of alternative prognostic models.

    PubMed

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

    2012-01-30

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

  10. Modeling Adhesive Anchors in a Discrete Element Framework

    PubMed Central

    Marcon, Marco; Vorel, Jan; Ninčević, Krešimir; Wan-Wendner, Roman

    2017-01-01

    In recent years, post-installed anchors are widely used to connect structural members and to fix appliances to load-bearing elements. A bonded anchor typically denotes a threaded bar placed into a borehole filled with adhesive mortar. The high complexity of the problem, owing to the multiple materials and failure mechanisms involved, requires a numerical support for the experimental investigation. A reliable model able to reproduce a system’s short-term behavior is needed before the development of a more complex framework for the subsequent investigation of the lifetime of fasteners subjected to various deterioration processes can commence. The focus of this contribution is the development and validation of such a model for bonded anchors under pure tension load. Compression, modulus, fracture and splitting tests are performed on standard concrete specimens. These serve for the calibration and validation of the concrete constitutive model. The behavior of the adhesive mortar layer is modeled with a stress-slip law, calibrated on a set of confined pull-out tests. The model validation is performed on tests with different configurations comparing load-displacement curves, crack patterns and concrete cone shapes. A model sensitivity analysis and the evaluation of the bond stress and slippage along the anchor complete the study. PMID:28786964

  11. Modeling Adhesive Anchors in a Discrete Element Framework.

    PubMed

    Marcon, Marco; Vorel, Jan; Ninčević, Krešimir; Wan-Wendner, Roman

    2017-08-08

    In recent years, post-installed anchors are widely used to connect structural members and to fix appliances to load-bearing elements. A bonded anchor typically denotes a threaded bar placed into a borehole filled with adhesive mortar. The high complexity of the problem, owing to the multiple materials and failure mechanisms involved, requires a numerical support for the experimental investigation. A reliable model able to reproduce a system's short-term behavior is needed before the development of a more complex framework for the subsequent investigation of the lifetime of fasteners subjected to various deterioration processes can commence. The focus of this contribution is the development and validation of such a model for bonded anchors under pure tension load. Compression, modulus, fracture and splitting tests are performed on standard concrete specimens. These serve for the calibration and validation of the concrete constitutive model. The behavior of the adhesive mortar layer is modeled with a stress-slip law, calibrated on a set of confined pull-out tests. The model validation is performed on tests with different configurations comparing load-displacement curves, crack patterns and concrete cone shapes. A model sensitivity analysis and the evaluation of the bond stress and slippage along the anchor complete the study.

  12. An Epidemiological Framework for Modelling Fungicide Dynamics and Control

    PubMed Central

    Castle, Matthew D.; Gilligan, Christopher A.

    2012-01-01

    Defining appropriate policies for controlling the spread of fungal disease in agricultural landscapes requires appropriate theoretical models. Most existing models for the fungicidal control of plant diseases do not explicitly include the dynamics of the fungicide itself, nor do they consider the impact of infection occurring during the host growth phase. We introduce a modelling framework for fungicide application that allows us to consider how “explicit” modelling of fungicide dynamics affects the invasion and persistence of plant pathogens. Specifically, we show that “explicit” models exhibit bistability zones for values of the basic reproductive number () less than one within which the invasion and persistence threshold depends on the initial infection levels. This is in contrast to classical models where invasion and persistence thresholds are solely dependent on . In addition if initial infection occurs during the growth phase then an additional “invasion zone” can exist for even smaller values of . Within this region the system will experience an epidemic that is not able to persist. We further show that ideal fungicides with high levels of effectiveness, low rates of application and low rates of decay lead to the existence of these bistability zones. The results are robust to the inclusion of demographic stochasticity. PMID:22899992

  13. A Categorical Framework for Model Classification in the Geosciences

    NASA Astrophysics Data System (ADS)

    Hauhs, Michael; Trancón y Widemann, Baltasar; Lange, Holger

    2016-04-01

    Models have a mixed record of success in the geosciences. In meteorology, model development and implementation has been among the first and most successful examples of triggering computer technology in science. On the other hand, notorious problems such as the 'equifinality issue' in hydrology lead to a rather mixed reputation of models in other areas. The most successful models in geosciences are applications of dynamic systems theory to non-living systems or phenomena. Thus, we start from the hypothesis that the success of model applications relates to the influence of life on the phenomenon under study. We thus focus on the (formal) representation of life in models. The aim is to investigate whether disappointment in model performance is due to system properties such as heterogeneity and historicity of ecosystems, or rather reflects an abstraction and formalisation problem at a fundamental level. As a formal framework for this investigation, we use category theory as applied in computer science to specify behaviour at an interface. Its methods have been developed for translating and comparing formal structures among different application areas and seems highly suited for a classification of the current "model zoo" in the geosciences. The approach is rather abstract, with a high degree of generality but a low level of expressibility. Here, category theory will be employed to check the consistency of assumptions about life in different models. It will be shown that it is sufficient to distinguish just four logical cases to check for consistency of model content. All four cases can be formalised as variants of coalgebra-algebra homomorphisms. It can be demonstrated that transitions between the four variants affect the relevant observations (time series or spatial maps), the formalisms used (equations, decision trees) and the test criteria of success (prediction, classification) of the resulting model types. We will present examples from hydrology and ecology in

  14. Usage Intention Framework Model: A Fuzzy Logic Interpretation of the Classical Utaut Model

    ERIC Educational Resources Information Center

    Sandaire, Johnny

    2009-01-01

    A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence…

  15. Usage Intention Framework Model: A Fuzzy Logic Interpretation of the Classical Utaut Model

    ERIC Educational Resources Information Center

    Sandaire, Johnny

    2009-01-01

    A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence…

  16. Proposed framework for thermomechanical life modeling of metal matrix composites

    NASA Technical Reports Server (NTRS)

    Halford, Gary R.; Lerch, Bradley A.; Saltsman, James F.

    1993-01-01

    The framework of a mechanics of materials model is proposed for thermomechanical fatigue (TMF) life prediction of unidirectional, continuous-fiber metal matrix composites (MMC's). Axially loaded MMC test samples are analyzed as structural components whose fatigue lives are governed by local stress-strain conditions resulting from combined interactions of the matrix, interfacial layer, and fiber constituents. The metallic matrix is identified as the vehicle for tracking fatigue crack initiation and propagation. The proposed framework has three major elements. First, TMF flow and failure characteristics of in situ matrix material are approximated from tests of unreinforced matrix material, and matrix TMF life prediction equations are numerically calibrated. The macrocrack initiation fatigue life of the matrix material is divided into microcrack initiation and microcrack propagation phases. Second, the influencing factors created by the presence of fibers and interfaces are analyzed, characterized, and documented in equation form. Some of the influences act on the microcrack initiation portion of the matrix fatigue life, others on the microcrack propagation life, while some affect both. Influencing factors include coefficient of thermal expansion mismatch strains, residual (mean) stresses, multiaxial stress states, off-axis fibers, internal stress concentrations, multiple initiation sites, nonuniform fiber spacing, fiber debonding, interfacial layers and cracking, fractured fibers, fiber deflections of crack fronts, fiber bridging of matrix cracks, and internal oxidation along internal interfaces. Equations exist for some, but not all, of the currently identified influencing factors. The third element is the inclusion of overriding influences such as maximum tensile strain limits of brittle fibers that could cause local fractures and ensuing catastrophic failure of surrounding matrix material. Some experimental data exist for assessing the plausibility of the proposed

  17. Quasi-3D Multi-scale Modeling Framework Development

    NASA Astrophysics Data System (ADS)

    Arakawa, A.; Jung, J.

    2008-12-01

    When models are truncated in or near an energetically active range of the spectrum, model physics must be changed as the resolution changes. The model physics of GCMs and that of CRMs are, however, quite different from each other and at present there is no unified formulation of model physics that automatically provides transition between these model physics. The Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is an attempt to bridge this gap. Like the recently proposed Heterogeneous Multiscale Method (HMM) (E and Engquist 2003), MMF combines a macroscopic model, GCM, and a microscopic model, CRM. Unlike the traditional multiscale methods such as the multi-grid and adapted mesh refinement techniques, HMM and MMF are for solving multi-physics problems. They share the common objective "to design combined macroscopic-microscopic computational methods that are much more efficient than solving the full microscopic model and at the same time give the information we need" (E et al. 2008). The question is then how to meet this objective in practice, which can be highly problem dependent. In HHM, the efficiency is gained typically by localization of the microscale problem. Following the pioneering work by Grabowski and Smolarkiewicz (1999) and Grabowski (2001), MMF takes advantage of the fact that 2D CRMs are reasonably successful in simulating deep clouds. In this approach, the efficiency is gained by sacrificing the three-dimensionality of cloud-scale motion. It also "localizes" the algorithm through embedding a CRM in each GCM grid box using cyclic boundary condition. The Q3D MMF is an attempt to reduce the expense due to these constraints by partially including the cloud-scale 3D effects and extending the CRM beyond individual GCM grid boxes. As currently formulated, the Q3D MMF is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic cloud-resolving vector vorticity equation model (VVM) applied to a network of horizontal grids. The network

  18. Structural uncertainty in watershed phosphorus modeling: Toward a stochastic framework

    NASA Astrophysics Data System (ADS)

    Chen, Lei; Gong, Yongwei; Shen, Zhenyao

    2016-06-01

    Structural uncertainty is an important source of model predictive errors, but few studies have been conducted on the error-transitivity from model structure to nonpoint source (NPS) prediction. In this study, we focused on the structural uncertainty caused by the algorithms and equations that are used to describe the phosphorus (P) cycle at the watershed scale. The sensitivity of simulated P to each algorithm/equation was quantified using the Soil and Water Assessment Tool (SWAT) in the Three Gorges Reservoir Area, China. The results indicated that the ratios of C:N and P:N for humic materials, as well as the algorithm of fertilization and P leaching contributed the largest output uncertainties. In comparison, the initiation of inorganic P in the soil layer and the transformation algorithm between P pools are less sensitive for the NPS-P predictions. In addition, the coefficient of variation values were quantified as 0.028-0.086, indicating that the structure-induced uncertainty is minor compared to NPS-P prediction uncertainty caused by the model input and parameters. Using the stochastic framework, the cumulative probability of simulated NPS-P data provided a trade-off between expenditure burden and desired risk. In this sense, this paper provides valuable information for the control of model structural uncertainty, and can be extrapolated to other model-based studies.

  19. BALLView: An object-oriented molecular visualization and modeling framework

    NASA Astrophysics Data System (ADS)

    Moll, Andreas; Hildebrandt, Andreas; Lenhof, Hans-Peter; Kohlbacher, Oliver

    2005-11-01

    We present BALLView, an extensible tool for visualizing and modeling bio-molecular structures. It provides a variety of different models for bio-molecular visualization, e.g. ball-and-stick models, molecular surfaces, or ribbon models. In contrast to most existing visualization tools, BALLView also offers rich functionality for molecular modeling and simulation, including molecular mechanics methods (AMBER and CHARMM force fields), continuum electrostatics methods employing a Finite-Difference Poisson Boltzmann solver, and secondary structure calculation. Results of these computations can be exported as publication quality images or as movies. Even unexperienced users have direct access to this functionality through an intuitive graphical user interface, which makes BALLView particularly useful for teaching. For more advanced users, BALLView is extensible in different ways. Owing to its framework design, extension on the level of C‰+‰‰+ code is very convenient. In addition, an interface to the scripting language Python allows the interactive rapid prototyping of new methods. BALLView is portable and runs on all major platforms (Windows, MacOS X, Linux, most Unix flavors). It is available free of charge under the GNU Public License (GPL) from our website http://www.ballview.org.

  20. Extreme Precipitation in a Multi-Scale Modeling Framework

    NASA Astrophysics Data System (ADS)

    Phillips, M.; Denning, S.; Arabi, M.

    2015-12-01

    Extreme precipitation events are characterized by infrequent but large magnitude accummulatations that generally occur on scales belowthat resolved by the typical Global Climate Model. The Multi-scale Modeling Framework allows for information about the precipitation on these scales to be simulated for long periods of time without the large computational resources required for the use of a full cloud permitting model. The Community Earth System Model was run for 30 years in both its MMF and GCM modes, and the annual maximum series of 24 hour precipitation accumulations were used to estimate the parameters of statistical distributions. The distributions generated from model ouput were then fit to a General Extreme Value distribution and evaluated against observations. These results indicate that the MMF produces extreme precipitation with a statistical distribution that closely resembles that of observations and motivates the continued use of the MMF for analysis of extreme precipitation, and shows an improvement over the traditional GCM. The improvement in statistical distributions of annual maxima is greatest in regions that are dominated by convective precipitation where the small-scale information provided by the MMF heavily influences precipitation processes.

  1. Modelling grain growth in the framework of Rational Extended Thermodynamics

    NASA Astrophysics Data System (ADS)

    Kertsch, Lukas; Helm, Dirk

    2016-05-01

    Grain growth is a significant phenomenon for the thermomechanical processing of metals. Since the mobility of the grain boundaries is thermally activated and energy stored in the grain boundaries is released during their motion, a mutual interaction with the process conditions occurs. To model such phenomena, a thermodynamic framework for the representation of thermomechanical coupling phenomena in metals including a microstructure description is required. For this purpose, Rational Extended Thermodynamics appears to be a useful tool. We apply an entropy principle to derive a thermodynamically consistent model for grain coarsening due to the growth and shrinkage of individual grains. Despite the rather different approaches applied, we obtain a grain growth model which is similar to existing ones and can be regarded as a thermodynamic extension of that by Hillert (1965) to more general systems. To demonstrate the applicability of the model, we compare our simulation results to grain growth experiments in pure copper by different authors, which we are able to reproduce very accurately. Finally, we study the implications of the energy release due to grain growth on the energy balance. The present unified approach combining a microstructure description and continuum mechanics is ready to be further used to develop more elaborate material models for complex thermo-chemo-mechanical coupling phenomena.

  2. Assessment of Solution Uncertainties in Single-Column Modeling Frameworks.

    NASA Astrophysics Data System (ADS)

    Hack, James J.; Pedretti, John A.

    2000-01-01

    Single-column models (SCMs) have been extensively promoted in recent years as an effective means to develop and test physical parameterizations targeted for more complex three-dimensional climate models. Although there are some clear advantages associated with single-column modeling, there are also some significant disadvantages, including the absence of large-scale feedbacks. Basic limitations of an SCM framework can make it difficult to interpret solutions, and at times contribute to rather striking failures to identify even first-order sensitivities as they would be observed in a global climate simulation. This manuscript will focus on one of the basic experimental approaches currently exploited by the single-column modeling community, with an emphasis on establishing the inherent uncertainties in the numerical solutions. The analysis will employ the standard physics package from the NCAR CCM3 and will illustrate the nature of solution uncertainties that arise from nonlinearities in parameterized physics. The results of this study suggest the need to make use of an ensemble methodology when conducting single-column modeling investigations.

  3. Assessment of solution uncertainties in single-column modeling frameworks

    SciTech Connect

    Hack, J.J.; Pedretti, J.A.

    2000-01-15

    Single-column models (SCMs) have been extensively promoted in recent years as an effective means to develop and test physical parameterizations targeted for more complex three-dimensional climate models. Although there are some clear advantages associated with single-column modeling, there are also some significant disadvantages, including the absence of large-scale feedbacks. Basic limitations of an SCM framework can make it difficult to interpret solutions, and at times contribute to rather striking failures to identify even first-order sensitivities as they would be observed in a global climate simulation. This manuscript will focus on one of the basic experimental approaches currently exploited by the single-column modeling community, with an emphasis on establishing the inherent uncertainties in the numerical solutions. The analysis will employ the standard physics package from the NCAR CCM3 and will illustrate the nature of solution uncertainties that arise from nonlinearities in parameterized physics. The results of this study suggest the need to make use of an ensemble methodology when conducting single-column modeling investigations.

  4. A Data Driven Framework for Integrating Regional Climate Models

    NASA Astrophysics Data System (ADS)

    Lansing, C.; Kleese van Dam, K.; Liu, Y.; Elsethagen, T.; Guillen, Z.; Stephan, E.; Critchlow, T.; Gorton, I.

    2012-12-01

    There are increasing needs for research addressing complex climate sensitive issues of concern to decision-makers and policy planners at a regional level. Decisions about allocating scarce water across competing municipal, agricultural, and ecosystem demands is just one of the challenges ahead, along with decisions regarding competing land use priorities such as biofuels, food, and species habitat. Being able to predict the extent of future climate change in the context of introducing alternative energy production strategies requires a new generation of modeling capabilities. We will also need more complete representations of human systems at regional scales, incorporating the influences of population centers, land use, agriculture and existing and planned electrical demand and generation infrastructure. At PNNL we are working towards creating a first-of-a-kind capability known as the Integrated Regional Earth System Model (iRESM). The fundamental goal of the iRESM initiative is the critical analyses of the tradeoffs and consequences of decision and policy making for integrated human and environmental systems. This necessarily combines different scientific processes, bridging different temporal and geographic scales and resolving the semantic differences between them. To achieve this goal, iRESM is developing a modeling framework and supporting infrastructure that enable the scientific team to evaluate different scenarios in light of specific stakeholder questions such as "How do regional changes in mean climate states and climate extremes affect water storage and energy consumption and how do such decisions influence possible mitigation and carbon management schemes?" The resulting capability will give analysts a toolset to gain insights into how regional economies can respond to climate change mitigation policies and accelerated deployment of alternative energy technologies. The iRESM framework consists of a collection of coupled models working with high

  5. A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.

    PubMed

    Garin, Guillaume; Fournier, Christian; Andrieu, Bruno; Houlès, Vianney; Robert, Corinne; Pradal, Christophe

    2014-09-01

    Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both

  6. A modelling framework to simulate foliar fungal epidemics using functional–structural plant models

    PubMed Central

    Garin, Guillaume; Fournier, Christian; Andrieu, Bruno; Houlès, Vianney; Robert, Corinne; Pradal, Christophe

    2014-01-01

    Background and Aims Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional–structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. Methods Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant–environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. Key Results Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. Conclusions This study provides a framework for modelling a large number of pathosystems

  7. A framework for industrial systems modeling and simulation

    SciTech Connect

    Macfarlane, J.; Nachnani, S.; Tsai, L.H.; Kaae, P.; Freund, K.; Hoza, M.; Stahlman, E.

    1995-04-01

    To successfully compete in a global market, manufacturing production systems are being forced to reduce time to market and to provide improved responsiveness to changes in market conditions. The organizations that comprise the business links in the production system must constantly make tradeoffs between time and cost in order to achieve a competitive but quick response to consumer demand. Due to the inherent uncertainty of consumer demand, these tradeoffs are, by definition, made with incomplete information and can incur significant financial and competitive risk to the organization. Partnerships between organizations are a mechanism for increasing the information in the decision making process by combining information from the two partners. Partnerships are inherently difficult to implement due to trust issues. A mechanism for investigating and validating the mutual benefit to partnering would be useful in designing and implementing partnerships. This paper describes the development of a software framework for industrial systems modeling and simulation. The framework provides a mechanism for investigating changes to industrial systems in a manner which minimizes the effort and computational power needed to develop focused simulations. The architecture and it`s component parts are described.

  8. LAMMPS framework for dynamic bonding and an application modeling DNA

    NASA Astrophysics Data System (ADS)

    Svaneborg, Carsten

    2012-08-01

    We have extended the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to support directional bonds and dynamic bonding. The framework supports stochastic formation of new bonds, breakage of existing bonds, and conversion between bond types. Bond formation can be controlled to limit the maximal functionality of a bead with respect to various bond types. Concomitant with the bond dynamics, angular and dihedral interactions are dynamically introduced between newly connected triplets and quartets of beads, where the interaction type is determined from the local pattern of bead and bond types. When breaking bonds, all angular and dihedral interactions involving broken bonds are removed. The framework allows chemical reactions to be modeled, and use it to simulate a simplistic, coarse-grained DNA model. The resulting DNA dynamics illustrates the power of the present framework. Catalogue identifier: AEME_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEME_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 2 243 491 No. of bytes in distributed program, including test data, etc.: 771 Distribution format: tar.gz Programming language: C++ Computer: Single and multiple core servers Operating system: Linux/Unix/Windows Has the code been vectorized or parallelized?: Yes. The code has been parallelized by the use of MPI directives. RAM: 1 Gb Classification: 16.11, 16.12 Nature of problem: Simulating coarse-grain models capable of chemistry e.g. DNA hybridization dynamics. Solution method: Extending LAMMPS to handle dynamic bonding and directional bonds. Unusual features: Allows bonds to be created and broken while angular and dihedral interactions are kept consistent. Additional comments: The distribution file for this program is approximately 36 Mbytes and therefore is not delivered directly

  9. Testing a Conceptual Change Model Framework for Visual Data

    ERIC Educational Resources Information Center

    Finson, Kevin D.; Pedersen, Jon E.

    2015-01-01

    An emergent data analysis technique was employed to test the veracity of a conceptual framework constructed around visual data use and instruction in science classrooms. The framework incorporated all five key components Vosniadou (2007a, 2007b) described as existing in a learner's schema: framework theory, presuppositions, conceptual domains,…

  10. Factors of collaborative working: a framework for a collaboration model.

    PubMed

    Patel, Harshada; Pettitt, Michael; Wilson, John R

    2012-01-01

    The ability of organisations to support collaborative working environments is of increasing importance as they move towards more distributed ways of working. Despite the attention collaboration has received from a number of disparate fields, there is a lack of a unified understanding of the component factors of collaboration. As part of our work on a European Integrated Project, CoSpaces, collaboration and collaborative working and the factors which define it were examined through the literature and new empirical work with a number of partner user companies in the aerospace, automotive and construction sectors. This was to support development of a descriptive human factors model of collaboration - the CoSpaces Collaborative Working Model (CCWM). We identified seven main categories of factors involved in collaboration: Context, Support, Tasks, Interaction Processes, Teams, Individuals, and Overarching Factors, and summarised these in a framework which forms a basis for the model. We discuss supporting evidence for the factors which emerged from our fieldwork with user partners, and use of the model in activities such as collaboration readiness profiling.

  11. Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

    NASA Technical Reports Server (NTRS)

    Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo

    2013-01-01

    One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

  12. A Multiple Reaction Modelling Framework for Microbial Electrochemical Technologies.

    PubMed

    Oyetunde, Tolutola; Sarma, Priyangshu M; Ahmad, Farrukh; Rodríguez, Jorge

    2017-01-04

    A mathematical model for the theoretical evaluation of microbial electrochemical technologies (METs) is presented that incorporates a detailed physico-chemical framework, includes multiple reactions (both at the electrodes and in the bulk phase) and involves a variety of microbial functional groups. The model is applied to two theoretical case studies: (i) A microbial electrolysis cell (MEC) for continuous anodic volatile fatty acids (VFA) oxidation and cathodic VFA reduction to alcohols, for which the theoretical system response to changes in applied voltage and VFA feed ratio (anode-to-cathode) as well as membrane type are investigated. This case involves multiple parallel electrode reactions in both anode and cathode compartments; (ii) A microbial fuel cell (MFC) for cathodic perchlorate reduction, in which the theoretical impact of feed flow rates and concentrations on the overall system performance are investigated. This case involves multiple electrode reactions in series in the cathode compartment. The model structure captures interactions between important system variables based on first principles and provides a platform for the dynamic description of METs involving electrode reactions both in parallel and in series and in both MFC and MEC configurations. Such a theoretical modelling approach, largely based on first principles, appears promising in the development and testing of MET control and optimization strategies.

  13. A Multiple Reaction Modelling Framework for Microbial Electrochemical Technologies

    PubMed Central

    Oyetunde, Tolutola; Sarma, Priyangshu M.; Ahmad, Farrukh; Rodríguez, Jorge

    2017-01-01

    A mathematical model for the theoretical evaluation of microbial electrochemical technologies (METs) is presented that incorporates a detailed physico-chemical framework, includes multiple reactions (both at the electrodes and in the bulk phase) and involves a variety of microbial functional groups. The model is applied to two theoretical case studies: (i) A microbial electrolysis cell (MEC) for continuous anodic volatile fatty acids (VFA) oxidation and cathodic VFA reduction to alcohols, for which the theoretical system response to changes in applied voltage and VFA feed ratio (anode-to-cathode) as well as membrane type are investigated. This case involves multiple parallel electrode reactions in both anode and cathode compartments; (ii) A microbial fuel cell (MFC) for cathodic perchlorate reduction, in which the theoretical impact of feed flow rates and concentrations on the overall system performance are investigated. This case involves multiple electrode reactions in series in the cathode compartment. The model structure captures interactions between important system variables based on first principles and provides a platform for the dynamic description of METs involving electrode reactions both in parallel and in series and in both MFC and MEC configurations. Such a theoretical modelling approach, largely based on first principles, appears promising in the development and testing of MET control and optimization strategies. PMID:28054959

  14. Young diabetics' compliance in the framework of the MIMIC model.

    PubMed

    Kyngäs, H; Hentinen, M; Koivukangas, P; Ohinmaa, A

    1996-11-01

    The compliance of 346 young diabetics aged 13-17 years with health regimens is analysed in the framework of a MIMIC (multiple indicators, multiple causes) model. The data were compiled by means of a questionnaire on compliance, conditions for compliance, the meaning attached to treatment and the impact of the disease, and the model constructed using the LISREL VII programme, treating compliance as an unobserved variable formulated in terms of observed causes (x-variables) and observed indicators (y-variables). The resulting solutions are entirely satisfactory. The goodness-of-fit index is 0.983, the root mean square residual 0.058 and the chi-squared statistic 43.35 (P < 0.001). The values for the individual parameters in the model are also shown to be reliable and valid. The model shows compliance to be indicated by self-care behaviour, responsibility for treatment, intention to pursue the treatment and collaboration with the physician, and to be greatly determined by motivation, experience of the results of treatment and having the energy and will-power to pursue the treatment and, to a lesser extent, by a sense of normality and fear.

  15. A Hierarchical Modeling Framework for Multiple Observer Transect Surveys

    PubMed Central

    Conn, Paul B.; Laake, Jeffrey L.; Johnson, Devin S.

    2012-01-01

    Ecologists often use multiple observer transect surveys to census animal populations. In addition to animal counts, these surveys produce sequences of detections and non-detections for each observer. When combined with additional data (i.e. covariates such as distance from the transect line), these sequences provide the additional information to estimate absolute abundance when detectability on the transect line is less than one. Although existing analysis approaches for such data have proven extremely useful, they have some limitations. For instance, it is difficult to extrapolate from observed areas to unobserved areas unless a rigorous sampling design is adhered to; it is also difficult to share information across spatial and temporal domains or to accommodate habitat-abundance relationships. In this paper, we introduce a hierarchical modeling framework for multiple observer line transects that removes these limitations. In particular, abundance intensities can be modeled as a function of habitat covariates, making it easier to extrapolate to unsampled areas. Our approach relies on a complete data representation of the state space, where unobserved animals and their covariates are modeled using a reversible jump Markov chain Monte Carlo algorithm. Observer detections are modeled via a bivariate normal distribution on the probit scale, with dependence induced by a distance-dependent correlation parameter. We illustrate performance of our approach with simulated data and on a known population of golf tees. In both cases, we show that our hierarchical modeling approach yields accurate inference about abundance and related parameters. In addition, we obtain accurate inference about population-level covariates (e.g. group size). We recommend that ecologists consider using hierarchical models when analyzing multiple-observer transect data, especially when it is difficult to rigorously follow pre-specified sampling designs. We provide a new R package, hierarchical

  16. A Smart Modeling Framework for Integrating BMI-enabled Models as Web Services

    NASA Astrophysics Data System (ADS)

    Jiang, P.; Elag, M.; Kumar, P.; Peckham, S. D.; Liu, R.; Marini, L.; Hsu, L.

    2015-12-01

    Serviced-oriented computing provides an opportunity to couple web service models using semantic web technology. Through this approach, models that are exposed as web services can be conserved in their own local environment, thus making it easy for modelers to maintain and update the models. In integrated modeling, the serviced-oriented loose-coupling approach requires (1) a set of models as web services, (2) the model metadata describing the external features of a model (e.g., variable name, unit, computational grid, etc.) and (3) a model integration framework. We present the architecture of coupling web service models that are self-describing by utilizing a smart modeling framework. We expose models that are encapsulated with CSDMS (Community Surface Dynamics Modeling System) Basic Model Interfaces (BMI) as web services. The BMI-enabled models are self-describing by uncovering models' metadata through BMI functions. After a BMI-enabled model is serviced, a client can initialize, execute and retrieve the meta-information of the model by calling its BMI functions over the web. Furthermore, a revised version of EMELI (Peckham, 2015), an Experimental Modeling Environment for Linking and Interoperability, is chosen as the framework for coupling BMI-enabled web service models. EMELI allows users to combine a set of component models into a complex model by standardizing model interface using BMI as well as providing a set of utilities smoothing the integration process (e.g., temporal interpolation). We modify the original EMELI so that the revised modeling framework is able to initialize, execute and find the dependencies of the BMI-enabled web service models. By using the revised EMELI, an example will be presented on integrating a set of topoflow model components that are BMI-enabled and exposed as web services. Reference: Peckham, S.D. (2014) EMELI 1.0: An experimental smart modeling framework for automatic coupling of self-describing models, Proceedings of HIC 2014

  17. a Framework for AN Open Source Geospatial Certification Model

    NASA Astrophysics Data System (ADS)

    Khan, T. U. R.; Davis, P.; Behr, F.-J.

    2016-06-01

    The geospatial industry is forecasted to have an enormous growth in the forthcoming years and an extended need for well-educated workforce. Hence ongoing education and training play an important role in the professional life. Parallel, in the geospatial and IT arena as well in the political discussion and legislation Open Source solutions, open data proliferation, and the use of open standards have an increasing significance. Based on the Memorandum of Understanding between International Cartographic Association, OSGeo Foundation, and ISPRS this development led to the implementation of the ICA-OSGeo-Lab imitative with its mission "Making geospatial education and opportunities accessible to all". Discussions in this initiative and the growth and maturity of geospatial Open Source software initiated the idea to develop a framework for a worldwide applicable Open Source certification approach. Generic and geospatial certification approaches are already offered by numerous organisations, i.e., GIS Certification Institute, GeoAcademy, ASPRS, and software vendors, i. e., Esri, Oracle, and RedHat. They focus different fields of expertise and have different levels and ways of examination which are offered for a wide range of fees. The development of the certification framework presented here is based on the analysis of diverse bodies of knowledge concepts, i.e., NCGIA Core Curriculum, URISA Body Of Knowledge, USGIF Essential Body Of Knowledge, the "Geographic Information: Need to Know", currently under development, and the Geospatial Technology Competency Model (GTCM). The latter provides a US American oriented list of the knowledge, skills, and abilities required of workers in the geospatial technology industry and influenced essentially the framework of certification. In addition to the theoretical analysis of existing resources the geospatial community was integrated twofold. An online survey about the relevance of Open Source was performed and evaluated with 105

  18. A framework of modeling detector systems for computed tomography simulations

    NASA Astrophysics Data System (ADS)

    Youn, H.; Kim, D.; Kim, S. H.; Kam, S.; Jeon, H.; Nam, J.; Kim, H. K.

    2016-01-01

    Ultimate development in computed tomography (CT) technology may be a system that can provide images with excellent lesion conspicuity with the patient dose as low as possible. Imaging simulation tools have been cost-effectively used for these developments and will continue. For a more accurate and realistic imaging simulation, the signal and noise propagation through a CT detector system has been modeled in this study using the cascaded linear-systems theory. The simulation results are validated in comparisons with the measured results using a laboratory flat-panel micro-CT system. Although the image noise obtained from the simulations at higher exposures is slightly smaller than that obtained from the measurements, the difference between them is reasonably acceptable. According to the simulation results for various exposure levels and additive electronic noise levels, x-ray quantum noise is more dominant than the additive electronic noise. The framework of modeling a CT detector system suggested in this study will be helpful for the development of an accurate and realistic projection simulation model.

  19. Investigating GPDs in the framework of the double distribution model

    NASA Astrophysics Data System (ADS)

    Nazari, F.; Mirjalili, A.

    2016-06-01

    In this paper, we construct the generalized parton distribution (GPD) in terms of the kinematical variables x, ξ, t, using the double distribution model. By employing these functions, we could extract some quantities which makes it possible to gain a three-dimensional insight into the nucleon structure function at the parton level. The main objective of GPDs is to combine and generalize the concepts of ordinary parton distributions and form factors. They also provide an exclusive framework to describe the nucleons in terms of quarks and gluons. Here, we first calculate, in the Double Distribution model, the GPD based on the usual parton distributions arising from the GRV and CTEQ phenomenological models. Obtaining quarks and gluons angular momenta from the GPD, we would be able to calculate the scattering observables which are related to spin asymmetries of the produced quarkonium. These quantities are represented by AN and ALS. We also calculate the Pauli and Dirac form factors in deeply virtual Compton scattering. Finally, in order to compare our results with the existing experimental data, we use the difference of the polarized cross-section for an initial longitudinal leptonic beam and unpolarized target particles (ΔσLU). In all cases, our obtained results are in good agreement with the available experimental data.

  20. Internal modelling under Risk-Based Capital (RBC) framework

    NASA Astrophysics Data System (ADS)

    Ling, Ang Siew; Hin, Pooi Ah

    2015-12-01

    Very often the methods for the internal modelling under the Risk-Based Capital framework make use of the data which are in the form of run-off triangle. The present research will instead extract from a group of n customers, the historical data for the sum insured si of the i-th customer together with the amount paid yij and the amount aij reported but not yet paid in the j-th development year for j = 1, 2, 3, 4, 5, 6. We model the future value (yij+1, aij+1) to be dependent on the present year value (yij, aij) and the sum insured si via a conditional distribution which is derived from a multivariate power-normal mixture distribution. For a group of given customers with different original purchase dates, the distribution of the aggregate claims liabilities may be obtained from the proposed model. The prediction interval based on the distribution for the aggregate claim liabilities is found to have good ability of covering the observed aggregate claim liabilities.

  1. Quasi-3D Algorithm in Multi-scale Modeling Framework

    NASA Astrophysics Data System (ADS)

    Jung, J.; Arakawa, A.

    2008-12-01

    As discussed in the companion paper by Arakawa and Jung, the Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic vector vorticity equation model (VVM) applied to a Q3D network of horizontal grid points. This paper presents an outline of the recently revised Q3D algorithm and a highlight of the results obtained by application of the algorithm to an idealized model setting. The Q3D network of grid points consists of two sets of grid-point arrays perpendicular to each other. For a scalar variable, for example, each set consists of three parallel rows of grid points. Principal and supplementary predictions are made on the central and the two adjacent rows, respectively. The supplementary prediction is to allow the principal prediction be three-dimensional at least to the second-order accuracy. To accommodate a higher-order accuracy and to make the supplementary predictions formally three-dimensional, a few rows of ghost points are added at each side of the array. Values at these ghost points are diagnostically determined by a combination of statistical estimation and extrapolation. The basic structure of the estimation algorithm is determined in view of the global stability of Q3D advection. The algorithm is calibrated using the statistics of past data at and near the intersections of the two sets of grid- point arrays. Since the CRM in the Q3D MMF extends beyond individual GCM boxes, the CRM can be a GCM by itself. However, it is better to couple the CRM with the GCM because (1) the CRM is a Q3D CRM based on a highly anisotropic network of grid points and (2) coupling with a GCM makes it more straightforward to inherit our experience with the conventional GCMs. In the coupled system we have selected, prediction of thermdynamic variables is almost entirely done by the Q3D CRM with no direct forcing by the GCM. The coupling of the dynamics between the two components is through mutual

  2. Evolution of Climate Science Modelling Language within international standards frameworks

    NASA Astrophysics Data System (ADS)

    Lowe, Dominic; Woolf, Andrew

    2010-05-01

    The Climate Science Modelling Language (CSML) was originally developed as part of the NERC Data Grid (NDG) project in the UK. It was one of the first Geography Markup Language (GML) application schemas describing complex feature types for the metocean domain. CSML feature types can be used to describe typical climate products such as model runs or atmospheric profiles. CSML has been successfully used within NDG to provide harmonised access to a number of different data sources. For example, meteorological observations held in heterogeneous databases by the British Atmospheric Data Centre (BADC) and Centre for Ecology and Hydrology (CEH) were served uniformly as CSML features via Web Feature Service. CSML has now been substantially revised to harmonise it with the latest developments in OGC and ISO conceptual modelling for geographic information. In particular, CSML is now aligned with the near-final ISO 19156 Observations & Measurements (O&M) standard. CSML combines the O&M concept of 'sampling features' together with an observation result based on the coverage model (ISO 19123). This general pattern is specialised for particular data types of interest, classified on the basis of sampling geometry and topology. In parallel work, the OGC Met Ocean Domain Working Group has established a conceptual modelling activity. This is a cross-organisational effort aimed at reaching consensus on a common core data model that could be re-used in a number of met-related application areas: operational meteorology, aviation meteorology, climate studies, and the research community. It is significant to note that this group has also identified sampling geometry and topology as a key classification axis for data types. Using the Model Driven Architecture (MDA) approach as adopted by INSPIRE we demonstrate how the CSML application schema is derived from a formal UML conceptual model based on the ISO TC211 framework. By employing MDA tools which map consistently between UML and GML we

  3. Flexible modeling frameworks to replace small ensembles of hydrological models and move toward large ensembles?

    NASA Astrophysics Data System (ADS)

    Addor, Nans; Clark, Martyn P.; Mizukami, Naoki

    2017-04-01

    Climate change impacts on hydrological processes are typically assessed using small ensembles of hydrological models. That is, a handful of hydrological models are typically driven by a larger number of climate models. Such a setup has several limitations. Because the number of hydrological models is small, only a small proportion of the model space is sampled, likely leading to an underestimation of the uncertainties in the projections. Further, sampling is arbitrary: although hydrological models should be selected to provide a representative sample of existing models (in terms of complexity and governing hypotheses), they are instead usually selected based on legacy reasons. Furthermore, running several hydrological models currently constitutes a practical challenge because each model must be setup and calibrated individually. Finally, and probably most importantly, the differences between the projected impacts cannot be directly related to differences between hydrological models, because the models are different in almost every possible aspect. We are hence in a situation in which different hydrological models deliver different projections, but for reasons that are mostly unclear, and in which the uncertainty in the projections is probably underestimated. To overcome these limitations, we are experimenting with the flexible modeling framework FUSE (Framework for Understanding Model Errors). FUSE enables to construct conceptual models piece by piece (in a "pick and mix" approach), so it can be used to generate a large number of models that mimic existing models and/or models that differ from other models in single targeted respect (e.g. how baseflow is generated). FUSE hence allows for controlled modeling experiments, and for a more systematic and exhaustive sampling of the model space. Here we explore climate change impacts over the contiguous USA on a 12km grid using two groups of three models: the first group involves the commonly used models VIC, PRMS and HEC

  4. AN INTEGRATED MODELING FRAMEWORK FOR CARBON MANAGEMENT TECHNOLOGIES

    SciTech Connect

    Anand B. Rao; Edward S. Rubin; Michael B. Berkenpas

    2004-03-01

    CO{sub 2} capture and storage (CCS) is gaining widespread interest as a potential method to control greenhouse gas emissions from fossil fuel sources, especially electric power plants. Commercial applications of CO{sub 2} separation and capture technologies are found in a number of industrial process operations worldwide. Many of these capture technologies also are applicable to fossil fuel power plants, although applications to large-scale power generation remain to be demonstrated. This report describes the development of a generalized modeling framework to assess alternative CO{sub 2} capture and storage options in the context of multi-pollutant control requirements for fossil fuel power plants. The focus of the report is on post-combustion CO{sub 2} capture using amine-based absorption systems at pulverized coal-fired plants, which are the most prevalent technology used for power generation today. The modeling framework builds on the previously developed Integrated Environmental Control Model (IECM). The expanded version with carbon sequestration is designated as IECM-cs. The expanded modeling capability also includes natural gas combined cycle (NGCC) power plants and integrated coal gasification combined cycle (IGCC) systems as well as pulverized coal (PC) plants. This report presents details of the performance and cost models developed for an amine-based CO{sub 2} capture system, representing the baseline of current commercial technology. The key uncertainties and variability in process design, performance and cost parameters which influence the overall cost of carbon mitigation also are characterized. The new performance and cost models for CO{sub 2} capture systems have been integrated into the IECM-cs, along with models to estimate CO{sub 2} transport and storage costs. The CO{sub 2} control system also interacts with other emission control technologies such as flue gas desulfurization (FGD) systems for SO{sub 2} control. The integrated model is applied to

  5. Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework

    ERIC Educational Resources Information Center

    Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A.

    2012-01-01

    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…

  6. Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework

    ERIC Educational Resources Information Center

    Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A.

    2012-01-01

    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…

  7. Model-Based Reasoning in the Physics Laboratory: Framework and Initial Results

    ERIC Educational Resources Information Center

    Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

    2015-01-01

    We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable…

  8. Retrofitting Non-Cognitive-Diagnostic Reading Assessment under the Generalized DINA Model Framework

    ERIC Educational Resources Information Center

    Chen, Huilin; Chen, Jinsong

    2016-01-01

    Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a…

  9. Model-Based Reasoning in the Physics Laboratory: Framework and Initial Results

    ERIC Educational Resources Information Center

    Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

    2015-01-01

    We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable…

  10. Retrofitting Non-Cognitive-Diagnostic Reading Assessment under the Generalized DINA Model Framework

    ERIC Educational Resources Information Center

    Chen, Huilin; Chen, Jinsong

    2016-01-01

    Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a…

  11. Evaluation of Model Coupling Frameworks for Use by the Community Surface Dynamics Modeling System (CSDMS)

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.; Syvitski, J. P.

    2007-12-01

    The Community Surface Dynamics Modeling System (CSDMS) is a recently NSF-funded project that represents an effort to bring together a diverse community of surface dynamics modelers and model users. Key goals of the CSDMS project are to (1) promote open-source code sharing and re-use, (2) to develop a review process for code contributions, (3) promote recognition of contributors, (4) develop a "library" of low-level software tools and higher-level models that can be linked as easily as possible into new applications and (5) provide resources to simplify the efforts of surface dynamics modelers. The architectural framework of CSDMS is being designed to allow code contributions to be in any of several different programming languages (language independence), to support a migration towards parallel computation and to support multiple operating systems (platform independence). In addition, the architecture should permit structured, unstructured and adaptive grids. A variety of different "coupling frameworks" are currently in use or under development in support of similar projects in other communities. One of these, ESMF (Earth System Modeling Framework), is primarily centered on Fortran90, structured grids and Unix-based platforms. ESMF has significant buy-in from the climate modeling community in the U.S.; a closely-related framework called OASIS4 has been adopted by many climate modelers in Europe. OpenMI has emerged from the hydrologic community in Europe and is likely to be adopted for the NSF-funded CUAHSI project. OpenMI is primarily centered on the Windows platform and a programming language called "C-sharp" and is not oriented toward parallel computing. A third, DOE-funded framework called CCA (Common Component Architecture) achieves language interoperability using a tool called Babel. It fully supports parallel computation and virtually any operating system. CCA has also been shown to be interoperable with ESMF and MCT (Model Coupling Toolkit) and would appear

  12. A Global Modeling Framework for Plasma Kinetics: Development and Applications

    NASA Astrophysics Data System (ADS)

    Parsey, Guy Morland

    The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization

  13. Smart licensing and environmental flows: Modeling framework and sensitivity testing

    NASA Astrophysics Data System (ADS)

    Wilby, R. L.; Fenn, C. R.; Wood, P. J.; Timlett, R.; Lequesne, T.

    2011-12-01

    Adapting to climate change is just one among many challenges facing river managers. The response will involve balancing the long-term water demands of society with the changing needs of the environment in sustainable and cost effective ways. This paper describes a modeling framework for evaluating the sensitivity of low river flows to different configurations of abstraction licensing under both historical climate variability and expected climate change. A rainfall-runoff model is used to quantify trade-offs among environmental flow (e-flow) requirements, potential surface and groundwater abstraction volumes, and the frequency of harmful low-flow conditions. Using the River Itchen in southern England as a case study it is shown that the abstraction volume is more sensitive to uncertainty in the regional climate change projection than to the e-flow target. It is also found that "smarter" licensing arrangements (involving a mix of hands off flows and "rising block" abstraction rules) could achieve e-flow targets more frequently than conventional seasonal abstraction limits, with only modest reductions in average annual yield, even under a hotter, drier climate change scenario.

  14. A modeling framework for potential induced degradation in PV modules

    NASA Astrophysics Data System (ADS)

    Bermel, Peter; Asadpour, Reza; Zhou, Chao; Alam, Muhammad A.

    2015-09-01

    Major sources of performance degradation and failure in glass-encapsulated PV modules include moisture-induced gridline corrosion, potential-induced degradation (PID) of the cell, and stress-induced busbar delamination. Recent studies have shown that PV modules operating in damp heat at -600 V are vulnerable to large amounts of degradation, potentially up to 90% of the original power output within 200 hours. To improve module reliability and restore power production in the presence of PID and other failure mechanisms, a fundamental rethinking of accelerated testing is needed. This in turn will require an improved understanding of technology choices made early in development that impact failures later. In this work, we present an integrated approach of modeling, characterization, and validation to address these problems. A hierarchical modeling framework will allows us to clarify the mechanisms of corrosion, PID, and delamination. We will employ a physics-based compact model of the cell, topology of the electrode interconnection, geometry of the packaging stack, and environmental operating conditions to predict the current, voltage, temperature, and stress distributions in PV modules correlated with the acceleration of specific degradation modes. A self-consistent solution will capture the essential complexity of the technology-specific acceleration of PID and other degradation mechanisms as a function of illumination, ambient temperature, and relative humidity. Initial results from our model include specific lifetime predictions suitable for direct comparison with indoor and outdoor experiments, which are qualitatively validated by prior work. This approach could play a significant role in developing novel accelerated lifetime tests.

  15. A modeling and simulation framework for electrokinetic nanoparticle treatment

    NASA Astrophysics Data System (ADS)

    Phillips, James

    2011-12-01

    The focus of this research is to model and provide a simulation framework for the packing of differently sized spheres within a hard boundary. The novel contributions of this dissertation are the cylinders of influence (COI) method and sectoring method implementations. The impetus for this research stems from modeling electrokinetic nanoparticle (EN) treatment, which packs concrete pores with differently sized nanoparticles. We show an improved speed of the simulation compared to previously published results of EN treatment simulation while obtaining similar porosity reduction results. We mainly focused on readily, commercially available particle sizes of 2 nm and 20 nm particles, but have the capability to model other sizes. Our simulation has graphical capabilities and can provide additional data unobtainable from physical experimentation. The data collected has a median of 0.5750 and a mean of 0.5504. The standard error is 0.0054 at alpha = 0.05 for a 95% confidence interval of 0.5504 +/- 0.0054. The simulation has produced maximum packing densities of 65% and minimum packing densities of 34%. Simulation data are analyzed using linear regression via the R statistical language to obtain two equations: one that describes porosity reduction based on all cylinder and particle characteristics, and another that focuses on describing porosity reduction based on cylinder diameter for 2 and 20 nm particles into pores of 100 nm height. Simulation results are similar to most physical results obtained from MIP and WLR. Some MIP results do not fall within the simulation limits; however, this is expected as MIP has been documented to be an inaccurate measure of pore distribution and porosity of concrete. Despite the disagreement between WLR and MIP, there is a trend that porosity reduction is higher two inches from the rebar as compared to the rebar-concrete interface. The simulation also detects a higher porosity reduction further from the rebar. This may be due to particles

  16. Digital Moon: A three-dimensional framework for lunar modeling

    NASA Astrophysics Data System (ADS)

    Paige, D. A.; Elphic, R. C.; Foote, E. J.; Meeker, S. R.; Siegler, M. A.; Vasavada, A. R.

    2009-12-01

    The Moon has a complex three-dimensional shape with significant large-scale and small-scale topographic relief. The Moon’s topography largely controls the distribution of incident solar radiation, as well as the scattered solar and infrared radiation fields. Topography also affects the Moon’s interaction with the space environment, its magnetic field, and the propagation of seismic waves. As more extensive and detailed lunar datasets become available, there is an increasing need to interpret and compare them with the results of physical models in a fully three-dimensional context. We have developed a three-dimensional framework for lunar modeling we call the Digital Moon. The goal of this work is to enable high fidelity physical modeling and visualization of the Moon in a parallel computing environment. The surface of the Moon is described by a continuous triangular mesh of arbitrary shape and spatial scale. For regions of limited geographic extent, it is convenient to employ meshes on a rectilinear grid. However for global-scale modeling, we employ a continuous geodesic gridding scheme (Teanby, 2008). Each element in the mesh surface is allowed to have a unique set of physical properties. Photon and particle interactions between mesh elements are modeled using efficient ray tracing algorithms. Heat, mass, photon and particle transfer within each mesh element are modeled in one dimension. Each compute node is assigned a portion of the mesh and collective interactions between elements are handled through network interfaces. We have used the model to calculate lunar surface and subsurface temperatures that can be compared directly with radiometric temperatures measured by the Diviner Lunar Radiometer Experiment on the Lunar Reconnaissance Orbiter. The model includes realistic surface photometric functions based on goniometric measurements of lunar soil samples (Foote and Paige, 2009), and one-dimensional thermal models based on lunar remote sensing and Apollo

  17. Design of a framework for modeling, integration and simulation of physiological models.

    PubMed

    Erson, E Zeynep; Cavuşoğlu, M Cenk

    2012-09-01

    Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  18. Adaptive invasive species distribution models: A framework for modeling incipient invasions

    USGS Publications Warehouse

    Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

    2015-01-01

    The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

  19. The BlueSky Smoke Modeling Framework: Recent Developments

    NASA Astrophysics Data System (ADS)

    Sullivan, D. C.; Larkin, N.; Raffuse, S. M.; Strand, T.; ONeill, S. M.; Leung, F. T.; Qu, J. J.; Hao, X.

    2012-12-01

    (TRMM) Multi-satellite Precipitation Analysis Real-Time (TMPA-RT) data set is being used to improve dead fuel moisture estimates. - EastFire live fuel moisture estimates, which are derived from NASA's MODIS direct broadcast, are being used to improve live fuel moisture estimates. - NASA's Multi-angle Imaging Spectroradiometer (MISR) stereo heights are being used to improve estimates of plume injection heights. Further, the Fire Location and Modeling of Burning Emissions (FLAMBÉ) model was incorporated into the BlueSky Framework as an alternative means of calculating fire emissions. FLAMBÉ directly estimates emissions on the basis of fire detections and radiance measures from NASA's MODIS and NOAA's GOES satellites. (The authors gratefully acknowledge NASA's Applied Sciences Program [Grant Nos. NN506AB52A and NNX09AV76G)], the USDA Forest Service, and the Joint Fire Science Program for their support.)

  20. Design of a framework for modeling, integration and simulation of physiological models.

    PubMed

    Erson, E; Cavusoglu, M

    2010-01-01

    Modeling and simulation of physiological processes deal with the challenges of multiscale models in which coupling is very high within and among scales. Information technology approaches together with related analytical and computational tools will help to deal with these challenges. Physiological Model Simulation, Integration and Modeling Framework, Phy-SIM, provides the modeling environment which will help to cultivate various approaches to deal with the inherent problem of multiscale modeling of physiological systems. In this paper, we present the modular design of Phy-SIM. The proposed layered design of Phy-SIM, separates structure from function in physiological processes advocating modular thinking in developing and integrating physiological models. Moreover, the ontology based architecture will improve the modeling process by the mechanisms to attach anatomical and physiological ontological information to the models. The ultimate aim of the proposed approaches is to enhance the physiological model development and integration processes by providing the tools and mechanisms in Phy-SIM.

  1. XML-based 3D model visualization and simulation framework for dynamic models

    NASA Astrophysics Data System (ADS)

    Kim, Taewoo; Fishwick, Paul A.

    2002-07-01

    Relatively recent advances in computer technology enable us to create three-dimensional (3D) dynamic models and simulate them within a 3D web environment. The use of such models is especially valuable when teaching simulation, and the concepts behind dynamic models, since the models are made more accessible to the students. Students tend to enjoy a construction process in which they are able to employ their own cultural and aesthetic forms. The challenge is to create a language that allows for a grammar for modeling, while simultaneously permitting arbitrary presentation styles. For further flexibility, we need an effective way to represent and simulate dynamic models that can be shared by modelers over the Internet. We present an Extensible Markup Language (XML)-based framework that will guide a modeler in creating personalized 3D models, visualizing its dynamic behaviors, and simulating the created models. A model author will use XML files to represent geometries and topology of a dynamic model. Model Fusion Engine, written in Extensible Stylesheet Language Transformation (XSLT), expedites the modeling process by automating the creation of dynamic models with the user-defined XML files. Modelers can also link simulation programs with a created model to analyze the characteristics of the model. The advantages of this system lie in the education of modeling and simulating dynamic models, and in the exploitation of visualizing the dynamic model behaviors.

  2. D Geological Framework Models as a Teaching Aid for Geoscience

    NASA Astrophysics Data System (ADS)

    Kessler, H.; Ward, E.; Geological ModelsTeaching Project Team

    2010-12-01

    3D geological models have great potential as a resource for universities when teaching foundation geological concepts as it allows the student to visualise and interrogate UK geology. They are especially useful when dealing with the conversion of 2D field, map and GIS outputs into three dimensional geological units, which is a common problem for all students of geology. Today’s earth science students use a variety of skills and processes during their learning experience including the application of schema’s, spatial thinking, image construction, detecting patterns, memorising figures, mental manipulation and interpretation, making predictions and deducing the orientation of themselves and the rocks. 3D geological models can reinforce spatial thinking strategies and encourage students to think about processes and properties, in turn helping the student to recognise pre-learnt geological principles in the field and to convert what they see at the surface into a picture of what is going on at depth. Learning issues faced by students may also be encountered by experts, policy managers, and stakeholders when dealing with environmental problems. Therefore educational research of student learning in earth science may also improve environmental decision making. 3D geological framework models enhance the learning of Geosciences because they: ● enable a student to observe, manipulate and interpret geology; in particular the models instantly convert two-dimensional geology (maps, boreholes and cross-sections) into three dimensions which is a notoriously difficult geospatial skill to acquire. ● can be orientated to whatever the user finds comfortable and most aids recognition and interpretation. ● can be used either to teach geosciences to complete beginners or add to experienced students body of knowledge (whatever point that may be at). Models could therefore be packaged as a complete educational journey or students and tutor can select certain areas of the model

  3. Test designs and modeling under the general nominal diagnosis model framework.

    PubMed

    Chen, Jinsong; Zhou, Hui

    2017-01-01

    Most psychological questionnaires face issues of response bias in respondent-reported scales, inadequacy for criterion-reference testing, or difficulty in estimating a large number of latent traits. Situational tests together with the general nominal diagnosis model framework provide a viable alternative to alleviate these concerns. Under this framework, there are different ways to design situationally nominal items, which can offer more flexibility for test development. Any response bias remaining with respondent-reported questionnaires may be addressed with appropriate test designs. The saturated model subsumes different reduced forms that can help inform whether the test is designed as expected. Two simulation studies are presented to demonstrate the effectiveness of the models and designs.

  4. Subsurface and Surface Characterization using an Information Framework Model

    NASA Astrophysics Data System (ADS)

    Samuel-Ojo, Olusola

    Groundwater plays a critical dual role as a reservoir of fresh water for human consumption and as a cause of the most severe problems when dealing with construction works below the water table. This is why it is critical to monitor groundwater recharge, distribution, and discharge on a continuous basis. The conventional method of monitoring groundwater employs a network of sparsely distributed monitoring wells and it is laborious, expensive, and intrusive. The problem of sparse data and undersampling reduces the accuracy of sampled survey data giving rise to poor interpretation. This dissertation addresses this problem by investigating groundwater-deformation response in order to augment the conventional method. A blend of three research methods was employed, namely design science research, geological methods, and geophysical methods, to examine whether persistent scatterer interferometry, a remote sensing technique, might augment conventional groundwater monitoring. Observation data (including phase information for displacement deformation from permanent scatterer interferometric synthetic aperture radar and depth to groundwater data) was obtained from the Water District, Santa Clara Valley, California. An information framework model was built and applied, and then evaluated. Data was preprocessed and decomposed into five components or parts: trend, seasonality, low frequency, high frequency and octave bandwidth. Digital elevation models of observed and predicted hydraulic head were produced, illustrating the piezometric or potentiometric surface. The potentiometric surface characterizes the regional aquifer of the valley showing areal variation of rate of percolation, velocity and permeability, and completely defines flow direction, advising characteristics and design levels. The findings show a geologic forcing phenomenon which explains in part the long-term deformation behavior of the valley, characterized by poroelastic, viscoelastic, elastoplastic and

  5. A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization.

    PubMed

    Spicknall, Ian H; Foxman, Betsy; Marrs, Carl F; Eisenberg, Joseph N S

    2013-08-15

    Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To examine the implications of this, we first reviewed the literature on antibiotic-resistance modeling published between 1993 and 2011. We then classified each article's model structure into one or more of 6 categories based on the assumptions made in those articles regarding within-host and population-level competition between antibiotic-sensitive and antibiotic-resistant strains. Each model category has different dynamic implications with respect to how antibiotic use affects resistance prevalence, and therefore each may produce different conclusions about optimal treatment protocols that minimize resistance. Thus, even if all parameter values are correctly estimated, inferences may be incorrect because of the incorrect selection of model structure. Our framework provides insight into model selection.

  6. Modeling sports highlights using a time-series clustering framework and model interpretation

    NASA Astrophysics Data System (ADS)

    Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

    2005-01-01

    In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.

  7. Modeling sports highlights using a time-series clustering framework and model interpretation

    NASA Astrophysics Data System (ADS)

    Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

    2004-12-01

    In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.

  8. Linking Tectonics and Surface Processes through SNAC-CHILD Coupling: Preliminary Results Towards Interoperable Modeling Frameworks

    NASA Astrophysics Data System (ADS)

    Choi, E.; Kelbert, A.; Peckham, S. D.

    2014-12-01

    We demonstrate that code coupling can be an efficient and flexible method for modeling complicated two-way interactions between tectonic and surface processes with SNAC-CHILD coupling as an example. SNAC is a deep earth process model (a geodynamic/tectonics model), built upon a scientific software framework called StGermain and also compatible with a model coupling framework called Pyre. CHILD is a popular surface process model (a landscape evolution model), interfaced to the CSDMS (Community Surface Dynamics Modeling System) modeling framework. We first present proof-of-concept but non-trivial results from a simplistic coupling scheme. We then report progress towards augmenting SNAC with a Basic Model Interface (BMI), a framework-agnostic standard interface developed by CSDMS that uses the CSDMS Standard Names as controlled vocabulary for model communication across domains. Newly interfaced to BMI, SNAC will be easily coupled with CHILD as well as other BMI-compatible models. In broader context, this work will test BMI as a general and easy-to-implement mechanism for sharing models between modeling frameworks and is a part of the NSF-funded EarthCube Building Blocks project, "Earth System Bridge: Spanning Scientific Communities with Interoperable Modeling Frameworks."

  9. A Framework for Developing the Structure of Public Health Economic Models.

    PubMed

    Squires, Hazel; Chilcott, James; Akehurst, Ronald; Burr, Jennifer; Kelly, Michael P

    2016-01-01

    A conceptual modeling framework is a methodology that assists modelers through the process of developing a model structure. Public health interventions tend to operate in dynamically complex systems. Modeling public health interventions requires broader considerations than clinical ones. Inappropriately simple models may lead to poor validity and credibility, resulting in suboptimal allocation of resources. This article presents the first conceptual modeling framework for public health economic evaluation. The framework presented here was informed by literature reviews of the key challenges in public health economic modeling and existing conceptual modeling frameworks; qualitative research to understand the experiences of modelers when developing public health economic models; and piloting a draft version of the framework. The conceptual modeling framework comprises four key principles of good practice and a proposed methodology. The key principles are that 1) a systems approach to modeling should be taken; 2) a documented understanding of the problem is imperative before and alongside developing and justifying the model structure; 3) strong communication with stakeholders and members of the team throughout model development is essential; and 4) a systematic consideration of the determinants of health is central to identifying the key impacts of public health interventions. The methodology consists of four phases: phase A, aligning the framework with the decision-making process; phase B, identifying relevant stakeholders; phase C, understanding the problem; and phase D, developing and justifying the model structure. Key areas for further research involve evaluation of the framework in diverse case studies and the development of methods for modeling individual and social behavior. This approach could improve the quality of Public Health economic models, supporting efficient allocation of scarce resources. Copyright © 2016 International Society for Pharmacoeconomics

  10. Evolution of 3-D geologic framework modeling and its application to groundwater flow studies

    USGS Publications Warehouse

    Blome, Charles D.; Smith, David V.

    2012-01-01

    In this Fact Sheet, the authors discuss the evolution of project 3-D subsurface framework modeling, research in hydrostratigraphy and airborne geophysics, and methodologies used to link geologic and groundwater flow models.

  11. Holland's RIASEC Model as an Integrative Framework for Individual Differences

    ERIC Educational Resources Information Center

    Armstrong, Patrick Ian; Day, Susan X.; McVay, Jason P.; Rounds, James

    2008-01-01

    Using data from published sources, the authors investigated J. L. Holland's (1959, 1997) theory of interest types as an integrative framework for organizing individual differences variables that are used in counseling psychology. Holland's interest types were used to specify 2- and 3-dimensional interest structures. In Study 1, measures of…

  12. A unified framework for modeling landscape evolution by discrete flows

    NASA Astrophysics Data System (ADS)

    Shelef, Eitan; Hilley, George E.

    2016-05-01

    Topographic features such as branched valley networks and undissected convex-up hillslopes are observed in disparate physical environments. In some cases, these features are formed by sediment transport processes that occur discretely in space and time, while in others, by transport processes that are uniformly distributed across the landscape. This paper presents an analytical framework that reconciles the basic attributes of such sediment transport processes with the topographic features that they form and casts those in terms that are likely common to different physical environments. In this framework, temporal changes in surface elevation reflect the frequency with which the landscape is traversed by geophysical flows generated discretely in time and space. This frequency depends on the distance to which flows travel downslope, which depends on the dynamics of individual flows, the lithologic and topographic properties of the underlying substrate, and the coevolution of topography, erosion, and the routing of flows over the topographic surface. To explore this framework, we postulate simple formulations for sediment transport and flow runout distance and demonstrate that the conditions for hillslope and channel network formation can be cast in terms of fundamental parameters such as distance from drainage divide and a friction-like coefficient that describes a flow's resistance to motion. The framework we propose is intentionally general, but the postulated formulas can be substituted with those that aim to describe a specific process and to capture variations in the size distribution of such flow events.

  13. Holland's RIASEC Model as an Integrative Framework for Individual Differences

    ERIC Educational Resources Information Center

    Armstrong, Patrick Ian; Day, Susan X.; McVay, Jason P.; Rounds, James

    2008-01-01

    Using data from published sources, the authors investigated J. L. Holland's (1959, 1997) theory of interest types as an integrative framework for organizing individual differences variables that are used in counseling psychology. Holland's interest types were used to specify 2- and 3-dimensional interest structures. In Study 1, measures of…

  14. A conceptual modeling framework for discrete event simulation using hierarchical control structures.

    PubMed

    Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

    2015-08-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

  15. A framework for modeling the cathode fall illustrated with a single beam model

    NASA Astrophysics Data System (ADS)

    Sommerer, T. J.; Lawler, J. E.; Hitchon, W. N. G.

    1988-08-01

    A framework for a model of the cathode fall region of a dc glow discharge is presented, and a simple model is solved as an illustration. An extremum condition independent of the model is placed on the electric field behavior to produce a unique solution that agrees with experiment. The zeroth and second moments of the Boltzmann equation are solved for the electrons with a self-consistent electric field. A single-beam model with only two parameters (number density and beam velocity) is assumed for the electron distribution function. Ion motion is modeled with a parametric fit to known ion mobilities. The model is solved for conditions corresponding to the experimental results and to Monte Carlo simulations of Doughty, Den Hartog, and Lawler [Phys. Rev. Lett. 58, 2668 (1987)]. The results are in good qualitative and ``factor-of-two'' quantitative agreement with the published results.

  16. Experimental development based on mapping rule between requirements analysis model and web framework specific design model.

    PubMed

    Okuda, Hirotaka; Ogata, Shinpei; Matsuura, Saeko

    2013-12-01

    Model Driven Development is a promising approach to develop high quality software systems. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface prototype from UML requirements analysis model so that we can confirm validity of input/output data for each page and page transition on the system by directly operating the prototype. We proposes a mapping rule in which design information independent of each web application framework implementation is defined based on the requirements analysis model, so as to improve the traceability to the final product from the valid requirements analysis model. This paper discusses the result of applying our method to the development of a Group Work Support System that is currently running in our department.

  17. Parameter estimation and model comparison for stochastic epidemiological processes in a Bayesian framework

    NASA Astrophysics Data System (ADS)

    Mateus, Luis; Stollenwerk, Nico; Zambrini, Jean Claude

    2012-09-01

    We compare two stochastic epidemiological models in a Bayesian framework, both models performing on the same simulated data set. In some cases of data obtained under one model with specific parameter values the model comparison favours the model not underlying the simulated data.

  18. A conceptual modeling framework for discrete event simulation using hierarchical control structures

    PubMed Central

    Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

    2015-01-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940

  19. Advances in Geoscience Modeling: Smart Modeling Frameworks, Self-Describing Models and the Role of Standardized Metadata

    NASA Astrophysics Data System (ADS)

    Peckham, Scott

    2016-04-01

    Over the last decade, model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that make it much easier for modelers to connect heterogeneous sets of process models in a plug-and-play manner to create composite "system models". These mechanisms greatly simplify code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing with standardized metadata. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can use the self description functions to learn about each process model in a collection to be coupled and then automatically call framework service components (e.g. regridders

  20. Collaborative Project. A Flexible Atmospheric Modeling Framework for the Community Earth System Model (CESM)

    SciTech Connect

    Gettelman, Andrew

    2015-10-01

    In this project we have been upgrading the Multiscale Modeling Framework (MMF) in the Community Atmosphere Model (CAM), also known as Super-Parameterized CAM (SP-CAM). This has included a major effort to update the coding standards and interface with CAM so that it can be placed on the main development trunk. It has also included development of a new software structure for CAM to be able to handle sub-grid column information. These efforts have formed the major thrust of the work.

  1. Assessing Students' Understandings of Biological Models and Their Use in Science to Evaluate a Theoretical Framework

    ERIC Educational Resources Information Center

    Grünkorn, Juliane; Upmeier zu Belzen, Annette; Krüger, Dirk

    2014-01-01

    Research in the field of students' understandings of models and their use in science describes different frameworks concerning these understandings. Currently, there is no conjoint framework that combines these structures and so far, no investigation has focused on whether it reflects students' understandings sufficiently (empirical evaluation).…

  2. Applying the Nominal Response Model within a Longitudinal Framework to Construct the Positive Family Relationships Scale

    ERIC Educational Resources Information Center

    Preston, Kathleen Suzanne Johnson; Parral, Skye N.; Gottfried, Allen W.; Oliver, Pamella H.; Gottfried, Adele Eskeles; Ibrahim, Sirena M.; Delany, Danielle

    2015-01-01

    A psychometric analysis was conducted using the nominal response model under the item response theory framework to construct the Positive Family Relationships scale. Using data from the Fullerton Longitudinal Study, this scale was constructed within a long-term longitudinal framework spanning middle childhood through adolescence. Items tapping…

  3. Assessing Students' Understandings of Biological Models and Their Use in Science to Evaluate a Theoretical Framework

    ERIC Educational Resources Information Center

    Grünkorn, Juliane; Upmeier zu Belzen, Annette; Krüger, Dirk

    2014-01-01

    Research in the field of students' understandings of models and their use in science describes different frameworks concerning these understandings. Currently, there is no conjoint framework that combines these structures and so far, no investigation has focused on whether it reflects students' understandings sufficiently (empirical evaluation).…

  4. Applying the Nominal Response Model within a Longitudinal Framework to Construct the Positive Family Relationships Scale

    ERIC Educational Resources Information Center

    Preston, Kathleen Suzanne Johnson; Parral, Skye N.; Gottfried, Allen W.; Oliver, Pamella H.; Gottfried, Adele Eskeles; Ibrahim, Sirena M.; Delany, Danielle

    2015-01-01

    A psychometric analysis was conducted using the nominal response model under the item response theory framework to construct the Positive Family Relationships scale. Using data from the Fullerton Longitudinal Study, this scale was constructed within a long-term longitudinal framework spanning middle childhood through adolescence. Items tapping…

  5. Spatially distributed modelling of pesticide leaching at European scale with the PyCatch modelling framework

    NASA Astrophysics Data System (ADS)

    Schmitz, Oliver; van der Perk, Marcel; Karssenberg, Derek; Häring, Tim; Jene, Bernhard

    2017-04-01

    The modelling of pesticide transport through the soil and estimating its leaching to groundwater is essential for an appropriate environmental risk assessment. Pesticide leaching models commonly used in regulatory processes often lack the capability of providing a comprehensive spatial view, as they are implemented as non-spatial point models or only use a few combinations of representative soils to simulate specific plots. Furthermore, their handling of spatial input and output data and interaction with available Geographical Information Systems tools is limited. Therefore, executing several scenarios simulating and assessing the potential leaching on national or continental scale at high resolution is rather inefficient and prohibits the straightforward identification of areas prone to leaching. We present a new pesticide leaching model component of the PyCatch framework developed in PCRaster Python, an environmental modelling framework tailored to the development of spatio-temporal models (http://www.pcraster.eu). To ensure a feasible computational runtime of large scale models, we implemented an elementary field capacity approach to model soil water. Currently implemented processes are evapotranspiration, advection, dispersion, sorption, degradation and metabolite transformation. Not yet implemented relevant additional processes such as surface runoff, snowmelt, erosion or other lateral flows can be integrated with components already implemented in PyCatch. A preliminary version of the model executes a 20-year simulation of soil water processes for Germany (20 soil layers, 1 km2 spatial resolution, and daily timestep) within half a day using a single CPU. A comparison of the soil moisture and outflow obtained from the PCRaster implementation and PELMO, a commonly used pesticide leaching model, resulted in an R2 of 0.98 for the FOCUS Hamburg scenario. We will further discuss the validation of the pesticide transport processes and show case studies applied to

  6. Integration of the DAYCENT Biogeochemical Model within a Multi-Model Framework

    SciTech Connect

    David Muth

    2012-07-01

    Agricultural residues are the largest near term source of cellulosic 13 biomass for bioenergy production, but removing agricultural residues sustainably 14 requires considering the critical roles that residues play in the agronomic system. 15 Determining sustainable removal rates for agricultural residues has received 16 significant attention and integrated modeling strategies have been built to evaluate 17 sustainable removal rates considering soil erosion and organic matter constraints. 18 However the current integrated model does not quantitatively assess soil carbon 19 and long term crop yields impacts of residue removal. Furthermore the current 20 integrated model does not evaluate the greenhouse gas impacts of residue 21 removal, specifically N2O and CO2 gas fluxes from the soil surface. The DAYCENT 22 model simulates several important processes for determining agroecosystem 23 performance. These processes include daily Nitrogen-gas flux, daily carbon dioxide 24 flux from soil respiration, soil organic carbon and nitrogen, net primary productivity, 25 and daily water and nitrate leaching. Each of these processes is an indicator of 26 sustainability when evaluating emerging cellulosic biomass production systems for 27 bioenergy. A potentially vulnerable cellulosic biomass resource is agricultural 28 residues. This paper presents the integration of the DAYCENT model with the 29 existing integration framework modeling tool to investigate additional environment 30 impacts of agricultural residue removal. The integrated model is extended to 31 facilitate two-way coupling between DAYCENT and the existing framework. The 32 extended integrated model is applied to investigate additional environmental 33 impacts from a recent sustainable agricultural residue removal dataset. The 34 integrated model with DAYCENT finds some differences in sustainable removal 35 rates compared to previous results for a case study county in Iowa. The extended 36 integrated model with

  7. Assessing Students' Understandings of Biological Models and their Use in Science to Evaluate a Theoretical Framework

    NASA Astrophysics Data System (ADS)

    Grünkorn, Juliane; Belzen, Annette Upmeier zu; Krüger, Dirk

    2014-07-01

    Research in the field of students' understandings of models and their use in science describes different frameworks concerning these understandings. Currently, there is no conjoint framework that combines these structures and so far, no investigation has focused on whether it reflects students' understandings sufficiently (empirical evaluation). Therefore, the purpose of this article is to present the results of an empirical evaluation of a conjoint theoretical framework. The theoretical framework integrates relevant research findings and comprises five aspects which are subdivided into three levels each: nature of models, multiple models, purpose of models, testing, and changing models. The study was conducted with a sample of 1,177 seventh to tenth graders (aged 11-19 years) using open-ended items. The data were analysed by identifying students' understandings of models (nature of models and multiple models) and their use in science (purpose of models, testing, and changing models), and comparing as well as assigning them to the content of the theoretical framework. A comprehensive category system of students' understandings was thus developed. Regarding the empirical evaluation, the students' understandings of the nature and the purpose of models were sufficiently described by the theoretical framework. Concerning the understandings of multiple, testing, and changing models, additional initial understandings (only one model possible, no testing of models, and no change of models) need to be considered. This conjoint and now empirically tested framework for students' understandings can provide a common basis for future science education research. Furthermore, evidence-based indications can be provided for teachers and their instructional practice.

  8. EarthCube - Earth System Bridge: Spanning Scientific Communities with Interoperable Modeling Frameworks

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.; DeLuca, C.; Gochis, D. J.; Arrigo, J.; Kelbert, A.; Choi, E.; Dunlap, R.

    2014-12-01

    In order to better understand and predict environmental hazards of weather/climate, ecology and deep earth processes, geoscientists develop and use physics-based computational models. These models are used widely both in academic and federal communities. Because of the large effort required to develop and test models, there is widespread interest in component-based modeling, which promotes model reuse and simplified coupling to tackle problems that often cross discipline boundaries. In component-based modeling, the goal is to make relatively small changes to models that make it easy to reuse them as "plug-and-play" components. Sophisticated modeling frameworks exist to rapidly couple these components to create new composite models. They allow component models to exchange variables while accommodating different programming languages, computational grids, time-stepping schemes, variable names and units. Modeling frameworks have arisen in many modeling communities. CSDMS (Community Surface Dynamics Modeling System) serves the academic earth surface process dynamics community, while ESMF (Earth System Modeling Framework) serves many federal Earth system modeling projects. Others exist in both the academic and federal domains and each satisfies design criteria that are determined by the community they serve. While they may use different interface standards or semantic mediation strategies, they share fundamental similarities. The purpose of the Earth System Bridge project is to develop mechanisms for interoperability between modeling frameworks, such as the ability to share a model or service component. This project has three main goals: (1) Develop a Framework Description Language (ES-FDL) that allows modeling frameworks to be described in a standard way so that their differences and similarities can be assessed. (2) Demonstrate that if a model is augmented with a framework-agnostic Basic Model Interface (BMI), then simple, universal adapters can go from BMI to a

  9. Using a scalable modeling and simulation framework to evaluate the benefits of intelligent transportation systems.

    SciTech Connect

    Ewing, T.; Tentner, A.

    2000-03-21

    A scalable, distributed modeling and simulation framework has been developed at Argonne National Laboratory to study Intelligent Transportation Systems. The framework can run on a single-processor workstation, or run distributed on a multiprocessor computer or network of workstations. The framework is modular and supports plug-in models, hardware, and live data sources. The initial set of models currently includes road network and traffic flow, probe and smart vehicles, traffic management centers, communications between vehicles and centers, in-vehicle navigation systems, roadway traffic advisories. The modeling and simulation capability has been used to examine proposed ITS concepts. Results are presented from modeling scenarios from the Advanced Driver and Vehicle Advisory Navigation Concept (ADVANCE) experimental program to demonstrate how the framework can be used to evaluate the benefits of ITS and to plan future ITS operational tests and deployment initiatives.

  10. Temporo-spatial model construction using the MML and software framework.

    PubMed

    Chang, David C; Dokos, Socrates; Lovell, Nigel H

    2011-12-01

    Development of complex temporo-spatial biological computational models can be a time consuming and arduous task. These models may contain hundreds of differential equations as well as realistic geometries that may require considerable investment in time to ensure that all model components are correctly implemented and error free. To tackle this problem, the Modeling Markup Languages (MML) and software framework is a modular XML/HDF5-based specification and toolkits that aims to simplify this process. The main goal of this framework is to encourage reusability, sharing and storage. To achieve this, the MML framework utilizes the CellML specification and repository, which comprises an extensive range of curated models available for use. The MML framework is an open-source project available at http://mml.gsbme.unsw.edu.au.

  11. Design of a component-based integrated environmental modeling framework

    EPA Science Inventory

    Integrated environmental modeling (IEM) includes interdependent science-based components (e.g., models, databases, viewers, assessment protocols) that comprise an appropriate software modeling system. The science-based components are responsible for consuming and producing inform...

  12. Design of a component-based integrated environmental modeling framework

    EPA Science Inventory

    Integrated environmental modeling (IEM) includes interdependent science-based components (e.g., models, databases, viewers, assessment protocols) that comprise an appropriate software modeling system. The science-based components are responsible for consuming and producing inform...

  13. Model-based reasoning in the physics laboratory: Framework and initial results

    NASA Astrophysics Data System (ADS)

    Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

    2015-12-01

    [This paper is part of the Focused Collection on Upper Division Physics Courses.] We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.

  14. A model independent S/W framework for search-based software testing.

    PubMed

    Oh, Jungsup; Baik, Jongmoon; Lim, Sung-Hwa

    2014-01-01

    In Model-Based Testing (MBT) area, Search-Based Software Testing (SBST) has been employed to generate test cases from the model of a system under test. However, many types of models have been used in MBT. If the type of a model has changed from one to another, all functions of a search technique must be reimplemented because the types of models are different even if the same search technique has been applied. It requires too much time and effort to implement the same algorithm over and over again. We propose a model-independent software framework for SBST, which can reduce redundant works. The framework provides a reusable common software platform to reduce time and effort. The software framework not only presents design patterns to find test cases for a target model but also reduces development time by using common functions provided in the framework. We show the effectiveness and efficiency of the proposed framework with two case studies. The framework improves the productivity by about 50% when changing the type of a model.

  15. Hydrogeologic Framework Model for the Saturated Zone Site Scale flow and Transport Model

    SciTech Connect

    T. Miller

    2004-11-15

    The purpose of this report is to document the 19-unit, hydrogeologic framework model (19-layer version, output of this report) (HFM-19) with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results in accordance with AP-SIII.10Q, Models. The HFM-19 is developed as a conceptual model of the geometric extent of the hydrogeologic units at Yucca Mountain and is intended specifically for use in the development of the ''Saturated Zone Site-Scale Flow Model'' (BSC 2004 [DIRS 170037]). Primary inputs to this model report include the GFM 3.1 (DTN: MO9901MWDGFM31.000 [DIRS 103769]), borehole lithologic logs, geologic maps, geologic cross sections, water level data, topographic information, and geophysical data as discussed in Section 4.1. Figure 1-1 shows the information flow among all of the saturated zone (SZ) reports and the relationship of this conceptual model in that flow. The HFM-19 is a three-dimensional (3-D) representation of the hydrogeologic units surrounding the location of the Yucca Mountain geologic repository for spent nuclear fuel and high-level radioactive waste. The HFM-19 represents the hydrogeologic setting for the Yucca Mountain area that covers about 1,350 km2 and includes a saturated thickness of about 2.75 km. The boundaries of the conceptual model were primarily chosen to be coincident with grid cells in the Death Valley regional groundwater flow model (DTN: GS960808312144.003 [DIRS 105121]) such that the base of the site-scale SZ flow model is consistent with the base of the regional model (2,750 meters below a smoothed version of the potentiometric surface), encompasses the exploratory boreholes, and provides a framework over the area of interest for groundwater flow and radionuclide transport modeling. In depth, the model domain extends from land surface to the base of the regional groundwater flow model (D'Agnese et al. 1997 [DIRS 100131], p 2). For the site-scale SZ flow model, the HFM

  16. An Integrated Modeling Framework Forecasting Ecosystem Services: Application to the Albemarle Pamlico Basins, NC and VA (USA)

    EPA Science Inventory

    We demonstrate an Integrated Modeling Framework that predicts the state of freshwater ecosystem services within the Albemarle-Pamlico Basins. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standa...

  17. An Integrated Modeling Framework Forcasting Ecosystem Services--Application to the Albemarle Pamlico Basins, NC and VA (USA) and Beyond

    EPA Science Inventory

    We demonstrate an Integrated Modeling Framework that predicts the state of freshwater ecosystem services within the Albemarle-Pamlico Basins. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standa...

  18. An Integrated Modeling Framework Forcasting Ecosystem Services--Application to the Albemarle Pamlico Basins, NC and VA (USA) and Beyond

    EPA Science Inventory

    We demonstrate an Integrated Modeling Framework that predicts the state of freshwater ecosystem services within the Albemarle-Pamlico Basins. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standa...

  19. An Integrated Modeling Framework Forecasting Ecosystem Services: Application to the Albemarle Pamlico Basins, NC and VA (USA)

    EPA Science Inventory

    We demonstrate an Integrated Modeling Framework that predicts the state of freshwater ecosystem services within the Albemarle-Pamlico Basins. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standa...

  20. A Complementary Modeling Framework to Quantify and Reduce Groundwater Flow Model Uncertainty

    NASA Astrophysics Data System (ADS)

    Valocchi, A. J.; Demissie, Y. K.

    2008-12-01

    Although modern inverse techniques are powerful tools for parameter estimation, results of calibrated groundwater models are nevertheless subject to uncertainty since it is not possible to account for all the natural subsurface complexity. We present a complementary modeling framework in which error-correcting data-driven models are used to handle the bias and uncertainties arising mainly from ignored or misrepresented processes in the physically-based groundwater model. We use MODFLOW as the groundwater flow model and PEST for automatic calibration. The uncertainty of the combined MODFLOW and data-driven models is quantified using First Order Second Moment (FOSM) and bootstrap methods. For both methods, we consider the propagation of uncertainty due to the estimation variance of both the MODFLOW and data-driven models parameters. However, since the data-driven model uses the estimated MODFLOW heads as an input, its predictive variance also incorporates the effect of input data uncertainty. The prediction uncertainties are presented as approximate 95 percent confidence and prediction intervals or quantiles of the underlying distribution of prediction errors. The methods are applied to a case study of transient groundwater flow in the Spokane Valley aquifer that has been previously addressed using a calibrated MODFLOW model. The results are compared with those of more common uncertainty estimation techniques, such as Generalized Likelihood Uncertainty Estimation (GLUE) and Bayesian Model Averaging (BMA). We compare the performance and efficiency of the methods, and discuss some of the challenges related to their practical application.

  1. Design of a Model Execution Framework: Repetitive Object-Oriented Simulation Environment (ROSE)

    NASA Technical Reports Server (NTRS)

    Gray, Justin S.; Briggs, Jeffery L.

    2008-01-01

    The ROSE framework was designed to facilitate complex system analyses. It completely divorces the model execution process from the model itself. By doing so ROSE frees the modeler to develop a library of standard modeling processes such as Design of Experiments, optimizers, parameter studies, and sensitivity studies which can then be applied to any of their available models. The ROSE framework accomplishes this by means of a well defined API and object structure. Both the API and object structure are presented here with enough detail to implement ROSE in any object-oriented language or modeling tool.

  2. A Framework for Multifaceted Evaluation of Student Models

    ERIC Educational Resources Information Center

    Huang, Yun; González-Brenes, José P.; Kumar, Rohit; Brusilovsky, Peter

    2015-01-01

    Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…

  3. eTOXlab, an open source modeling framework for implementing predictive models in production environments.

    PubMed

    Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

    2015-01-01

    Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by e

  4. Poly(ethylene glycol) (PEG) in a Polyethylene (PE) Framework: A Simple Model for Simulation Studies of a Soluble Polymer in an Open Framework.

    PubMed

    Xie, Liangxu; Chan, Kwong-Yu; Quirke, Nick

    2017-08-16

    Canonical molecular dynamics simulations are performed to investigate the behavior of single-chain and multiple-chain poly(ethylene glycol) (PEG) contained within a cubic framework spanned by polyethylene (PE) chains. This simple model is the first of its kind to study the chemical physics of polymer-threaded organic frameworks, which are materials with potential applications in catalysis and separation processes. For a single-chain 9-mer, 14-mer, and 18-mer in a small framework, the PEG will interact strongly with the framework and assume a more linear geometry chain with an increased radius of gyration Rg compared to that of a large framework. The interaction between PEG and the framework decreases with increasing mesh size in both vacuum and water. In the limit of a framework with an infinitely large cavity (infinitely long linkers), PEG behavior approaches simulation results without a framework. The solvation of PEG is simulated by adding explicit TIP3P water molecules to a 6-chain PEG 14-mer aggregate confined in a framework. The 14-mer chains are readily solvated and leach out of a large 2.6 nm mesh framework. There are fewer water-PEG interactions in a small 1.0 nm mesh framework, as indicated by a smaller number of hydrogen bonds. The PEG aggregate, however, still partially dissolves but is retained within the 1.0 nm framework. The preliminary results illustrate the effectiveness of the simple model in studying polymer-threaded framework materials and in optimizing polymer or framework parameters for high performance.

  5. ASSESSING POPULATION EXPOSURES TO MULTIPLE AIR POLLUTANTS USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

    EPA Science Inventory

    The Modeling Environment for Total Risks studies (MENTOR) system, combined with an extension of the SHEDS (Stochastic Human Exposure and Dose Simulation) methodology, provide a mechanistically consistent framework for conducting source-to-dose exposure assessments of multiple pol...

  6. ASSESSING POPULATION EXPOSURES TO MULTIPLE AIR POLLUTANTS USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

    EPA Science Inventory

    The Modeling Environment for Total Risks studies (MENTOR) system, combined with an extension of the SHEDS (Stochastic Human Exposure and Dose Simulation) methodology, provide a mechanistically consistent framework for conducting source-to-dose exposure assessments of multiple pol...

  7. Landscape - Soilscape Modelling: Proposed framework for a model comparison benchmarking exercise, who wants to join?

    NASA Astrophysics Data System (ADS)

    Schoorl, Jeroen M.; Jetten, Victor G.; Coulthard, Thomas J.; Hancock, Greg R.; Renschler, Chris S.; Irvine, Brian J.; Cerdan, Olivier; Kirkby, Mike J.; (A) Veldkamp, Tom

    2014-05-01

    Current landscape - soilscape modelling frameworks are developed under a wide range of spatial and temporal resolutions and extents, from the so called event-based models, soil erosion models to the landscape evolution models. In addition, these models are based on different assumptions, include variable and different processes descriptions and produce different outcomes. Consequently, the models often need specific input data and their development and calibration is best linked to a specific area and local conditions. Model validation is often limited and restricted to the shorter time scales and single events. A first workshop on catchment based modelling (6 event based models were challenged then) was organised in the late 90's and the results lead to some excellent discussions on predictive modelling, equifinality and a special issue in Catena. It is time for a similar exercise: new models have been made, older models have been updated, and judging from literature there is a lot more experience in calibration/validation and reflections on processes observed in the field and how these should be simulated. In addition there are new data sources, such as high resolution remote sensing (including DEMs), new pattern analysis, comparison techniques and continuous developments and results in dating sediment archives and erosion rates. The main goal of this renewed exercise will be to come up with a benchmarking methodology for comparing and judging model behaviour including the issues of upscaling and downscaling of results. Model comparison may lead to the development of new research questions and lead to a firmer understanding of different models performance under different circumstances.

  8. A Framework for Sharing and Integrating Remote Sensing and GIS Models Based on Web Service

    PubMed Central

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016

  9. A framework for sharing and integrating remote sensing and GIS models based on Web service.

    PubMed

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.

  10. A flexible and efficient multi-model framework in support of water management

    NASA Astrophysics Data System (ADS)

    Wolfs, Vincent; Tran Quoc, Quan; Willems, Patrick

    2016-05-01

    Flexible, fast and accurate water quantity models are essential tools in support of water management. Adjustable levels of model detail and the ability to handle varying spatial and temporal resolutions are requisite model characteristics to ensure that such models can be employed efficiently in various applications. This paper uses a newly developed flexible modelling framework that aims to generate such models. The framework incorporates several approaches to model catchment hydrology, rivers and floodplains, and the urban drainage system by lumping processes on different levels. To illustrate this framework, a case study of integrated hydrological-hydraulic modelling is elaborated for the Grote Nete catchment in Belgium. Three conceptual rainfall-runoff models (NAM, PDM and VHM) were implemented in a generalized model structure, allowing flexibility in the spatial resolution by means of an innovative disaggregation/aggregation procedure. They were linked to conceptual hydraulic models of the rivers in the catchment, which were developed by means of an advanced model structure identification and calibration procedure. The conceptual models manage to emulate the simulation results of a detailed full hydrodynamic model accurately. The models configured using the approaches of this framework are well-suited for many applications in water management due to their very short calculation time, interfacing possibilities and adjustable level of detail.

  11. An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

    PubMed

    Wu, Zujian; Pang, Wei; Coghill, George M

    Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

  12. A scalable delivery framework and a pricing model for streaming media with advertisements

    NASA Astrophysics Data System (ADS)

    Al-Hadrusi, Musab; Sarhan, Nabil J.

    2008-01-01

    This paper presents a delivery framework for streaming media with advertisements and an associated pricing model. The delivery model combines the benefits of periodic broadcasting and stream merging. The advertisements' revenues are used to subsidize the price of the media content. The pricing is determined based on the total ads' viewing time. Moreover, this paper presents an efficient ad allocation scheme and three modified scheduling policies that are well suited to the proposed delivery framework. Furthermore, we study the effectiveness of the delivery framework and various scheduling polices through extensive simulation in terms of numerous metrics, including customer defection probability, average number of ads viewed per client, price, arrival rate, profit, and revenue.

  13. BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

    PubMed

    Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

    2016-06-15

    Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

  14. BioASF: a framework for automatically generating executable pathway models specified in BioPAX

    PubMed Central

    Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K. Anton; Abeln, Sanne; Heringa, Jaap

    2016-01-01

    Motivation: Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. Results: To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. Availability and Implementation: The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF. Contact: j.heringa@vu.nl PMID:27307645

  15. A framework for regional modeling of past climates

    NASA Astrophysics Data System (ADS)

    Sloan, L. C.

    2006-09-01

    The methods of reconstructing ancient climate information from the rock record are summarized, and the climate forcing factors that have been active at global and regional scales through Earth history are reviewed. In this context, the challenges and approaches to modeling past climates by using a regional climate model are discussed. A significant challenge to such modeling efforts arises if the time period of interest occurred prior to the past ˜3 5 million years, at which point land sea distributions and topography markedly different from present must be specified at the spatial resolution required by regional climate models. Creating these boundary conditions requires a high degree of geologic knowledge, and also depends greatly upon the global climate model driving conditions. Despite this and other challenges, regional climate models represent an important and unique tool for paleoclimate investigations. Application of regional climate models to paleoclimate studies may provide another way to assess the overall performance of regional climate models.

  16. A general computational framework for modeling cellular structure and function.

    PubMed Central

    Schaff, J; Fink, C C; Slepchenko, B; Carson, J H; Loew, L M

    1997-01-01

    The "Virtual Cell" provides a general system for testing cell biological mechanisms and creates a framework for encapsulating the burgeoning knowledge base comprising the distribution and dynamics of intracellular biochemical processes. It approaches the problem by associating biochemical and electrophysiological data describing individual reactions with experimental microscopic image data describing their subcellular localizations. Individual processes are collected within a physical and computational infrastructure that accommodates any molecular mechanism expressible as rate equations or membrane fluxes. An illustration of the method is provided by a dynamic simulation of IP3-mediated Ca2+ release from endoplasmic reticulum in a neuronal cell. The results can be directly compared to experimental observations and provide insight into the role of experimentally inaccessible components of the overall mechanism. Images FIGURE 1 FIGURE 2 FIGURE 4 FIGURE 5 PMID:9284281

  17. Multiple-species analysis of point count data: A more parsimonious modelling framework

    USGS Publications Warehouse

    Alldredge, M.W.; Pollock, K.H.; Simons, T.R.; Shriner, S.A.

    2007-01-01

    1. Although population surveys often provide information on multiple species, these data are rarely analysed within a multiple-species framework despite the potential for more efficient estimation of population parameters. 2. We have developed a multiple-species modelling framework that uses similarities in capture/detection processes among species to model multiple species data more parsimoniously. We present examples of this approach applied to distance, time of detection and multiple observer sampling for avian point count data. 3. Models that included species as a covariate and individual species effects were generally selected as the best models for distance sampling, but group models without species effects performed best for the time of detection and multiple observer methods. Population estimates were more precise for no-species-effect models than for species-effect models, demonstrating the benefits of exploiting species' similarities when modelling multiple species data. Partial species-effect models and additive models were also useful because they modelled similarities among species while allowing for species differences. 4. Synthesis and applications. We recommend the adoption of multiple-species modelling because of its potential for improved population estimates. This framework will be particularly beneficial for modelling count data from rare species because information on the detection process can be 'borrowed' from more common species. The multiple-species modelling framework presented here is applicable to a wide range of sampling techniques and taxa. ?? 2007 The Authors.

  18. An Integration and Evaluation Framework for ESPC Coupled Models

    DTIC Science & Technology

    2014-09-30

    Models PI: Ben Kirtman University of Miami – RSMAS Atmospheric Sciences 4600 Rickenbacker Causeway Miami, FL 33149 Phone: (305) 421-4046...annual report. 7 ESPC Testbed: Interactive ensemble Initial prototype of multi- model interactive ensemble coupling infrastructure. Initial...get HYCOM integrated. Enhanced the interactive ensemble so that multiple atmosphere, land and ice component models can be simultaneously coupled

  19. A MODELLING FRAMEWORK FOR MERCURY CYCLING IN LAKE MICHIGAN

    EPA Science Inventory

    A time-dependent mercury model was developed to describe mercury cycling in Lake Michigan. The model addresses dynamic relationships between net mercury loadings and the resulting concentrations of mercury species in the water and sediment. The simplified predictive modeling fram...

  20. A MODELLING FRAMEWORK FOR MERCURY CYCLING IN LAKE MICHIGAN

    EPA Science Inventory

    A time-dependent mercury model was developed to describe mercury cycling in Lake Michigan. The model addresses dynamic relationships between net mercury loadings and the resulting concentrations of mercury species in the water and sediment. The simplified predictive modeling fram...

  1. Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

    ERIC Educational Resources Information Center

    Young, Cristobal; Holsteen, Katherine

    2017-01-01

    Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

  2. Enhancing a socio-hydrological modelling framework through field observations: a case study in India

    NASA Astrophysics Data System (ADS)

    den Besten, Nadja; Pande, Saket; Savenije, Huub H. G.

    2016-04-01

    Recently a smallholder socio-hydrological modelling framework was proposed and deployed to understand the underlying dynamics of Agrarian Crisis in Maharashtra state of India. It was found that cotton and sugarcane smallholders whom lack irrigation and storage techniques are most susceptible to distress. This study further expands the application of the modelling framework to other crops that are abundant in the state of Maharashtra, such as Paddy, Jowar and Soyabean to assess whether the conclusions on the possible causes behind smallholder distress still hold. Further, a fieldwork will be undertaken in March 2016 in the district of Pune. During the fieldwork 50 smallholders will be interviewed in which socio-hydrological assumptions on hydrology and capital equations and corresponding closure relationships, incorporated the current model, will be put to test. Besides the assumptions, the questionnaires will be used to better understand the hydrological reality of the farm holders, in terms of water usage and storage capacity. In combination with historical records on the smallholders' socio-economic data acquired over the last thirty years available through several NGOs in the region, socio-hydrological realism of the modelling framework will be enhanced. The preliminary outcomes of a desktop study show the possibilities of a water-centric modelling framework in understanding the constraints on smallholder farming. The results and methods described can be a first step guiding following research on the modelling framework: a start in testing the framework in multiple rural locations around the globe.

  3. Computational Morphodynamics: A modeling framework to understand plant growth

    PubMed Central

    Chickarmane, Vijay; Roeder, Adrienne H.K.; Tarr, Paul T.; Cunha, Alexandre; Tobin, Cory; Meyerowitz, Elliot M.

    2014-01-01

    Computational morphodynamics utilizes computer modeling to understand the development of living organisms over space and time. Results from biological experiments are used to construct accurate and predictive models of growth. These models are then used to make novel predictions providing further insight into the processes in question, which can be tested experimentally to either confirm or rule out the validity of the computational models. This review highlights two fundamental issues: (1.) models should span and integrate single cell behavior with tissue development and (2.) the necessity to understand the feedback between mechanics of growth and chemical or molecular signaling. We review different approaches to model plant growth and discuss a variety of model types that can be implemented, with the aim of demonstrating how this methodology can be used, to explore the morphodynamics of plant development. PMID:20192756

  4. Approaches to implementing deterministic models in a probabilistic framework

    SciTech Connect

    Talbott, D.V.

    1995-04-01

    The increasing use of results from probabilistic risk assessments in the decision-making process makes it ever more important to eliminate simplifications in probabilistic models that might lead to conservative results. One area in which conservative simplifications are often made is modeling the physical interactions that occur during the progression of an accident sequence. This paper demonstrates and compares different approaches for incorporating deterministic models of physical parameters into probabilistic models; parameter range binning, response curves, and integral deterministic models. An example that combines all three approaches in a probabilistic model for the handling of an energetic material (i.e. high explosive, rocket propellant,...) is then presented using a directed graph model.

  5. Integration of the Radiation Belt Environment Model Into the Space Weather Modeling Framework

    NASA Technical Reports Server (NTRS)

    Glocer, A.; Toth, G.; Fok, M.; Gombosi, T.; Liemohn, M.

    2009-01-01

    We have integrated the Fok radiation belt environment (RBE) model into the space weather modeling framework (SWMF). RBE is coupled to the global magnetohydrodynamics component (represented by the Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme, BATS-R-US, code) and the Ionosphere Electrodynamics component of the SWMF, following initial results using the Weimer empirical model for the ionospheric potential. The radiation belt (RB) model solves the convection-diffusion equation of the plasma in the energy range of 10 keV to a few MeV. In stand-alone mode RBE uses Tsyganenko's empirical models for the magnetic field, and Weimer's empirical model for the ionospheric potential. In the SWMF the BATS-R-US model provides the time dependent magnetic field by efficiently tracing the closed magnetic field-lines and passing the geometrical and field strength information to RBE at a regular cadence. The ionosphere electrodynamics component uses a two-dimensional vertical potential solver to provide new potential maps to the RBE model at regular intervals. We discuss the coupling algorithm and show some preliminary results with the coupled code. We run our newly coupled model for periods of steady solar wind conditions and compare our results to the RB model using an empirical magnetic field and potential model. We also simulate the RB for an active time period and find that there are substantial differences in the RB model results when changing either the magnetic field or the electric field, including the creation of an outer belt enhancement via rapid inward transport on the time scale of tens of minutes.

  6. Integration of the Radiation Belt Environment Model Into the Space Weather Modeling Framework

    NASA Technical Reports Server (NTRS)

    Glocer, A.; Toth, G.; Fok, M.; Gombosi, T.; Liemohn, M.

    2009-01-01

    We have integrated the Fok radiation belt environment (RBE) model into the space weather modeling framework (SWMF). RBE is coupled to the global magnetohydrodynamics component (represented by the Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme, BATS-R-US, code) and the Ionosphere Electrodynamics component of the SWMF, following initial results using the Weimer empirical model for the ionospheric potential. The radiation belt (RB) model solves the convection-diffusion equation of the plasma in the energy range of 10 keV to a few MeV. In stand-alone mode RBE uses Tsyganenko's empirical models for the magnetic field, and Weimer's empirical model for the ionospheric potential. In the SWMF the BATS-R-US model provides the time dependent magnetic field by efficiently tracing the closed magnetic field-lines and passing the geometrical and field strength information to RBE at a regular cadence. The ionosphere electrodynamics component uses a two-dimensional vertical potential solver to provide new potential maps to the RBE model at regular intervals. We discuss the coupling algorithm and show some preliminary results with the coupled code. We run our newly coupled model for periods of steady solar wind conditions and compare our results to the RB model using an empirical magnetic field and potential model. We also simulate the RB for an active time period and find that there are substantial differences in the RB model results when changing either the magnetic field or the electric field, including the creation of an outer belt enhancement via rapid inward transport on the time scale of tens of minutes.

  7. Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework.

    PubMed

    Kwok, T; Smith, K A

    2000-09-01

    The aim of this paper is to study both the theoretical and experimental properties of chaotic neural network (CNN) models for solving combinatorial optimization problems. Previously we have proposed a unifying framework which encompasses the three main model types, namely, Chen and Aihara's chaotic simulated annealing (CSA) with decaying self-coupling, Wang and Smith's CSA with decaying timestep, and the Hopfield network with chaotic noise. Each of these models can be represented as a special case under the framework for certain conditions. This paper combines the framework with experimental results to provide new insights into the effect of the chaotic neurodynamics of each model. By solving the N-queen problem of various sizes with computer simulations, the CNN models are compared in different parameter spaces, with optimization performance measured in terms of feasibility, efficiency, robustness and scalability. Furthermore, characteristic chaotic neurodynamics crucial to effective optimization are identified, together with a guide to choosing the corresponding model parameters.

  8. Introducing MERGANSER: A Flexible Framework for Ecological Niche Modeling

    NASA Astrophysics Data System (ADS)

    Klawonn, M.; Dow, E. M.

    2015-12-01

    Ecological Niche Modeling (ENM) is a collection of techniques to find a "fundamental niche", the range of environmental conditions suitable for a species' survival in the absence of inter-species interactions, given a set of environmental parameters. Traditional approaches to ENM face a number of obstacles including limited data accessibility, data management problems, computational costs, interface usability, and model validation. The MERGANSER system, which stands for Modeling Ecological Residency Given A Normalized Set of Environmental Records, addresses these issues through powerful data persistence and flexible data access, coupled with a clear presentation of results and fine-tuned control over model parameters. MERGANSER leverages data measuring 72 weather related phenomena, land cover, soil type, population, species occurrence, general species information, and elevation, totaling over 1.5 TB of data. To the best of the authors' knowledge, MERGANSER uses higher-resolution spatial data sets than previously published models. Since MERGANSER stores data in an instance of Apache SOLR, layers generated in support of niche models are accessible to users via simplified Apache Lucene queries. This is made even simpler via an HTTP front end that generates Lucene queries automatically. Specifically, a user need only enter the name of a place and a species to run a model. Using this approach to synthesizing model layers, the MERGANSER system has successfully reproduced previously published niche model results with a simplified user experience. Input layers for the model are generated dynamically using OpenStreetMap and SOLR's spatial search functionality. Models are then run using either user-specified or automatically determined parameters after normalizing them into a common grid. Finally, results are visualized in the web interface, which allows for quick validation. Model results and all surrounding metadata are also accessible to the user for further study.

  9. Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

    DOE PAGES

    Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.; ...

    2016-04-25

    Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FEmore » meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.« less

  10. Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

    SciTech Connect

    Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.; Hanks, Byron W.; Foulk, James W.; Battaile, Corbett C.

    2016-04-25

    Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FE meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.

  11. Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

    SciTech Connect

    Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.; Hanks, Byron W.; Foulk, James W.; Battaile, Corbett C.

    2016-04-25

    Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FE meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.

  12. A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

    EPA Science Inventory

    This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

  13. Modeling in Chemistry as Cultural Practice: A Theoretical Framework with Implications for Chemistry Education. Draft.

    ERIC Educational Resources Information Center

    Erduran, Sibel

    This paper reports on an interdisciplinary theoretical framework for the characterization of models and modeling that can be useful in application to chemistry education. The underlying argument marks a departure from an emphasis on concepts that are the outcomes of chemical inquiry about how knowledge growth occurs through modeling in chemistry.…

  14. A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

    EPA Science Inventory

    This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

  15. Deep Modeling: Circuit Characterization Using Theory Based Models in a Data Driven Framework

    SciTech Connect

    Bolme, David S; Mikkilineni, Aravind K; Rose, Derek C; Yoginath, Srikanth B; Holleman, Jeremy; Judy, Mohsen

    2017-01-01

    Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity can degrade system performance. Furthermore, in all but the simplest systems, it is impossible to directly measure the intermediate outputs of all sub-circuits. The result is that circuit designers are unable to accurately evaluate the non-idealities of computational circuits in-situ and are therefore unable to fully utilize measurement results to improve future designs. In this paper we present a technique to use deep learning frameworks to model physical systems. Recently developed libraries like TensorFlow make it possible to use back propagation to learn parameters in the context of modeling circuit behavior. Offsets and scaling errors can be discovered even for sub-circuits that are deeply embedded in a computational system and not directly observable. The learned parameters can be used to refine simulation methods or to identify appropriate compensation strategies. We demonstrate the framework using a mixed-signal convolution operator as an example circuit.

  16. A Model Framework for Course Materials Construction (Second Edition).

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    Designed for use by Coast Guard course writers, curriculum developers, course coordinators, and instructors as a decision-support system, this publication presents a model that translates the Intraservices Procedures for Instructional Systems Development curriculum design model into materials usable by classroom teachers and students. Although…

  17. A Framework for Modeling and Analyzing Complex Distributed Systems

    DTIC Science & Technology

    2005-08-15

    tool Kronos , Hybrid Systems HI, Verification and Control, Springer-Verlag, pages 208-219, LNCS, volume 1066, 1996 [16] Roberto De Prisco, Alan Fekete...Open- Kronos model checker for timed automata. Monte Carlo model checking has already been implemented in Open- Kronos and has demonstrated significant

  18. An integrated hydrologic modeling framework for coupling SWAT with MODFLOW

    USDA-ARS?s Scientific Manuscript database

    The Soil and Water Assessment Tool (SWAT), MODFLOW, and Energy Balance based Evapotranspiration (EB_ET) models are extensively used to estimate different components of the hydrological cycle. Surface and subsurface hydrological processes are modeled in SWAT but limited to the extent of shallow aquif...

  19. Physical Models of Galaxy Formation in a Cosmological Framework

    NASA Astrophysics Data System (ADS)

    Somerville, Rachel S.; Davé, Romeel

    2015-08-01

    Modeling galaxy formation in a cosmological context presents one of the greatest challenges in astrophysics today due to the vast range of scales and numerous physical processes involved. Here we review the current status of models that employ two leading techniques to simulate the physics of galaxy formation: semianalytic models and numerical hydrodynamic simulations. We focus on a set of observational targets that describe the evolution of the global and structural properties of galaxies from roughly cosmic high noon (z â¼ 2-3) to the present. Although minor discrepancies remain, overall, models show remarkable convergence among different methods and make predictions that are in qualitative agreement with observations. Modelers have converged on a core set of physical processes that are critical for shaping galaxy properties. This core set includes cosmological accretion, strong stellar-driven winds that are more efficient at low masses, black hole feedback that preferentially suppresses star formation at high masses, and structural and morphological evolution through merging and environmental processes. However, all cosmological models currently adopt phenomenological implementations of many of these core processes, which must be tuned to observations. Many details of how these diverse processes interact within a hierarchical structure formation setting remain poorly understood. Emerging multiscale simulations are helping to bridge the gap between stellar and cosmological scales, placing models on a firmer, more physically grounded footing. Concurrently, upcoming telescope facilities will provide new challenges and constraints for models, particularly by directly constraining inflows and outflows through observations of gas in and around galaxies.

  20. Developing an Interdisciplinary Curriculum Framework for Aquatic-Ecosystem Modeling

    ERIC Educational Resources Information Center

    Saito, Laurel; Segale, Heather M.; DeAngelis, Donald L.; Jenkins, Stephen H.

    2007-01-01

    This paper presents results from a July 2005 workshop and course aimed at developing an interdisciplinary course on modeling aquatic ecosystems that will provide the next generation of practitioners with critical skills for which formal training is presently lacking. Five different course models were evaluated: (1) fundamentals/general principles…

  1. Developing an Interdisciplinary Curriculum Framework for Aquatic-Ecosystem Modeling

    ERIC Educational Resources Information Center

    Saito, Laurel; Segale, Heather M.; DeAngelis, Donald L.; Jenkins, Stephen H.

    2007-01-01

    This paper presents results from a July 2005 workshop and course aimed at developing an interdisciplinary course on modeling aquatic ecosystems that will provide the next generation of practitioners with critical skills for which formal training is presently lacking. Five different course models were evaluated: (1) fundamentals/general principles…

  2. Source-to-Outcome Microbial Exposure and Risk Modeling Framework

    EPA Science Inventory

    A Quantitative Microbial Risk Assessment (QMRA) is a computer-based data-delivery and modeling approach that integrates interdisciplinary fate/transport, exposure, and impact models and databases to characterize potential health impacts/risks due to pathogens. As such, a QMRA ex...

  3. Abdominal surgery process modeling framework for simulation using spreadsheets.

    PubMed

    Boshkoska, Biljana Mileva; Damij, Talib; Jelenc, Franc; Damij, Nadja

    2015-08-01

    We provide a continuation of the existing Activity Table Modeling methodology with a modular spreadsheets simulation. The simulation model developed is comprised of 28 modeling elements for the abdominal surgery cycle process. The simulation of a two-week patient flow in an abdominal clinic with 75 beds demonstrates the applicability of the methodology. The simulation does not include macros, thus programming experience is not essential for replication or upgrading the model. Unlike the existing methods, the proposed solution employs a modular approach for modeling the activities that ensures better readability, the possibility of easily upgrading the model with other activities, and its easy extension and connectives with other similar models. We propose a first-in-first-served approach for simulation of servicing multiple patients. The uncertain time duration of the activities is modeled using the function "rand()". The patients movements from one activity to the next one is tracked with nested "if()" functions, thus allowing easy re-creation of the process without the need of complex programming.

  4. Simulation Framework for Teaching in Modeling and Simulation Areas

    ERIC Educational Resources Information Center

    De Giusti, Marisa Raquel; Lira, Ariel Jorge; Villarreal, Gonzalo Lujan

    2008-01-01

    Simulation is the process of executing a model that describes a system with enough detail; this model has its entities, an internal state, some input and output variables and a list of processes bound to these variables. Teaching a simulation language such as general purpose simulation system (GPSS) is always a challenge, because of the way it…

  5. The Relational-Cultural Model: A Framework for Group Process

    ERIC Educational Resources Information Center

    Comstock, Dana L.; Duffey, Thelma; St. George, Holly

    2002-01-01

    The relational-cultural model of psychotherapy has been evolving for the past 20 years. Within this model, difficult group dynamics are conceptualized as the playing out of the central relational paradox. This paradox recognizes that an individual may yearn for connection but, out of a sense of fear, simultaneously employ strategies that restrict…

  6. Source-to-Outcome Microbial Exposure and Risk Modeling Framework

    EPA Science Inventory

    A Quantitative Microbial Risk Assessment (QMRA) is a computer-based data-delivery and modeling approach that integrates interdisciplinary fate/transport, exposure, and impact models and databases to characterize potential health impacts/risks due to pathogens. As such, a QMRA ex...

  7. A Framework for Non-Gaussian Signal Modeling and Estimation

    DTIC Science & Technology

    1999-06-01

    1993. [38] B. P. Carlin , N. G. Polson, and D. S. Stoffer, "A Monte Carlo approach to nonnormal and nonlinear state-space modeling," Journal of the...NJ: Prentice-Hall, 1992. [198] J. R. Thompson, Empirical Model Building. New York: John Wiley & Sons, 1989. [199] J. R. Thompson and R. A. Tapia

  8. A MULTISCALE, CELL-BASED FRAMEWORK FOR MODELING CANCER DEVELOPMENT

    SciTech Connect

    JIANG, YI

    2007-01-16

    Cancer remains to be one of the leading causes of death due to diseases. We use a systems approach that combines mathematical modeling, numerical simulation, in vivo and in vitro experiments, to develop a predictive model that medical researchers can use to study and treat cancerous tumors. The multiscale, cell-based model includes intracellular regulations, cellular level dynamics and intercellular interactions, and extracellular level chemical dynamics. The intracellular level protein regulations and signaling pathways are described by Boolean networks. The cellular level growth and division dynamics, cellular adhesion and interaction with the extracellular matrix is described by a lattice Monte Carlo model (the Cellular Potts Model). The extracellular dynamics of the signaling molecules and metabolites are described by a system of reaction-diffusion equations. All three levels of the model are integrated through a hybrid parallel scheme into a high-performance simulation tool. The simulation results reproduce experimental data in both avasular tumors and tumor angiogenesis. By combining the model with experimental data to construct biologically accurate simulations of tumors and their vascular systems, this model will enable medical researchers to gain a deeper understanding of the cellular and molecular interactions associated with cancer progression and treatment.

  9. A Framework for Modeling Human-Machine Interactions

    NASA Technical Reports Server (NTRS)

    Shafto, Michael G.; Rosekind, Mark R. (Technical Monitor)

    1996-01-01

    Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

  10. A Framework for Modeling Human-Machine Interactions

    NASA Technical Reports Server (NTRS)

    Shafto, Michael G.; Rosekind, Mark R. (Technical Monitor)

    1996-01-01

    Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

  11. Bayesian model selection framework for identifying growth patterns in filamentous fungi.

    PubMed

    Lin, Xiao; Terejanu, Gabriel; Shrestha, Sajan; Banerjee, Sourav; Chanda, Anindya

    2016-06-07

    This paper describes a rigorous methodology for quantification of model errors in fungal growth models. This is essential to choose the model that best describes the data and guide modeling efforts. Mathematical modeling of growth of filamentous fungi is necessary in fungal biology for gaining systems level understanding on hyphal and colony behaviors in different environments. A critical challenge in the development of these mathematical models arises from the indeterminate nature of their colony architecture, which is a result of processing diverse intracellular signals induced in response to a heterogeneous set of physical and nutritional factors. There exists a practical gap in connecting fungal growth models with measurement data. Here, we address this gap by introducing the first unified computational framework based on Bayesian inference that can quantify individual model errors and rank the statistical models based on their descriptive power against data. We show that this Bayesian model comparison is just a natural formalization of Occam׳s razor. The application of this framework is discussed in comparing three models in the context of synthetic data generated from a known true fungal growth model. This framework of model comparison achieves a trade-off between data fitness and model complexity and the quantified model error not only helps in calibrating and comparing the models, but also in making better predictions and guiding model refinements. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Comparison of Hugoniots calculated for aluminum in the framework of three quantum-statistical models

    NASA Astrophysics Data System (ADS)

    Kadatskiy, M. A.; Khishchenko, K. V.

    2015-11-01

    The results of calculations of thermodynamic properties of aluminum under shock compression in the framework of the Thomas-Fermi model, the Thomas-Fermi model with quantum and exchange corrections and the Hartree-Fock-Slater model are presented. The influences of the thermal motion and the interaction of ions are taken into account in the framework of three models: the ideal gas, the one-component plasma and the charged hard spheres. Calculations are performed in the pressure range from 1 to 107 GPa. Calculated Hugoniots are compared with available experimental data.

  13. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework.

    PubMed

    Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

    2014-03-04

    The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.

  14. The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

    PubMed Central

    Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

    2014-01-01

    The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

  15. Surgical model-view-controller simulation software framework for local and collaborative applications

    PubMed Central

    Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

    2010-01-01

    Purpose Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. Methods A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. Results The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. Conclusion A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users. PMID:20714933

  16. Surgical model-view-controller simulation software framework for local and collaborative applications.

    PubMed

    Maciel, Anderson; Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

    2011-07-01

    Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users.

  17. A big-microsite framework for soil carbon modeling.

    PubMed

    Davidson, Eric A; Savage, Kathleen E; Finzi, Adrien C

    2014-12-01

    Soil carbon cycling processes potentially play a large role in biotic feedbacks to climate change, but little agreement exists at present on what the core of numerical soil C cycling models should look like. In contrast, most canopy models of photosynthesis and leaf gas exchange share a common 'Farquhaur-model' core structure. Here, we explore why a similar core model structure for heterotrophic soil respiration remains elusive and how a pathway to that goal might be envisioned. The spatial and temporal variation in soil microsite conditions greatly complicates modeling efforts, but we believe it is possible to develop a tractable number of parameterizable equations that are organized into a coherent, modular, numerical model structure. First, we show parallels in insights gleaned from linking Arrhenius and Michaelis-Menten kinetics for both photosynthesis and soil respiration. Additional equations and layers of complexity are then added to simulate substrate supply. For soils, model modules that simulate carbon stabilization processes will be key to estimating the fraction of soil C that is accessible to enzymes. Potential modules for dynamic photosynthate input, wetting-event inputs, freeze-thaw impacts on substrate diffusion, aggregate turnover, soluble-C sorption, gas transport, methane respiration, and microbial dynamics are described for conceptually and numerically linking our understanding of fast-response processes of soil gas exchange with longer-term dynamics of soil carbon and nitrogen stocks. © 2014 John Wiley & Sons Ltd.

  18. Validation framework of the finite element modeling of liver tissue.

    PubMed

    Shi, Hongjian; Fahmi, Rachid; Farag, Aly A

    2005-01-01

    In this work, we aim at validating some soft tissue deformation models using high resolution Micro Computed Tomography (Micro-CT) and medium resolution Cone-Beam CT (CBCT) images. These imaging techniques play a key role in detecting the tissue deformation details in the contact region between the tissue and the surgical tool (probe) even for small force loads, and provide good capabilities for creating accurate 3D models of tissues. Surgical simulations rely on accurate representation of the mechanical response of soft tissues subjected to surgical manipulations. Several finite element (F.E.) models have been suggested to characterize soft tissues. However, validating these models for specific tissues still remains a challenge. For our validation, ex vivo lamb liver is chosen to validate the linear elastic model (LEM), the linear viscoelastic model (LVEM), and the neo-Hooke hyperelastic model (NHM). We found that the LEM is more applicable to lamb liver than the LVEM for small force loads (< 40 g) and that the NHM is closer to reality than the LVEM for this same range of force loads.

  19. Brokering as a framework for hydrological model repeatability

    NASA Astrophysics Data System (ADS)

    Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary

    2015-04-01

    Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.

  20. A framework to establish credibility of computational models in biology.

    PubMed

    Patterson, Eann A; Whelan, Maurice P

    2016-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance.

  1. The Community Earth System Model: A Framework for Collaborative Research

    SciTech Connect

    Hurrell, Jim; Holland, Marika M.; Gent, Peter R.; Ghan, Steven J.; Kay, Jennifer; Kushner, P.; Lamarque, J.-F.; Large, William G.; Lawrence, David M.; Lindsay, Keith; Lipscomb, William; Long , Matthew; Mahowald, N.; Marsh, D.; Neale, Richard; Rasch, Philip J.; Vavrus, Steven J.; Vertenstein, Mariana; Bader, David C.; Collins, William D.; Hack, James; Kiehl, J. T.; Marshall, Shawn

    2013-09-30

    The Community Earth System Model (CESM) is a flexible and extensible community tool used to investigate a diverse set of earth system interactions across multiple time and space scales. This global coupled model is a natural evolution from its predecessor, the Community Climate System Model, following the incorporation of new earth system capabilities. These include the ability to simulate biogeochemical cycles, atmospheric chemistry, ice sheets, and a high-top atmosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new predictive capabilities and increasing our collective knowledge about the behavior and interactions of the earth system. Simulations with numerous configurations of the CESM have been provided to the Coupled Model Intercomparison Project Phase 5 (CMIP5) and are being analyzed by the broader community of scientists. Additionally, the model source code and associated documentation are freely available to the scientific community to use for earth system studies, making it a true community tool. Here we describe this earth modeling system, its various possible configurations, and illustrate its capabilities with a few science highlights.

  2. An Integrated Model Framework of Catchment-Scale Ecohydrological Processes

    NASA Astrophysics Data System (ADS)

    Niu, G.; Troch, P. A.; Paniconi, C.; Zeng, X.; Scott, R. L.; Huxman, T. E.; Pelletier, J. D.

    2012-12-01

    The interactions between the atmospheric, hydrological, and ecological processes at various spatial and temporal scales are not fully represented in most hydrometeorological, ecohydrological, and Earth System Models. We present a fully integrated catchment-scale ecohydrological model consisting of a 3-dimensional (3D) process-based hydrological model and a land surface model (LSM) and tests over an energy limited catchment (8.4 km2) of the Sleepers River watershed in Vermont and a water limited catchment in Arizona (7.92 ha). The hydrological model (CATHY) describes 3D subsurface flow in variably saturated porous media and surface routing on hillslopes and in stream channels, while the LSM, an augmented version of Noah LSM with multiple parameterization schemes (NoahMP), accounts for energy, water, and carbon flux exchanges between land surface and the atmosphere. CATHY and NoahMP are coupled through an exchange of fluxes and state variables. The coupled CATHY/NoahMP model, with minor calibration, performs well in simulating the observed snow mass and discharge. In the energy-limited catchment where runoff is dominant, the coupled model at both 90 m and 30 m resolutions simulated the observed discharge in response to snowmelt better than did the 1D NoahMP. The coupled model also simulates surface energy, water, and CO2 fluxes reasonably well at various temporal scales over the water-limited catchment. The 3D coupled model produced wetter soils in lowland areas along stream rills and channels through re-infiltration of lateral overland flow. This water subsidy provide plants with favorable conditions to produce more persistent leaves, CO2, and ET fluxes during drought years and dry-down periods.

  3. Next Generation Framework for Aquatic Modeling of the Earth System (NextFrAMES)

    NASA Astrophysics Data System (ADS)

    Fekete, B. M.; Wollheim, W. M.; Lakhankar, T.; Vorosmarty, C. J.

    2008-12-01

    Earth System model development is becoming an increasingly complex task. As scientists attempt to represent the physical and bio-geochemical processes and various feedback mechanisms in unprecedented detail, the models themselves are becoming increasingly complex. At the same time, the surrounding IT infrastructure needed to carry out these detailed model computations is growing increasingly complex as well. To be accurate and useful, Earth System models must manage a vast amount of data in heterogenous computing environments ranging from single CPU systems to Beowulf type computer clusters. Scientists developing Earth System models increasingly confront obstacles associated with IT infrastructure. Numerous development efforts are on the way to ease that burden and offer model development platforms that reduce IT challenges and allow scientists to focus on their science. While these new modeling frameworks (e.g. FMS, ESMF, CCA, OpenMI) do provide solutions to many IT challenges (performing input/output, managing space and time, establishing model coupling, etc.), they are still considerably complex and often have steep learning curves. Over the course of the last fifteen years ,the University of New Hampshire developed several modeling frameworks independently from the above-mentioned efforts (Data Assembler, Frameworks for Aquatic Modeling of the Earth System and NextFrAMES which is continued at CCNY). While the UNH modeling frameworks have numerous similarities to those developed by other teams, these frameworks, in particular the latest NextFrAMES, represent a novel model development paradigm. While other modeling frameworks focus on providing services to modelers to perform various tasks, NextFrAMES strives to hide all of those services and provide a new approach for modelers to express their scientific thoughts. From a scientific perspective, most models have two core elements: the overall model structure (defining the linkages between the simulated processes

  4. Distribution modeling of nonlinear inverse controllers under a Bayesian framework.

    PubMed

    Herzallah, Randa; Lowe, David

    2007-01-01

    The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems and is demonstrated on nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) examples.

  5. Integrated Modeling, Mapping, and Simulation (IMMS) framework for planning exercises.

    SciTech Connect

    Friedman-Hill, Ernest J.; Plantenga, Todd D.

    2010-06-01

    The Integrated Modeling, Mapping, and Simulation (IMMS) program is designing and prototyping a simulation and collaboration environment for linking together existing and future modeling and simulation tools to enable analysts, emergency planners, and incident managers to more effectively, economically, and rapidly prepare, analyze, train, and respond to real or potential incidents. When complete, the IMMS program will demonstrate an integrated modeling and simulation capability that supports emergency managers and responders with (1) conducting 'what-if' analyses and exercises to address preparedness, analysis, training, operations, and lessons learned, and (2) effectively, economically, and rapidly verifying response tactics, plans and procedures.

  6. Development of a practical modeling framework for estimating the impact of wind technology on bird populations

    SciTech Connect

    Morrison, M.L.; Pollock, K.H.

    1997-11-01

    One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds, in a cost-effective way. The authors accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds.

  7. Model Components of the Certification Framework for Geologic Carbon Sequestration Risk Assessment

    SciTech Connect

    Oldenburg, Curtis M.; Bryant, Steven L.; Nicot, Jean-Philippe; Kumar, Navanit; Zhang, Yingqi; Jordan, Preston; Pan, Lehua; Granvold, Patrick; Chow, Fotini K.

    2009-06-01

    We have developed a framework for assessing the leakage risk of geologic carbon sequestration sites. This framework, known as the Certification Framework (CF), emphasizes wells and faults as the primary potential leakage conduits. Vulnerable resources are grouped into compartments, and impacts due to leakage are quantified by the leakage flux or concentrations that could potentially occur in compartments under various scenarios. The CF utilizes several model components to simulate leakage scenarios. One model component is a catalog of results of reservoir simulations that can be queried to estimate plume travel distances and times, rather than requiring CF users to run new reservoir simulations for each case. Other model components developed for the CF and described here include fault characterization using fault-population statistics; fault connection probability using fuzzy rules; well-flow modeling with a drift-flux model implemented in TOUGH2; and atmospheric dense-gas dispersion using a mesoscale weather prediction code.

  8. A Model Framework for Science and Other Course Materials Construction.

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    A model is presented to provide guidance for Coast Guard writers, curriculum developers, course coordinators, and instructors who intend to update, or draft course materials. Detailed instructions are provided for developing instructor's guides and student's guides. (CS)

  9. A model integration framework for linking SWAT and MODFLOW

    USDA-ARS?s Scientific Manuscript database

    Hydrological response and transport phenomena are driven by atmospheric, surface and subsurface processes. These complex processes occur at different spatiotemporal scales requiring comprehensive modeling to assess the impact of anthropogenic activity on hydrology and fate and transport of chemical ...

  10. A Model Framework for Science and Other Course Materials Construction.

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    A model is presented to provide guidance for Coast Guard writers, curriculum developers, course coordinators, and instructors who intend to update, or draft course materials. Detailed instructions are provided for developing instructor's guides and student's guides. (CS)

  11. Effective Thermal Conductivity Modeling of Sandstones: SVM Framework Analysis

    NASA Astrophysics Data System (ADS)

    Rostami, Alireza; Masoudi, Mohammad; Ghaderi-Ardakani, Alireza; Arabloo, Milad; Amani, Mahmood

    2016-06-01

    Among the most significant physical characteristics of porous media, the effective thermal conductivity (ETC) is used for estimating the thermal enhanced oil recovery process efficiency, hydrocarbon reservoir thermal design, and numerical simulation. This paper reports the implementation of an innovative least square support vector machine (LS-SVM) algorithm for the development of enhanced model capable of predicting the ETCs of dry sandstones. By means of several statistical parameters, the validity of the presented model was evaluated. The prediction of the developed model for determining the ETCs of dry sandstones was in excellent agreement with the reported data with a coefficient of determination value ({R}2) of 0.983 and an average absolute relative deviation of 0.35 %. Results from present research show that the proposed LS-SVM model is robust, reliable, and efficient in calculating the ETCs of sandstones.

  12. A PROBABILISTIC MODELING FRAMEWORK FOR PREDICTING POPULATION EXPOSURES TO BENZENE

    EPA Science Inventory

    The US Environmental Protection Agency (EPA) is modifying their probabilistic Stochastic Human Exposure Dose Simulation (SHEDS) model to assess aggregate exposures to air toxics. Air toxics include urban Hazardous Air Pollutants (HAPS) such as benzene from mobile sources, part...

  13. A PROBABILISTIC MODELING FRAMEWORK FOR PREDICTING POPULATION EXPOSURES TO BENZENE

    EPA Science Inventory

    The US Environmental Protection Agency (EPA) is modifying their probabilistic Stochastic Human Exposure Dose Simulation (SHEDS) model to assess aggregate exposures to air toxics. Air toxics include urban Hazardous Air Pollutants (HAPS) such as benzene from mobile sources, part...

  14. C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework

    DTIC Science & Technology

    2010-06-01

    structural constraints to this active set has value both at the level of representation robustness and at the level of signal interpretation (in particular...structure (and robustness ) to the problem is to consider the simultaneous encoding of multiple signals, requesting that they all share the same...in the set, which translates into robustness in the model (class) selection. As with models such as Lasso and Group Lasso, the optimal parameters λ1

  15. Integrated Modeling Framework for Anthropometry and Physiology Virtual Body

    DTIC Science & Technology

    2007-06-01

    crash dummies (HYBRID III and THOR) databases, generation of geometrical models for and a state of the art instrumented thorax for blast simulations...graphics. Early humans were represented as simple performance, de-mining, ballistic protection, and other articulated bodies made of segments and...cfdrc.com 2. ATB 1998, Articulated Total Body Model Version V Website: www.cfdrc.com Users Manual: Phone: 256-726-4857 Fax: 256-726-4806 8

  16. Model Adaptation for Prognostics in a Particle Filtering Framework

    NASA Technical Reports Server (NTRS)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  17. Design theoretic analysis of three system modeling frameworks.

    SciTech Connect

    McDonald, Michael James

    2007-05-01

    This paper analyzes three simulation architectures from the context of modeling scalability to address System of System (SoS) and Complex System problems. The paper first provides an overview of the SoS problem domain and reviews past work in analyzing model and general system complexity issues. It then identifies and explores the issues of vertical and horizontal integration as well as coupling and hierarchical decomposition as the system characteristics and metrics against which the tools are evaluated. In addition, it applies Nam Suh's Axiomatic Design theory as a construct for understanding coupling and its relationship to system feasibility. Next it describes the application of MATLAB, Swarm, and Umbra (three modeling and simulation approaches) to modeling swarms of Unmanned Flying Vehicle (UAV) agents in relation to the chosen characteristics and metrics. Finally, it draws general conclusions for analyzing model architectures that go beyond those analyzed. In particular, it identifies decomposition along phenomena of interaction and modular system composition as enabling features for modeling large heterogeneous complex systems.

  18. Multiscale Model of Colorectal Cancer Using the Cellular Potts Framework

    PubMed Central

    Osborne, James M

    2015-01-01

    Colorectal cancer (CRC) is one of the major causes of death in the developed world and forms a canonical example of tumorigenesis. CRC arises from a string of mutations of individual cells in the colorectal crypt, making it particularly suited for multiscale multicellular modeling, where mutations of individual cells can be clearly represented and their effects readily tracked. In this paper, we present a multicellular model of the onset of colorectal cancer, utilizing the cellular Potts model (CPM). We use the model to investigate how, through the modification of their mechanical properties, mutant cells colonize the crypt. Moreover, we study the influence of mutations on the shape of cells in the crypt, suggesting possible cell- and tissue-level indicators for identifying early-stage cancerous crypts. Crucially, we discuss the effect that the motility parameters of the model (key factors in the behavior of the CPM) have on the distribution of cells within a homeostatic crypt, resulting in an optimal parameter regime that accurately reflects biological assumptions. In summary, the key results of this paper are 1) how to couple the CPM with processes occurring on other spatial scales, using the example of the crypt to motivate suitable motility parameters; 2) modeling mutant cells with the CPM; 3) and investigating how mutations influence the shape of cells in the crypt. PMID:26461973

  19. Multiscale Model of Colorectal Cancer Using the Cellular Potts Framework.

    PubMed

    Osborne, James M

    2015-01-01

    Colorectal cancer (CRC) is one of the major causes of death in the developed world and forms a canonical example of tumorigenesis. CRC arises from a string of mutations of individual cells in the colorectal crypt, making it particularly suited for multiscale multicellular modeling, where mutations of individual cells can be clearly represented and their effects readily tracked. In this paper, we present a multicellular model of the onset of colorectal cancer, utilizing the cellular Potts model (CPM). We use the model to investigate how, through the modification of their mechanical properties, mutant cells colonize the crypt. Moreover, we study the influence of mutations on the shape of cells in the crypt, suggesting possible cell- and tissue-level indicators for identifying early-stage cancerous crypts. Crucially, we discuss the effect that the motility parameters of the model (key factors in the behavior of the CPM) have on the distribution of cells within a homeostatic crypt, resulting in an optimal parameter regime that accurately reflects biological assumptions. In summary, the key results of this paper are 1) how to couple the CPM with processes occurring on other spatial scales, using the example of the crypt to motivate suitable motility parameters; 2) modeling mutant cells with the CPM; 3) and investigating how mutations influence the shape of cells in the crypt.

  20. A full annual cycle modeling framework for American black ducks

    USGS Publications Warehouse

    Robinson, Orin J.; McGowan, Conor; Devers, Patrick K.; Brook, Rodney W.; Huang, Min; Jones, Malcom; McAuley, Daniel G.; Zimmerman, Guthrie S.

    2016-01-01

    American black ducks (Anas rubripes) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density-dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.

  1. Utilisation of theoretical models and frameworks in the process of evidence synthesis.

    PubMed

    Godfrey, Christina M; Harrison, Margaret B; Graham, Ian D; Ross-White, Amanda

    2010-01-01

    A systematic review is a comprehensive enquiry or study of secondary data sources. There is a research question, an a priori articulation of methods and a set of procedures to focus the investigation. Despite these rigorous structures to guide the review, synthesising evidence is a challenging, resource intense and time consuming process. Large volumes of information complicate not only the search functions, but also the conceptualisation of the evidence needed to create the concise and integrated results. Use of a theoretical model or framework could serve as an essential element in effectively focusing the review and designing the methods to respond to the knowledge question. This scoping review sought to confirm the value of models or frameworks used by authors working within traditional methodologies for evidence synthesis. Types of participants The focus of this review was on the context of health care.Types of intervention(s)/phenomena of interest All studies that discussed models or frameworks used specifically to address the process of synthesis were included.Types of studies Discussion, scholarship or methodology papers and reviews were included.Types of outcome All theoretical models or frameworks were described, with specific attention to the purpose of the framework for each study, and the contribution of the framework to the process of synthesis. The search strategy aimed to find both published and unpublished studies. A three-step search strategy was utilised. The databases for published material included CINAHL; Medline; EMBASE; PsycINFO; AMED; Cochrane; Biomed Central; Scirus; and Mednar. Databases for unpublished material included Dissertation Abstracts; Sociological Abstracts; Conference proceedings. The review was a focused scoping review to locate and describe the contribution of theoretical models or frameworks to the process of synthesis. The methodological quality of the discussion papers was therefore not assessed. Data was extracted from

  2. Towards uncertainty quantification and parameter estimation for Earth system models in a component-based modeling framework

    NASA Astrophysics Data System (ADS)

    Peckham, Scott D.; Kelbert, Anna; Hill, Mary C.; Hutton, Eric W. H.

    2016-05-01

    Component-based modeling frameworks make it easier for users to access, configure, couple, run and test numerical models. However, they do not typically provide tools for uncertainty quantification or data-based model verification and calibration. To better address these important issues, modeling frameworks should be integrated with existing, general-purpose toolkits for optimization, parameter estimation and uncertainty quantification. This paper identifies and then examines the key issues that must be addressed in order to make a component-based modeling framework interoperable with general-purpose packages for model analysis. As a motivating example, one of these packages, DAKOTA, is applied to a representative but nontrivial surface process problem of comparing two models for the longitudinal elevation profile of a river to observational data. Results from a new mathematical analysis of the resulting nonlinear least squares problem are given and then compared to results from several different optimization algorithms in DAKOTA.

  3. Introducing a boreal wetland model within the Earth System model framework

    NASA Astrophysics Data System (ADS)

    Getzieh, R. J.; Brovkin, V.; Reick, C.; Kleinen, T.; Raddatz, T.; Raivonen, M.; Sevanto, S.

    2009-04-01

    Wetlands of the northern high latitudes with their low temperatures and waterlogged conditions are prerequisite for peat accumulation. They store at least 25% of the global soil organic carbon and constitute currently the largest natural source of methane. These boreal and subarctic peat carbon pools are sensitive to climate change since the ratio of carbon sequestration and emission is closely dependent on hydrology and temperature. Global biogeochemistry models used for simulations of CO2 dynamics in the past and future climates usually ignore changes in the peat storages. Our approach aims at the evaluation of the boreal wetland feedback to climate through the CO2 and CH4 fluxes on decadal to millennial time scales. A generic model of organic matter accumulation and decay in boreal wetlands is under development in the MPI for Meteorology in cooperation with the University of Helsinki. Our approach is to develop a wetland model which is consistent with the physical and biogeochemical components of the land surface module JSBACH as a part of the Earth System model framework ECHAM5-MPIOM-JSBACH. As prototypes, we use modelling approach by Frolking et al. (2001) for the peat dynamics and the wetland model by Wania (2007) for vegetation cover and plant productivity. An initial distribution of wetlands follows the GLWD-3 map by Lehner and Döll (2004). First results of the modelling approach will be presented. References: Frolking, S. E., N. T. Roulet, T. R. Moore, P. J. H. Richard, M. Lavoie and S. D. Muller (2001): Modeling Northern Peatland Decomposition and Peat Accumulation, Ecosystems, 4, 479-498. Lehner, B., Döll P. (2004): Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296 (1-4), 1-22. Wania, R. (2007): Modelling northern peatland land surface processes, vegetation dynamics and methane emissions. PhD thesis, University of Bristol, 122 pp.

  4. Building an Open Source Framework for Integrated Catchment Modeling

    NASA Astrophysics Data System (ADS)

    Jagers, B.; Meijers, E.; Villars, M.

    2015-12-01

    In order to develop effective strategies and associated policies for environmental management, we need to understand the dynamics of the natural system as a whole and the human role therein. This understanding is gained by comparing our mental model of the world with observations from the field. However, to properly understand the system we should look at dynamics of water, sediments, water quality, and ecology throughout the whole system from catchment to coast both at the surface and in the subsurface. Numerical models are indispensable in helping us understand the interactions of the overall system, but we need to be able to update and adjust them to improve our understanding and test our hypotheses. To support researchers around the world with this challenging task we started a few years ago with the development of a new open source modeling environment DeltaShell that integrates distributed hydrological models with 1D, 2D, and 3D hydraulic models including generic components for the tracking of sediment, water quality, and ecological quantities throughout the hydrological cycle composed of the aforementioned components. The open source approach combined with a modular approach based on open standards, which allow for easy adjustment and expansion as demands and knowledge grow, provides an ideal starting point for addressing challenging integrated environmental questions.

  5. Hybrid Stars in the Framework of NJL Models

    NASA Astrophysics Data System (ADS)

    Contrera, Gustavo A.; Orsaria, Milva; Ranea-Sandoval, I. F.; Weber, Fridolin

    We compute models for the equation of state (EoS) of the matter in the cores of hybrid stars. Hadronic matter is treated in the non-linear relativistic mean-field approximation, and quark matter is modeled by three-flavor local and non-local Nambu‑Jona-Lasinio (NJL) models with repulsive vector interactions. The transition from hadronic to quark matter is constructed by considering either a soft phase transition (Gibbs construction) or a sharp phase transition (Maxwell construction). We find that high-mass neutron stars with masses up to 2.1 ‑ 2.4M⊙ may contain a mixed phase with hadrons and quarks in their cores, if global charge conservation is imposed via the Gibbs conditions. However, if the Maxwell conditions is considered, the appearance of a pure quark matter core either destabilizes the star immediately (commonly for non-local NJL models) or leads to a very short hybrid star branch in the mass-radius relation (generally for local NJL models).

  6. Implementation of a PETN failure model using ARIA's general chemistry framework

    SciTech Connect

    Hobbs, Michael L.

    2017-01-01

    We previously developed a PETN thermal decomposition model that accurately predicts thermal ignition and detonator failure [1]. This model was originally developed for CALORE [2] and required several complex user subroutines. Recently, a simplified version of the PETN decomposition model was implemented into ARIA [3] using a general chemistry framework without need for user subroutines. Detonator failure was also predicted with this new model using ENCORE. The model was simplified by 1) basing the model on moles rather than mass, 2) simplifying the thermal conductivity model, and 3) implementing ARIA’s new phase change model. This memo briefly describes the model, implementation, and validation.

  7. Toward a multiscale modeling framework for understanding serotonergic function

    PubMed Central

    Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

    2017-01-01

    Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

  8. Modeling Agriculture and Land Use in an Integrated Assessment Framework

    SciTech Connect

    Sands, Ronald D.; Leimbach, Marian

    2003-01-01

    The Agriculture and Land Use (AgLU) model is a top-down economic model with just enough structure to simulate global land use change and the resulting carbon emissions over one century. These simulations are done with and without a carbon policy represented by a positive carbon price. Increases in the carbon price create incentives for production of commercial biomass that affect the distribution of other land types and, therefore, carbon emissions from land use change. Commercial biomass provides a link between the agricultural and energy systems. The ICLIPS core model uses AgLU to provide estimates of carbon emissions from land use change as one component of total greenhouse gas emissions.

  9. A Flexible Atmospheric Modeling Framework for the CESM

    SciTech Connect

    Randall, David; Heikes, Ross; Konor, Celal

    2014-11-12

    We have created two global dynamical cores based on the unified system of equations and Z-grid staggering on an icosahedral grid, which are collectively called UZIM (Unified Z-grid Icosahedral Model). The z-coordinate version (UZIM-height) can be run in hydrostatic and nonhydrostatic modes. The sigma-coordinate version (UZIM-sigma) runs in only hydrostatic mode. The super-parameterization has been included as a physics option in both models. The UZIM versions with the super-parameterization are called SUZI. With SUZI-height, we have completed aquaplanet runs. With SUZI-sigma, we are making aquaplanet runs and realistic climate simulations. SUZI-sigma includes realistic topography and a SiB3 model to parameterize the land-surface processes.

  10. A modelling and reasoning framework for social networks policies

    NASA Astrophysics Data System (ADS)

    Governatori, Guido; Iannella, Renato

    2011-02-01

    Policy languages (such as privacy and rights) have had little impact on the wider community. Now that social networks have taken off, the need to revisit policy languages and realign them towards social networks requirements has become more apparent. One such language is explored as to its applicability to the social networks masses. We also argue that policy languages alone are not sufficient and thus they should be paired with reasoning mechanisms to provide precise and unambiguous execution models of the policies. To this end, we propose a computationally oriented model to represent, reason with and execute policies for social networks.

  11. BlueSky Modeling Framework: Current application, user tools, and future additions

    NASA Astrophysics Data System (ADS)

    Strand, T.; Larkin, N.; Solomon, R.; Sullivan, D.; Raffuse, S. M.; Pryden, D.; Craig, K.; Wheeler, N.; Chinkin, L.

    2009-12-01

    The BlueSky Smoke Modeling Framework (BlueSky) uses models, static and dynamic datasets, and real-time satellite data streams to simulated fuel consumption, smoke emissions, and plume rise and transport. BlueSky is a modular system that allows for addition and modification of the smoke modeling pathway with new models or datasets. BlueSky can be applied to: simulate smoke transport and air quality impacts over the next three-seven days; determine probable smoke behavior from a prescribed fire based on climatological data; estimate emissions from fire on a regional and national scale; and assess model pathway uncertainties, strengths, and weaknesses. BlueSky is embedded in many real-time smoke prediction systems including the U.S. National Weather Service’s Operational Smoke Predictions and the U.S. National Emissions Inventory uses BlueSky to estimate fire emissions. BlueSky is a framework that incorporates many different models at each modeling step ([Fuel loading]-[fuel Consumption]-[Time rate of consumption]-[Emissions]-[Plume rise]-[Transport and dispersion of smoke]). The underlying models are not changed from their original form or programming language, instead, they are surrounded by a Python wrapper. These wrappers serve as a standard interface throughout the framework and ensure that the models receive the data they require in the proper format. This unprecedented flexibility allows for the user to select models and datasets at each modeling step. BlueSky users can choose from over 3,000 different model pathway combinations. The utility of BlueSky is through its framework, for example, any model enabled within BlueSky can automatically be served in a web-services environment and used remotely. This enables novel applications for both the science and community end-user. We present current applications, decision support system tools and current research uses, and a discussion of future BlueSky framework development.

  12. The Plug model: A potential new framework for modeling cyclic activity in Strombolian-type volcanoes

    NASA Astrophysics Data System (ADS)

    Suckale, J.; Hager, B. H.; Cashman, K. V.; Belien, I. L.; Persson, P. O.

    2011-12-01

    Normal Strombolian activity is possibly one of the most famous examples of cyclic activity in volcanology. The leading paradigm for this type of activity posits that each eruption represents the burst of a large gas slug ascending through liquid magma in the volcanic conduit. When this slug model was first devised, the petrological characteristics of the Strombolian plumbing system were poorly constrained. Since then, numerous petrological studies have established the existence of highly crystalline magma in the upper few hundred meters of the Strombolian conduit. The goal of this paper is to incorporate the recent petrological evidence into a more general framework of normal activity at Stromboli and potentially other basaltic volcanoes exhibiting comparable eruptive patterns. We model the gas- and crystal-rich magma in the upper part of the conduit as a porous material with finite yield strength. Since the ascent velocities of gas bubbles decreases upon reaching this zone, gas accumulates below the plug-like crystalline layer and exerts a buoyancy pressure in the vertical direction. In order to evaluate the resulting stress and strain inside the plug, we have developed a numerical model that captures the variable material properties of the plug and the surrounding host rock based on a finite-element discretization in 3D. Our simulations indicate that the accumulating gas pressure could cause yielding and failure in the plug. We hypothesize that failure of the plug in conjunction with drainage of gas-rich magma represents a normal eruption. Our alternative view of the mechanism behind normal eruptions also offers an explanation for the origin of the VLP signal as the seismic signal associated with the onset of failure, and sheds new light on the crater morphology at Stromboli. While our model is currently adjusted to reflect the geometry and magmatic properties of Stromboli volcano, it could be generalized to other volcanoes and could provide a framework for

  13. Iberian (South American) Model of Judicial Review: Toward Conceptual Framework

    ERIC Educational Resources Information Center

    Klishas, Andrey A.

    2016-01-01

    The paper explores Latin American countries legislation with the view to identify specific features of South American model of judicial review. The research methodology rests on comparative approach to analyzing national constitutions' provisions and experts' interpretations thereof. The constitutional provisions of Brazil, Peru, Mexico, and…

  14. An Empirical Generative Framework for Computational Modeling of Language Acquisition

    ERIC Educational Resources Information Center

    Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

    2010-01-01

    This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…

  15. COMPASS: A Framework for Automated Performance Modeling and Prediction

    SciTech Connect

    Lee, Seyong; Meredith, Jeremy S; Vetter, Jeffrey S

    2015-01-01

    Flexible, accurate performance predictions offer numerous benefits such as gaining insight into and optimizing applications and architectures. However, the development and evaluation of such performance predictions has been a major research challenge, due to the architectural complexities. To address this challenge, we have designed and implemented a prototype system, named COMPASS, for automated performance model generation and prediction. COMPASS generates a structured performance model from the target application's source code using automated static analysis, and then, it evaluates this model using various performance prediction techniques. As we demonstrate on several applications, the results of these predictions can be used for a variety of purposes, such as design space exploration, identifying performance tradeoffs for applications, and understanding sensitivities of important parameters. COMPASS can generate these predictions across several types of applications from traditional, sequential CPU applications to GPU-based, heterogeneous, parallel applications. Our empirical evaluation demonstrates a maximum overhead of 4%, flexibility to generate models for 9 applications, speed, ease of creation, and very low relative errors across a diverse set of architectures.

  16. An Empirical Generative Framework for Computational Modeling of Language Acquisition

    ERIC Educational Resources Information Center

    Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

    2010-01-01

    This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…

  17. A Framework for Modelling Connective Tissue Changes in VIIP Syndrome

    NASA Technical Reports Server (NTRS)

    Ethier, C. R.; Best, L.; Gleason, R.; Mulugeta, L.; Myers, J. G.; Nelson, E. S.; Samuels, B. C.

    2014-01-01

    Insertion of astronauts into microgravity induces a cascade of physiological adaptations, notably including a cephalad fluid shift. Longer-duration flights carry an increased risk of developing Visual Impairment and Intracranial Pressure (VIIP) syndrome, a spectrum of ophthalmic changes including posterior globe flattening, choroidal folds, distension of the optic nerve sheath, kinking of the optic nerve and potentially permanent degradation of visual function. The slow onset of changes in VIIP, their chronic nature, and the similarity of certain clinical features of VIIP to ophthalmic findings in patients with raised intracranial pressure strongly suggest that: (i) biomechanical factors play a role in VIIP, and (ii) connective tissue remodeling must be accounted for if we wish to understand the pathology of VIIP. Our goal is to elucidate the pathophysiology of VIIP and suggest countermeasures based on biomechanical modeling of ocular tissues, suitably informed by experimental data, and followed by validation and verification. We specifically seek to understand the quasi-homeostatic state that evolves over weeks to months in space, during which ocular tissue remodeling occurs. This effort is informed by three bodies of work: (i) modeling of cephalad fluid shifts; (ii) modeling of ophthalmic tissue biomechanics in glaucoma; and (iii) modeling of connective tissue changes in response to biomechanical loading.

  18. Extensible Modeling and Simulation Framework (XMSF) 2004 Project Summary Report

    DTIC Science & Technology

    2007-11-02

    Modeling Language (UML) • Agent Based Technologies o Supporting Technologies Artificial Intelligence research Autonomous and cooperating agents...et. al., 2003) Gangemi, A., Guarino, N., Masolo, C., and Oltramari, A., “ Sweetening WORDNET with DOLCE,” AI Magazine, 24:3, Fall 2003, pp 13-24

  19. A framework for modelling kinematic measurements in gravity field applications

    NASA Technical Reports Server (NTRS)

    Schwarz, K. P.; Wei, M.

    1989-01-01

    To assess the resolution of the local gravity field from kinematic measurements, a state model for motion in the gravity field of the earth is formulated. The resulting set of equations can accommodate gravity gradients, specific force, acceleration, velocity and position as input data and can take into account approximation errors as well as sensor errors.

  20. Formulating the Brogden Classification Framework as a Discrete Choice Model

    DTIC Science & Technology

    2012-11-01

    that satisfy the job quota constraints using an MMNL parameter estimation algorithm. Biogeme ( Bierle , 2003) model files for carrying out the...demand. Cambridge, MA: MIT Press. Bierle , M. (2003). An introduction to BIOGEME (Version 1.3) http://roso.epfl.ch/biogeme. Brogden, H. E. (1954). A

  1. Development of a distributed air pollutant dry deposition modeling framework

    Treesearch

    Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

    2012-01-01

    A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

  2. Levine's Conservation Model: A Framework for Advanced Gerontology Nursing Practice.

    PubMed

    Abumaria, Ibrahim Mahmoud; Hastings-Tolsma, Marie; Sakraida, Teresa J

    2015-01-01

    Growing numbers of older adults place increased demands on already burdened healthcare systems. The cost of managing chronic illnesses mandates greater emphasis on management and prevention. This article explores the adaptation of Levine's Conservation Model as a structure for providing care to the older adult by the adult-gerontology primary care nurse practitioner (AGNP). The AGNP role, designed to provide quality care to adult and older adult populations, offers the opportunity to not only manage health care of the elderly, but to also advocate, lead in collaborative care efforts, conduct advanced planning, and manage and negotiate health delivery systems. The use of nursing models can foster the design of effective interventions that promote health of the older adult, particularly in the long-term care environment. Levine's Conservation Model provides a useful structure for older adult care in the long-term care setting. As an ideal care manager, the AGNP would be well served to consider use of the model to guide advanced nursing practice. Recommendations for clinical practice, research, and health policy. © 2014 Wiley Periodicals, Inc.

  3. A modeling framework for life history-based conservation planning

    Treesearch

    Eileen S. Burns; Sandor F. Toth; Robert G. Haight

    2013-01-01

    Reserve site selection models can be enhanced by including habitat conditions that populations need for food, shelter, and reproduction. We present a new population protection function that determines whether minimum areas of land with desired habitat features are present within the desired spatial conditions in the protected sites. Embedding the protection function as...

  4. Quasi-continuous stochastic simulation framework for flood modelling

    NASA Astrophysics Data System (ADS)

    Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

    2017-04-01

    Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

  5. Generic framework for mining cellular automata models on protein-folding simulations.

    PubMed

    Diaz, N; Tischer, I

    2016-05-13

    Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

  6. Using a guided inquiry and modeling instructional framework (EIMA) to support preservice K-8 science teaching

    NASA Astrophysics Data System (ADS)

    Schwarz, Christina V.; Gwekwerere, Yovita N.

    2007-01-01

    This paper presents results from a study aimed at helping preservice elementary and middle school teachers incorporate model-centered scientific inquiry into their science teaching practices. Specifically, the authors studied the effect of using a guided inquiry and modeling instructional framework (EIMA) and accompanying science methods instruction on preservice elementary teachers' science lesson design skills, scientific model use, and teaching orientations. Analysis of preservice teachers' pre-posttests, classroom artifacts, peer interviews, and lesson plans throughout the semester indicates that the framework successfully built on preservice teachers' prior instructional ideas, and that the majority of preservice teachers learned and used the framework in their lesson plans and teaching. Additionally, analysis of pre-posttest differences indicates an increase in posttest lesson plans that focused on engaging students in scientific inquiry using several kinds of models. Most importantly, the framework and accompanying instruction enabled two thirds of the class to move their teaching orientations away from discovery or didactic approaches toward reform-based approaches such as conceptual change, inquiry, and guided inquiry. Results from this study show that using instructional frameworks such as EIMA can enable preservice teachers to socially construct, synthesize, and apply their knowledge for enacting reform-oriented science teaching approaches such as model-centered scientific inquiry.

  7. Development of a framework for reporting health service models for managing rheumatoid arthritis.

    PubMed

    O'Donnell, Siobhan; Li, Linda C; King, Judy; Lauzon, Chantal; Finn, Heather; Vliet Vlieland, Theodora P M

    2010-02-01

    The purpose of this study was to develop a framework for reporting health service models for managing rheumatoid arthritis (RA). We conducted a search of the health sciences literature for primary studies that described interventions which aimed to improve the implementation of health services in adults with RA. Thereafter, a nominal group consensus process was used to synthesize the evidence for the development of the reporting framework. Of the 2,033 citations screened, 68 primary studies were included which described 93 health service models for RA. The origin and meaning of the labels given to these health service delivery models varied widely and, in general, the reporting of their components lacked detail or was absent. The six dimensions underlying the framework for reporting RA health service delivery models are: (1) Why was it founded? (2) Who was involved? (3) What were the roles of those participating? (4) When were the services provided? (5) Where were the services provided/received? (6) How were the services/interventions accessed and implemented, how long was the intervention, how did individuals involved communicate, and how was the model supported/sustained? The proposed framework has the potential to facilitate knowledge exchange among clinicians, researchers, and decision makers in the area of health service delivery. Future work includes the validation of the framework with national and international stakeholders such as clinicians, health care administrators, and health services researchers.

  8. A Distributed Multi-User Role-Based Model Integration Framework

    SciTech Connect

    Dorow, Kevin E.; Gorton, Ian; Thurman, David A.

    2004-06-14

    Integrated computational modeling can be very useful in making quick, yet informed decisions related to environmental issues including Brownfield assessments. Unfortunately, the process of creating meaningful information using this methodology is fraught with difficulties, particularly when multiple computational models are required. Common problems include the inability to seamlessly transfer information between models, the difficulty of incorporating new models and integrating heterogeneous data sources, executing large numbers of model runs in a reasonable time frame, and adequately capturing pedigree information that describes the specific computational steps and data required to reproduce results. While current model integration frameworks have successfully addressed some of these problems, none have addressed all of them. Building on existing work at Pacific Northwest National Laboratory (PNNL), we have created an extensible software architecture for the next generation of model integration frameworks that addresses these issues. This paper describes this architecture that is being developed to support integrated water resource modeling in a metropolitan area.

  9. Systematic narrative review of decision frameworks to select the appropriate modelling approaches for health economic evaluations.

    PubMed

    Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R

    2015-06-17

    In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.

  10. A model for phenotype change in a stochastic framework.

    PubMed

    Wake, Graeme; Pleasants, Anthony; Beedle, Alan; Gluckman, Peter

    2010-07-01

    In some species, an inducible secondary phenotype will develop some time after the environmental change that evokes it. Nishimura (2006) [4] showed how an individual organism should optimize the time it takes to respond to an environmental change ("waiting time''). If the optimal waiting time is considered to act over the population, there are implications for the expected value of the mean fitness in that population. A stochastic predator-prey model is proposed in which the prey have a fixed initial energy budget. Fitness is the product of survival probability and the energy remaining for non-defensive purposes. The model is placed in the stochastic domain by assuming that the waiting time in the population is a normally distributed random variable because of biological variance inherent in mounting the response. It is found that the value of the mean waiting time that maximises fitness depends linearly on the variance of the waiting time.

  11. An Access Control Model for the Uniframe Framework

    DTIC Science & Technology

    2005-05-01

    Because the success or failure of writing of a student record depends on the success or failure of multiple components, the system uses...report the model failure . There are several other temporal properties that can be easily verified. • No student should be able to read any...Systems System Result 1 Failure : These conditions are false. • No student should be able to read any portion of another student’s record. • No

  12. A Computational Framework for Phase-field Modeling

    DTIC Science & Technology

    2011-01-01

    twin embryo within an otherwise perfect single crystal (12). Analytical models based on free energy variations in the context of phase...transformations have been applied to describe twin nucleation (12, 13). Such approaches consider nucleation of a twin embryo of idealized geometry—an elliptical...Crystals, in preparation, 2011. 12. Christian , J. W.; Mahajan, S. Deformation Twinning. Prog. Mater. Sci. 1995, 39, 1–157. 13. Lee, J. K.; Yoo, M

  13. Framework for an asymptotically safe standard model via dynamical breaking

    NASA Astrophysics Data System (ADS)

    Abel, Steven; Sannino, Francesco

    2017-09-01

    We present a consistent embedding of the matter and gauge content of the Standard Model into an underlying asymptotically safe theory that has a well-determined interacting UV fixed point in the large color/flavor limit. The scales of symmetry breaking are determined by two mass-squared parameters with the breaking of electroweak symmetry being driven radiatively. There are no other free parameters in the theory apart from gauge couplings.

  14. Using the Bifocal Modeling Framework to Resolve "Discrepant Events" between Physical Experiments and Virtual Models in Biology

    ERIC Educational Resources Information Center

    Blikstein, Paulo; Fuhrmann, Tamar; Salehi, Shima

    2016-01-01

    In this paper, we investigate an approach to supporting students' learning in science through a combination of physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework, which we call "bifocal modeling," to link student-designed experiments and computer models in real time. In this…

  15. Using the Bifocal Modeling Framework to Resolve "Discrepant Events" between Physical Experiments and Virtual Models in Biology

    ERIC Educational Resources Information Center

    Blikstein, Paulo; Fuhrmann, Tamar; Salehi, Shima

    2016-01-01

    In this paper, we investigate an approach to supporting students' learning in science through a combination of physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework, which we call "bifocal modeling," to link student-designed experiments and computer models in real time. In this…

  16. Computational fluid dynamics framework for aerodynamic model assessment

    NASA Astrophysics Data System (ADS)

    Vallespin, D.; Badcock, K. J.; Da Ronch, A.; White, M. D.; Perfect, P.; Ghoreyshi, M.

    2012-07-01

    This paper reviews the work carried out at the University of Liverpool to assess the use of CFD methods for aircraft flight dynamics applications. Three test cases are discussed in the paper, namely, the Standard Dynamic Model, the Ranger 2000 jet trainer and the Stability and Control Unmanned Combat Air Vehicle. For each of these, a tabular aerodynamic model based on CFD predictions is generated along with validation against wind tunnel experiments and flight test measurements. The main purpose of the paper is to assess the validity of the tables of aerodynamic data for the force and moment prediction of realistic aircraft manoeuvres. This is done by generating a manoeuvre based on the tables of aerodynamic data, and then replaying the motion through a time-accurate computational fluid dynamics calculation. The resulting forces and moments from these simulations were compared with predictions from the tables. As the latter are based on a set of steady-state predictions, the comparisons showed perfect agreement for slow manoeuvres. As manoeuvres became more aggressive some disagreement was seen, particularly during periods of large rates of change in attitudes. Finally, the Ranger 2000 model was used on a flight simulator.

  17. An efficient framework for modeling clouds from Landsat8 images

    NASA Astrophysics Data System (ADS)

    Yuan, Chunqiang; Guo, Jing

    2015-03-01

    Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

  18. Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models.

    PubMed

    Liang, Hua; Wu, Hulin

    2008-12-01

    Differential equation (DE) models are widely used in many scientific fields that include engineering, physics and biomedical sciences. The so-called "forward problem", the problem of simulations and predictions of state variables for given parameter values in the DE models, has been extensively studied by mathematicians, physicists, engineers and other scientists. However, the "inverse problem", the problem of parameter estimation based on the measurements of output variables, has not been well explored using modern statistical methods, although some least squares-based approaches have been proposed and studied. In this paper, we propose parameter estimation methods for ordinary differential equation models (ODE) based on the local smoothing approach and a pseudo-least squares (PsLS) principle under a framework of measurement error in regression models. The asymptotic properties of the proposed PsLS estimator are established. We also compare the PsLS method to the corresponding SIMEX method and evaluate their finite sample performances via simulation studies. We illustrate the proposed approach using an application example from an HIV dynamic study.

  19. Modelling diagnosis in physical therapy: a blackboard framework and models of experts and novices.

    PubMed

    James, G A

    2007-03-01

    The primary objective of this study was to explore clinical reasoning in physical therapy and to highlight the similarities and differences by modelling the diagnostic phase of clinical reasoning. An experimental design comparing expert and novice physical therapists was utilized. Concurrent verbal protocols detailing the clinical reasoning about standardized case material were elicited. A framework for modelling diagnosis was specified and provided the parameters for analysis. The diagnostic utterances were classified as cues or hypotheses and the knowledge utilized was identified. The experts recruited significantly more knowledge than the novices (p = 0.01) and used more cues (p < 0.01). Their diagnoses were more accurate when compared to the original diagnosis. This difference between the experts and novices was reflected in the differences shown in the models (p < 0.01). The differences between these subjects focused upon the knowledge recruitment, which impacted on the accuracy of the diagnosis. The novices' inaccurate or non-existent diagnoses led to poor quality of treatment prescription. Modelling proved to be a useful way of representing these differences.

  20. Evaluation of Hydrometeor Occurrence Profiles in the Multiscale Modeling Framework Climate Model using Atmospheric Classification

    SciTech Connect

    Marchand, Roger T.; Beagley, Nathaniel; Ackerman, Thomas P.

    2009-09-01

    Vertical profiles of hydrometeor occurrence from the Multiscale Modeling Framework (MMF) climate model are compared with profiles observed by a vertically pointing millimeter wavelength cloud-radar (located in the U.S. Southern Great Plains) as a function of the largescale atmospheric state. The atmospheric state is determined by classifying (or clustering) the large-scale (synoptic) fields produced by the MMF and a numerical weather prediction model using a neural network approach. The comparison shows that for cold frontal and post-cold frontal conditions the MMF produces profiles of hydrometeor occurrence that compare favorably with radar observations, while for warm frontal conditions the model tends to produce hydrometeor fractions that are too large with too much cloud (non-precipitating hydrometeors) above 7 km and too much precipitating hydrometeor coverage below 7 km. We also find that the MMF has difficulty capturing the formation of low clouds and that for all atmospheric states that occur during June, July, and August, the MMF produces too much high and thin cloud, especially above 10 km.

  1. Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

    NASA Astrophysics Data System (ADS)

    Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

    2016-12-01

    Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem

  2. A Theoretical Framework for Research in Algebra: Modification of Janvier's "Star" Model of Function Understanding.

    ERIC Educational Resources Information Center

    Bowman, Anita H.

    A pentagonal model, based on the star model of function understanding of C. Janvier (1987), is presented as a framework for the design and interpretation of research in the area of learning the concept of mathematical function. The five vertices of the pentagon correspond to five common representations of mathematical function: (1) graph; (2)…

  3. A modeling framework for characterizing near-road air pollutant concentration at community scales

    EPA Science Inventory

    In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LIN...

  4. A modeling framework for characterizing near-road air pollutant concentration at community scales

    EPA Science Inventory

    In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LIN...

  5. An Odds Ratio Approach for Detecting DDF under the Nested Logit Modeling Framework

    ERIC Educational Resources Information Center

    Terzi, Ragip; Suh, Youngsuk

    2015-01-01

    An odds ratio approach (ORA) under the framework of a nested logit model was proposed for evaluating differential distractor functioning (DDF) in multiple-choice items and was compared with an existing ORA developed under the nominal response model. The performances of the two ORAs for detecting DDF were investigated through an extensive…

  6. Exploring Students' Visual Conception of Matter: Towards Developing a Teaching Framework Using Models

    ERIC Educational Resources Information Center

    Espinosa, Allen A.; Marasigan, Arlyne C.; Datukan, Janir T.

    2016-01-01

    This study explored how students visualise the states and classifications of matter with the use of scientific models. Misconceptions of students in using scientific models were also identified to formulate a teaching framework. To elicit data in the study, a Visual Conception Questionnaire was administered to thirty-four (34), firstyear, general…

  7. HexSim - A general purpose framework for spatially-explicit, individual-based modeling

    EPA Science Inventory

    HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

  8. The Dimensions of Social Justice Model: Transforming Traditional Group Work into a Socially Just Framework

    ERIC Educational Resources Information Center

    Ratts, Manivong J.; Anthony, Loni; Santos, KristiAnna Nicole T.

    2010-01-01

    Social justice is a complex and abstract concept that can be difficult to discuss and integrate within group work. To address this concern, this article introduces readers to the Dimensions of Social Justice Model. The model provides group leaders with a conceptual framework for understanding the degree to which social justice is integrated within…

  9. Exploring Students' Visual Conception of Matter: Towards Developing a Teaching Framework Using Models

    ERIC Educational Resources Information Center

    Espinosa, Allen A.; Marasigan, Arlyne C.; Datukan, Janir T.

    2016-01-01

    This study explored how students visualise the states and classifications of matter with the use of scientific models. Misconceptions of students in using scientific models were also identified to formulate a teaching framework. To elicit data in the study, a Visual Conception Questionnaire was administered to thirty-four (34), firstyear, general…

  10. Applications of a Complimentary Modeling Framework to Improve Regional-Scale Groundwater Prediction

    NASA Astrophysics Data System (ADS)

    Valocchi, A. J.; Demissie, Y.

    2010-12-01

    Computational models of groundwater flow are important tools that help guide management policies and decisions. Modern inverse modeling techniques lead to improved model calibration and knowledge of parameter sensitivity and uncertainty. However, their effectiveness in real world groundwater model application is often limited because of the complexity and heterogeneity of natural subsurface systems as well as the insufficiency of representative measured data. Models are often used to make predictions to evaluate the impact of future scenarios or management policies quite different from the historical conditions that provided the data used for calibration. Models are normally calibrated to yield a good overall match (e.g., as measured by the least squares error criterion) to all the available data, while predictions often focus upon critical spatial locations with the largest impact upon social or hydro-ecological factors. We present a complementary modeling framework to improve the performance of inverse modeling by integrating a calibrated physically-based groundwater model with error-correcting data-driven models to handle the bias and uncertainties arising mainly from ignored or misrepresented processes in the groundwater model. The feasibility of adopting the framework is enhanced by advances in measurement technology and observation networks that are leading to increased amounts of hydrologic data. We have previously published an application of the framework to a hypothetical problem, showing promising results. We present application of the framework to two complex real-world case studies where calibrated MODFLOW models have been developed: the Spokane Valley Rathdrum Prairie and Republican River Compact Administration models. The MODFLOW and data-driven models are calibrated to a portion of the available data, and prediction accuracy is assessed using the remaining data. We find that in general the prediction accuracy of using the complementary model is

  11. Eco-hydrological Modeling in the Framework of Climate Change

    NASA Astrophysics Data System (ADS)

    Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

    2010-05-01

    A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately

  12. Modeling framework for exploring emission impacts of alternative future scenarios

    NASA Astrophysics Data System (ADS)

    Loughlin, D. H.; Benjey, W. G.; Nolte, C. G.

    2010-11-01

    This article presents an approach for creating anthropogenic emission scenarios that can be used to simulate future regional air quality. The approach focuses on energy production and use since these are principal sources of air pollution. We use the MARKAL model to characterize alternative realizations of the US energy system through 2050. Emission growth factors are calculated for major energy system categories using MARKAL, while growth factors from non-energy sectors are based on economic and population projections. The SMOKE model uses these factors to grow a base-year 2002 inventory to future years through 2050. The approach is demonstrated for two emission scenarios: Scenario 1 extends current air regulations through 2050, while Scenario 2 applies a hypothetical policy that limits carbon dioxide (CO2) emissions from the energy system. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role in investigations of linkages among emission drivers, climate and air quality by the U.S. EPA and others.

  13. Spatiotemporal nonpoint source pollution water quality management framework using bi-directional model-GIS linkage

    SciTech Connect

    Faizullabhoy, M.S.; Yoon, J.

    1999-07-01

    A framework for water quality assessment and management purposes was developed. In this framework, a bilateral linkage was implemented between the distributed model, Agricultural Nonpoint Source Pollution Model (AGNPS) and the Geographic Information System (GIS) to investigate a spatiotemporal nonpoint source pollution problem from a 750-acre watershed in the NSGA (Naval Security Group Activity) Northwest base at the Virginia/North Carolina border. AGNPS is an event-based, distributed parameter model that simulates runoff and the transport of sediment and nutrients (nitrogen and phosphorus) from predominantly agricultural watersheds. In this study rather than manually implementing AGNPS simulation, extracted data are integrated in an automated fashion through a direct bilateral linkage framework between the AGNPS model engine and the GIS. This bilateral linkage framework resulted in a powerful, up-to-date tool that would be capable of monitoring and instantaneously visualizing the transport of any pollutant as well as effectively identifying critical areas of the nonpoint source (NPS) pollution. The framework also allowed the various what if scenarios to support the decision-making processes. Best Management Practices (BMP) for the watershed can be generated in a close loop iterative scheme, until predefined management objectives are achieved. Simulated results showed that the optimal BMP scenario achieved an average reduction of about 41% in soluble and sediment-attached nitrogen and about 62% reduction in soluble and sediment phosphorus from current NPS pollution levels.

  14. A new fit-for-purpose model testing framework: Decision Crash Tests

    NASA Astrophysics Data System (ADS)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  15. A mechanistic modeling framework for gas-phase adsorption kinetics and fixed-bed transport

    DOE PAGES

    Ladshaw, Austin P.; Yiacoumi, Sotira; Lin, Ronghong; ...

    2017-07-12

    Adsorption is a complex physicochemical process involving interparticle transport, interphase mass-transfer, intraparticle diffusion, and surface reactions. Although the exact description of the adsorption process will inevitably vary from system to system, it will always be governed by those primary mechanisms. Thus, by devising a model framework that can inherently include those mechanisms, it would be possible to create a modeling platform on which many different adsorption problems could be solved numerically. In order to accomplish this task, a generalized 1-D conservation law model was created to include the necessary mechanisms of adsorption on several different geometrical domains. Specific model applicationsmore » for adsorption were developed under that framework and validated using experimental data available in literature or obtained in this work. This modeling platform makes it easier to model various adsorption problems and develop new adsorption models because of the common treatment of the mathematics governing the physical processes.« less

  16. Common Research Framework for Global Hydrology Utilizing Various Datasets and Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Kim, H.; Oki, T.; Kanae, S.; Seto, S.

    2008-12-01

    A flexible research framework is developed for common needs in global hydrological research. This framework consists of five components including input/output (I/O) interfaces, models, analyzers, and publishers. Backbone chassis of this framework is developed using the Python, because it provides functionalities to wrap and integrate other languages. Global hydrologic simulation needs various dataset such as model forcing data, parameter sets, and validation data, and all of them are distributed in different formats. Therefore, I/O interfaces are implemented to handle different dataset uniformly. They does not only support various data format including text, binary, network common data form (netCDF), gridded binary (GRIB), and GTool, but also provide presets for many field/satellite observational datasets. Model part provides modulized models and interface generators for external numerical models. Noah land surface model and Total Runoff Integrated Pathway (TRIP) are modulized, and helper interfaces to manage an environment of numerical simulation projects including atmospheric and hydrologic models. The analyzer part and publisher consists of many small snippets and utilities to manipulate data with graphical user interface and to publish data on web or so. For computational efficiency, most of base components are written in native compiler languages such as Fortran and C with a wrapping tool F2py, and the Python array calculation module Numpy and plotting module matplotlib are heavily used. This framework solves many difficulties dramatically reducing required time and effort to prepare simulation and process result in the research of global hydrology.

  17. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Izaurralde, R. C.; Sahajpal, R.; Houborg, R.; Milla, Z.

    2013-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  18. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Houborg, R.; Izaurralde, R. C.

    2014-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  19. Clinical Interdisciplinary Collaboration Models and Frameworks From Similarities to Differences: A Systematic Review.

    PubMed

    Mahdizadeh, Mousa; Heydari, Abbas; Karimi Moonaghi, Hossien

    2015-04-19

    So far, various models of interdisciplinary collaboration in clinical nursing have been presented, however, yet a comprehensive model is not available. The purpose of this study is to review the evidences that had presented model or framework with qualitative approach about interdisciplinary collaboration in clinical nursing. All the articles and theses published from 1990 to 10 June 2014 which in both English and Persian models or frameworks of clinicians had presented model or framework of clinical collaboration were searched using databases of Proquest, Scopus, pub Med, Science Direct, and Iranian databases of Sid, Magiran, and Iranmedex. In this review, for published articles and theses, keywords according with MESH such as nurse-physician relations, care team, collaboration, interdisciplinary relations and their Persian equivalents were used. In this study contexts, processes and outcomes of interdisciplinary collaboration as findings were extracted. One of the major components affecting on collaboration that most of the models had emphasized was background of collaboration. Most of studies suggested that the outcome of collaboration were improved care, doctors and nurses' satisfaction, controlling costs, reducing clinical errors and patient's safety. Models and frameworks had different structures, backgrounds, and conditions, but the outcomes were similar. Organizational structure, culture and social factors are important aspects of clinical collaboration. So it is necessary to improve the quality and effectiveness of clinical collaboration these factors to be considered.

  20. A Physics-Informed Machine Learning Framework for RANS-based Predictive Turbulence Modeling

    NASA Astrophysics Data System (ADS)

    Xiao, Heng; Wu, Jinlong; Wang, Jianxun; Ling, Julia

    2016-11-01

    Numerical models based on the Reynolds-averaged Navier-Stokes (RANS) equations are widely used in turbulent flow simulations in support of engineering design and optimization. In these models, turbulence modeling introduces significant uncertainties in the predictions. In light of the decades-long stagnation encountered by the traditional approach of turbulence model development, data-driven methods have been proposed as a promising alternative. We will present a data-driven, physics-informed machine-learning framework for predictive turbulence modeling based on RANS models. The framework consists of three components: (1) prediction of discrepancies in RANS modeled Reynolds stresses based on machine learning algorithms, (2) propagation of improved Reynolds stresses to quantities of interests with a modified RANS solver, and (3) quantitative, a priori assessment of predictive confidence based on distance metrics in the mean flow feature space. Merits of the proposed framework are demonstrated in a class of flows featuring massive separations. Significant improvements over the baseline RANS predictions are observed. The favorable results suggest that the proposed framework is a promising path toward RANS-based predictive turbulence in the era of big data. (SAND2016-7435 A).

  1. The Modular Modeling System (MMS): A modeling framework for water- and environmental-resources management

    USGS Publications Warehouse

    Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.

    2004-01-01

    The interdisciplinary nature and increasing complexity of water- and environmental-resource problems require the use of modeling approaches that can incorporate knowledge from a broad range of scientific disciplines. The large number of distributed hydrological and ecosystem models currently available are composed of a variety of different conceptualizations of the associated processes they simulate. Assessment of the capabilities of these distributed models requires evaluation of the conceptualizations of the individual processes, and the identification of which conceptualizations are most appropriate for various combinations of criteria, such as problem objectives, data constraints, and spatial and temporal scales of application. With this knowledge, "optimal" models for specific sets of criteria can be created and applied. The U.S. Geological Survey (USGS) Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide these model development and application capabilities. MMS supports the integration of models and tools at a variety of levels of modular design. These include individual process models, tightly coupled models, loosely coupled models, and fully-integrated decision support systems. A variety of visualization and statistical tools are also provided. MMS has been coupled with the Bureau of Reclamation (BOR) object-oriented reservoir and river-system modeling framework, RiverWare, under a joint USGS-BOR program called the Watershed and River System Management Program. MMS and RiverWare are linked using a shared relational database. The resulting database-centered decision support system provides tools for evaluating and applying optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. Management issues being addressed include efficiency of water-resources management, environmental concerns such as meeting flow needs for

  2. A modeling framework for investment planning in interdependent infrastructures in multi-hazard environments.

    SciTech Connect

    Brown, Nathanael J. K.; Gearhart, Jared Lee; Jones, Dean A.; Nozick, Linda Karen; Prince, Michael

    2013-09-01

    Currently, much of protection planning is conducted separately for each infrastructure and hazard. Limited funding requires a balance of expenditures between terrorism and natural hazards based on potential impacts. This report documents the results of a Laboratory Directed Research & Development (LDRD) project that created a modeling framework for investment planning in interdependent infrastructures focused on multiple hazards, including terrorism. To develop this framework, three modeling elements were integrated: natural hazards, terrorism, and interdependent infrastructures. For natural hazards, a methodology was created for specifying events consistent with regional hazards. For terrorism, we modeled the terrorists actions based on assumptions regarding their knowledge, goals, and target identification strategy. For infrastructures, we focused on predicting post-event performance due to specific terrorist attacks and natural hazard events, tempered by appropriate infrastructure investments. We demonstrate the utility of this framework with various examples, including protection of electric power, roadway, and hospital networks.

  3. Operationalising a model framework for consumer and community participation in health and medical research

    PubMed Central

    Saunders, Carla; Crossing, Sally; Girgis, Afaf; Butow, Phyllis; Penman, Andrew

    2007-01-01

    The Consumers' Health Forum of Australia and the National Health and Medical Research Council has recently developed a Model Framework for Consumer and Community Participation in Health and Medical Research in order to better align health and medical research with community need, and improve the impact of research. Model frameworks may have little impact on what goes on in practice unless relevant organisations actively make use of them. Philanthropic and government bodies have reported involving consumers in more meaningful or collaborative ways of late. This paper describes how a large charity organisation, which funds a significant proportion of Australian cancer research, operationalised the model framework using a unique approach demonstrating that it is both possible and reasonable for research to be considerate of public values. PMID:17592651

  4. A framework for modelling the selection of assistive technology devices (ATDs).

    PubMed

    Scherer, Marcia; Jutai, Jeffrey; Fuhrer, Marcus; Demers, Louise; Deruyter, Frank

    2007-01-01

    The previously published 'Framework for the conceptual modelling of assistive technology device (ATD) outcomes' assumes antecedent factors that inform it and influence its component variables. This paper proposes a model of factors influencing consumer predispositions and provider practices related to procuring a particular ATD, which is the starting point in the framework. The relevant literature on a variety of factors that influence specific ATD selection is summarized. The decision that a particular ATD is an appropriate and desirable support for an individual is the result of a process which is affected by a broader societal climate that determines, in part, unique personal climates which then foster unique provider and consumer perspectives predisposing each to the selection of a particular ATD. The proposed 'Framework for modelling the selection of ATDs' can contribute to clinical practice and outcomes research by highlighting factors important to consider prior to ATD selection.

  5. Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

    SciTech Connect

    Trebotich, D

    2006-06-24

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

  6. A Bayesian modelling framework for tornado occurrences in North America.

    PubMed

    Cheng, Vincent Y S; Arhonditsis, George B; Sills, David M L; Gough, William A; Auld, Heather

    2015-03-25

    Tornadoes represent one of nature's most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Here we present a Bayesian modelling approach for elucidating the spatiotemporal patterns of tornado activity in North America. Our analysis shows a significant increase in the Canadian Prairies and the Northern Great Plains during the summer, indicating a clear transition of tornado activity from the United States to Canada. The linkage between monthly-averaged atmospheric variables and likelihood of tornado events is characterized by distinct seasonality; the convective available potential energy is the predominant factor in the summer; vertical wind shear appears to have a strong signature primarily in the winter and secondarily in the summer; and storm relative environmental helicity is most influential in the spring. The present probabilistic mapping can be used to draw inference on the likelihood of tornado occurrence in any location in North America within a selected time period of the year.

  7. A Bayesian modelling framework for tornado occurrences in North America

    NASA Astrophysics Data System (ADS)

    Cheng, Vincent Y. S.; Arhonditsis, George B.; Sills, David M. L.; Gough, William A.; Auld, Heather

    2015-03-01

    Tornadoes represent one of nature’s most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Here we present a Bayesian modelling approach for elucidating the spatiotemporal patterns of tornado activity in North America. Our analysis shows a significant increase in the Canadian Prairies and the Northern Great Plains during the summer, indicating a clear transition of tornado activity from the United States to Canada. The linkage between monthly-averaged atmospheric variables and likelihood of tornado events is characterized by distinct seasonality; the convective available potential energy is the predominant factor in the summer; vertical wind shear appears to have a strong signature primarily in the winter and secondarily in the summer; and storm relative environmental helicity is most influential in the spring. The present probabilistic mapping can be used to draw inference on the likelihood of tornado occurrence in any location in North America within a selected time period of the year.

  8. No-core shell model in an EFT framework

    NASA Astrophysics Data System (ADS)

    Stetcu, Ionel; Torkkola, Juhani L.; Barrett, Bruce R.; van Kolck, Ubirajara

    2006-10-01

    Based on an effective field theory (EFT) that integrates out the pions as degrees of freedom (pionless theory), we present a new approach to the derivation of effective interactions suitable for many-body calculations by means of the no-core shell model. The main investigation is directed toward the description of two-body scattering observables in a restricted harmonic oscillator (HO) basis, and the inherent Gibbs oscillation problem which arises from the truncation of the Hilbert space using HO wave functions. Application of the effective interactions to the description of ^4He will be discussed. I.S. J.L.T, and B.R.B. acknowledge partial support by NSF grant numbers PHY0070858 and PHY0244389. U.v.K. acknowledges partial support from DOE grant number DE-FG02-04ER41338 and from the Sloan Foundation.

  9. A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

    PubMed Central

    Heathcote, Andrew

    2016-01-01

    In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information. PMID:26760448

  10. Structural Uncertainties in RANS Models: Reynolds Stress Transport contra Eddy Viscosity Frameworks

    NASA Astrophysics Data System (ADS)

    Mishra, Aashwin; Edeling, Wouter; Iaccarino, Gianluca

    2016-11-01

    A vast majority of turbulent flow studies, both in academia and industry, utilize Reynolds Averaged Navier Stokes based models. There are different RANS modeling frameworks to select from, depending on their complexity and computational requirements, such as eddy viscosity based models, second moment closures, etc. While the relative strengths and weaknesses of each modeling paradigm (vis-a-vis their predictive fidelity, realizability, etc) are roughly established for disparate flows, there are no extant comparative estimates on the relative uncertainty in their predictions. In this investigation, we estimate the structural uncertainty inherent to different RANS modeling approaches for select internal flows. This involves comparisons between models conforming to the same framework, and, across different modeling frameworks. We establish, compare, analyze and explicate the model inadequacy for flows such as in parallel, curved, converging and diverging channels for different models. One of the novel facets of this study involves the estimation of the structural uncertainties of established Reynolds Stress Transport models, and, contrasting these against simpler eddy viscosity models. This work was supported under the DARPA EQUiPS project(Technical Monitor: Fariba Fahroo).

  11. A climate robust integrated modelling framework for regional impact assessment of climate change

    NASA Astrophysics Data System (ADS)

    Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

    2013-04-01

    Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change

  12. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    SciTech Connect

    Hartog, Bobi Kai Den

    1999-03-01

    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  13. A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

    NASA Astrophysics Data System (ADS)

    Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

    Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

  14. The Roy Adaptation Model: A Theoretical Framework for Nurses Providing Care to Individuals With Anorexia Nervosa.

    PubMed

    Jennings, Karen M

    2017-08-18

    Using a nursing theoretical framework to understand, elucidate, and propose nursing research is fundamental to knowledge development. This article presents the Roy Adaptation Model as a theoretical framework to better understand individuals with anorexia nervosa during acute treatment, and the role of nursing assessments and interventions in the promotion of weight restoration. Nursing assessments and interventions situated within the Roy Adaptation Model take into consideration how weight restoration does not occur in isolation but rather reflects an adaptive process within external and internal environments, and has the potential for more holistic care.

  15. The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care.

    PubMed

    van der Meijde, Elisabeth; van den Eertwegh, Alfons J M; Linn, Sabine C; Meijer, Gerrit A; Fijneman, Remond J A; Coupé, Veerle M H

    2016-01-01

    Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost-effectiveness needs to be evaluated. Most cancer cost-effectiveness models are based on the observed clinical events such as recurrence- free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature.

  16. The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care

    PubMed Central

    van der Meijde, Elisabeth; van den Eertwegh, Alfons J. M.; Linn, Sabine C.; Meijer, Gerrit A.; Fijneman, Remond J. A.; Coupé, Veerle M. H.

    2016-01-01

    Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost-effectiveness needs to be evaluated. Most cancer cost-effectiveness models are based on the observed clinical events such as recurrence- free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature. PMID:27346945

  17. A Physics-Based Modeling Framework for Prognostic Studies

    NASA Technical Reports Server (NTRS)

    Kulkarni, Chetan S.

    2014-01-01

    Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable

  18. A Framework for the Optimization of Discrete-Event Simulation Models

    NASA Technical Reports Server (NTRS)

    Joshi, B. D.; Unal, R.; White, N. H.; Morris, W. D.

    1996-01-01

    With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.

  19. Health behaviour models: a framework for studying adherence in children with atopic dermatitis.

    PubMed

    Chisolm, S S; Taylor, S L; Gryzwacz, J G; O'Neill, J L; Balkrishnan, R R; Feldman, S R

    2010-04-01

    Atopic dermatitis (AD) is a common problem of childhood causing considerable distress. Effective topical treatments exist, yet poor adherence often results in poor outcomes. A framework is needed to better understand adherence behaviour. To provide a basis for this framework, we reviewed established models used to describe health behaviour. Structural elements of these models informed the development of an adherence model for AD that can be used to complement empirical AD treatment trials. Health behaviour models provide a means to describe factors that affect adherence and that can mediate the effects of different adherence interventions. Models of adherence behaviour are important for promoting better treatment outcomes for children with AD and their families. These models provide a means to identify new targets to improve adherence and a guide for refining adherence interventions.

  20. Modeling overland flow-driven erosion across a watershed DEM using the Landlab modeling framework.

    NASA Astrophysics Data System (ADS)

    Adams, J. M.; Gasparini, N. M.; Tucker, G. E.; Hobley, D. E. J.; Hutton, E. W. H.; Nudurupati, S. S.; Istanbulluoglu, E.

    2015-12-01

    Many traditional landscape evolution models assume steady-state hydrology when computing discharge, and generally route flow in a single direction, along the path of steepest descent. Previous work has demonstrated that, for larger watersheds or short-duration storms, hydrologic steady-state may not be achieved. In semiarid regions, often dominated by convective summertime storms, landscapes are likely heavily influenced by these short-duration but high-intensity periods of rainfall. To capture these geomorphically significant bursts of rain, a new overland flow method has been implemented in the Landlab modeling framework. This overland flow method routes a hydrograph across a landscape, and allows flow to travel in multiple directions out of a given grid node. This study compares traditional steady-state flow routing and incision methods to the new, hydrograph-driven overland flow and erosion model in Landlab. We propose that for short-duration, high-intensity precipitation events, steady-state, single-direction flow routing models will significantly overestimate discharge and erosion when compared with non-steady, multiple flow direction model solutions. To test this hypothesis, discharge and erosion are modeled using both steady-state and hydrograph methods. A stochastic storm generator is used to generate short-duration, high-intensity precipitation intervals, which drive modeled discharge and erosion across a watershed imported from a digital elevation model, highlighting Landlab's robust raster-gridding library and watershed modeling capabilities. For each storm event in this analysis, peak discharge at the outlet, incision rate at the outlet, as well as total discharge and erosion depth are compared between methods. Additionally, these results are organized by storm duration and intensity to understand how erosion rates scale with precipitation between both flow routing methods. Results show that in many cases traditional steady-state methods overestimate

  1. Models and Frameworks: A Synergistic Association for Developing Component-Based Applications

    PubMed Central

    Sánchez-Ledesma, Francisco; Sánchez, Pedro; Pastor, Juan A.; Álvarez, Bárbara

    2014-01-01

    The use of frameworks and components has been shown to be effective in improving software productivity and quality. However, the results in terms of reuse and standardization show a dearth of portability either of designs or of component-based implementations. This paper, which is based on the model driven software development paradigm, presents an approach that separates the description of component-based applications from their possible implementations for different platforms. This separation is supported by automatic integration of the code obtained from the input models into frameworks implemented using object-oriented technology. Thus, the approach combines the benefits of modeling applications from a higher level of abstraction than objects, with the higher levels of code reuse provided by frameworks. In order to illustrate the benefits of the proposed approach, two representative case studies that use both an existing framework and an ad hoc framework, are described. Finally, our approach is compared with other alternatives in terms of the cost of software development. PMID:25147858

  2. Models and frameworks: a synergistic association for developing component-based applications.

    PubMed

    Alonso, Diego; Sánchez-Ledesma, Francisco; Sánchez, Pedro; Pastor, Juan A; Álvarez, Bárbara

    2014-01-01

    The use of frameworks and components has been shown to be effective in improving software productivity and quality. However, the results in terms of reuse and standardization show a dearth of portability either of designs or of component-based implementations. This paper, which is based on the model driven software development paradigm, presents an approach that separates the description of component-based applications from their possible implementations for different platforms. This separation is supported by automatic integration of the code obtained from the input models into frameworks implemented using object-oriented technology. Thus, the approach combines the benefits of modeling applications from a higher level of abstraction than objects, with the higher levels of code reuse provided by frameworks. In order to illustrate the benefits of the proposed approach, two representative case studies that use both an existing framework and an ad hoc framework, are described. Finally, our approach is compared with other alternatives in terms of the cost of software development.

  3. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection.

    PubMed

    Delaney, Declan T; O'Hare, Gregory M P

    2016-12-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  4. Implementation of EUnetHTA core Model® in Lombardia: the VTS framework.

    PubMed

    Radaelli, Giovanni; Lettieri, Emanuele; Masella, Cristina; Merlino, Luca; Strada, Alberto; Tringali, Michele

    2014-01-01

    This study describes the health technology assessment (HTA) framework introduced by Regione Lombardia to regulate the introduction of new technologies. The study outlines the process and dimensions adopted to prioritize, assess and appraise the requests of new technologies. The HTA framework incorporates and adapts elements from the EUnetHTA Core Model and the EVIDEM framework. It includes dimensions, topics, and issues provided by EUnetHTA Core Model to collect data and process the assessment. Decision making is instead supported by the criteria and Multi-Criteria Decision Analysis technique from the EVIDEM consortium. The HTA framework moves along three process stages: (i) prioritization of requests, (ii) assessment of prioritized technology, (iii) appraisal of technology in support of decision making. Requests received by Regione Lombardia are first prioritized according to their relevance along eight dimensions (e.g., costs, efficiency and efficacy, organizational impact, safety). Evidence about the impacts of the prioritized technologies is then collected following the issues and topics provided by EUnetHTA Core Model. Finally, the Multi-Criteria Decision Analysis technique is used to appraise the novel technology and support Regione Lombardia decision making. The VTS (Valutazione delle Tecnologie Sanitarie) framework has been successfully implemented at the end of 2011. From its inception, twenty-six technologies have been processed.

  5. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection †

    PubMed Central

    Delaney, Declan T.; O’Hare, Gregory M. P.

    2016-01-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks. PMID:27916929

  6. The C1C2: A framework for simultaneous model selection and assessment

    PubMed Central

    Eklund, Martin; Spjuth, Ola; Wikberg, Jarl ES

    2008-01-01

    Background There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper methods for model selection and assessment. Here, we have addressed this issue by introducing a novel and general framework, the C1C2, for simultaneous model selection and assessment. The framework relies on a partitioning of the data in order to separate model choice from model assessment in terms of used data. Since the number of conceivable models in general is vast, it was also of interest to investigate the employment of two automatic search methods, a genetic algorithm and a brute-force method, for model choice. As a demonstration, the C1C2 was applied to simulated and real-world datasets. A penalized linear model was assumed to reasonably approximate the true relation between the dependent and independent variables, thus reducing the model choice problem to a matter of variable selection and choice of penalizing parameter. We also studied the impact of assuming prior knowledge about the number of relevant variables on model choice and generalization error estimates. The results obtained with the C1C2 were compared to those obtained by employing repeated K-fold cross-validation for choosing and assessing a model. Results The C1C2 framework performed well at finding the true model in terms of choosing the correct variable subset and producing reasonable choices for the penalizing parameter, even in situations when the independent variables were highly correlated and when the number of observations was less than the number of variables. The C1C2 framework was also found to give accurate estimates of the generalization error. Prior information about the number of important independent variables improved the variable subset choice but reduced the accuracy of generalization error estimates. Using the genetic algorithm worsened the model choice but not the generalization error estimates

  7. A FRAMEWORK FOR EVALUATING REGIONAL-SCALE NUMERICAL PHOTOCHEMICAL MODELING SYSTEMS

    PubMed Central

    Dennis, Robin; Fox, Tyler; Fuentes, Montse; Gilliland, Alice; Hanna, Steven; Hogrefe, Christian; Irwin, John; Rao, S.Trivikrama.; Scheffe, Richard; Schere, Kenneth; Steyn, Douw; Venkatram, Akula

    2011-01-01

    This paper discusses the need for critically evaluating regional-scale (~200-2000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model’s credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development, and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper. PMID:21461126

  8. Modeling Electron Transport within the Framework of Hydrodynamic Description of Hall Thrusters (Preprint)

    DTIC Science & Technology

    2008-06-16

    kinetic effects related to electron transport in the framework on hydrodynamic model of the plasma flow inside the Hall thruster channel. In...particular, kinetics of the near wall conductivity (NWC) is analyzed and analytical expression is derived that takes into account the sheath effects . The...NWC model is incorporated into the hydrodynamic model. In addition we consider an effect of SEE electron thermalization. It is found that current

  9. Alternative Model-Based and Design-Based Frameworks for Inference from Samples to Populations: From Polarization to Integration

    ERIC Educational Resources Information Center

    Sterba, Sonya K.

    2009-01-01

    A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs.…

  10. Alternative Model-Based and Design-Based Frameworks for Inference from Samples to Populations: From Polarization to Integration

    ERIC Educational Resources Information Center

    Sterba, Sonya K.

    2009-01-01

    A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs.…

  11. Alternative Model-Based and Design-Based Frameworks for Inference From Samples to Populations: From Polarization to Integration

    PubMed Central

    Sterba, Sonya K.

    2010-01-01

    A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs. analytic) to different kinds of populations (finite vs. infinite). We describe the extent of each framework's implementation in observational psychology research. After clarifying some important limitations of each framework, we describe how these limitations are overcome by a newer hybrid model/design-based inferential framework. This hybrid framework allows both kinds of inference to both kinds of populations, given a random sample. We illustrate implementation of the hybrid framework using the High School and Beyond data set. PMID:20411042

  12. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    NASA Astrophysics Data System (ADS)

    Fan, Yanan; Olson, Roman; Evans, Jason P.

    2017-06-01

    We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  13. Implementing vertex dynamics models of cell populations in biology within a consistent computational framework.

    PubMed

    Fletcher, Alexander G; Osborne, James M; Maini, Philip K; Gavaghan, David J

    2013-11-01

    The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell-cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable.

  14. Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories

    NASA Astrophysics Data System (ADS)

    Hipsey, Matthew R.; Hamilton, David P.; Hanson, Paul C.; Carey, Cayelan C.; Coletti, Janaine Z.; Read, Jordan S.; Ibelings, Bas W.; Valesini, Fiona J.; Brookes, Justin D.

    2015-09-01

    Maintaining the health of aquatic systems is an essential component of sustainable catchment management, however, degradation of water quality and aquatic habitat continues to challenge scientists and policy-makers. To support management and restoration efforts aquatic system models are required that are able to capture the often complex trajectories that these systems display in response to multiple stressors. This paper explores the abilities and limitations of current model approaches in meeting this challenge, and outlines a strategy based on integration of flexible model libraries and data from observation networks, within a learning framework, as a means to improve the accuracy and scope of model predictions. The framework is comprised of a data assimilation component that utilizes diverse data streams from sensor networks, and a second component whereby model structural evolution can occur once the model is assessed against theoretically relevant metrics of system function. Given the scale and transdisciplinary nature of the prediction challenge, network science initiatives are identified as a means to develop and integrate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to model assessment that can guide model adaptation. We outline how such a framework can help us explore the theory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry, and, in doing so, also advance the role of prediction in aquatic ecosystem management.

  15. Frameworks for change in healthcare organisations: a formative evaluation of the NHS Change Model.

    PubMed

    Martin, Graham P; Sutton, Elizabeth; Willars, Janet; Dixon-Woods, Mary

    2013-08-01

    Organisational change in complex healthcare systems is a multifaceted process. The English National Health Service recently introduced a 'Change Model' that seeks to offer an evidence-based framework for guiding change. We report findings from a formative evaluation of the NHS Change Model and make recommendations for those developing the Model and its users. The evaluation involved 28 interviews with managers and clinicians making use of the Change Model in relation to a variety of projects. Interviews were fully transcribed and were analysed using an approach based on the Framework method. Participants saw the Change Model as valuable and practically useful. Fidelity to core principles of the Model was variable: participants often altered the Model, especially when using it to orchestrate the work of others. In challenging organisational contexts, the Change Model was sometimes used to delegitimise opposition rather than identify shared purpose among different interest groups. Those guiding change may benefit from frameworks, guidance and toolkits to structure and inform their planning and activities. Participants' experiences suggested the Change Model has much potential. Further work on its design and on supporting materials may optimise the approach, but its utility rests in particular on organisational cultures that support faithful application. © The Author(s) 2013 Reprints and permissions:]br]sagepub.co.uk/journalsPermissions.nav.

  16. A new framework to enhance the interpretation of external validation studies of clinical prediction models.

    PubMed

    Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

    2015-03-01

    It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  17. A conceptual framework to design a dimensional model based on the HL7 Clinical Document Architecture.

    PubMed

    Pecoraro, Fabrizio; Luzi, Daniela; Ricci, Fabrizio L

    2014-01-01

    This paper proposes a conceptual framework to design a dimensional model based on the HL7 Clinical Document Architecture (CDA) standard. The adoption of this framework can represent a possible solution to facilitate the integration of heterogeneous information systems in a clinical data warehouse. This can simplify the Extract, Transform and Load (ETL) procedures that are considered the most time-consuming and expensive part of the data warehouse development process. The paper describes the main activities to be carried out to design the dimensional model outlining the main advantages in the application of the proposed framework. The feasibility of our approach is also demonstrated providing a case study to define clinical indicators for quality assessment.

  18. A structured continuum modelling framework for martensitic transformation and reorientation in shape memory materials.

    PubMed

    Bernardini, Davide; Pence, Thomas J

    2016-04-28

    Models for shape memory material behaviour can be posed in the framework of a structured continuum theory. We study such a framework in which a scalar phase fraction field and a tensor field of martensite reorientation describe the material microstructure, in the context of finite strains. Gradients of the microstructural descriptors naturally enter the formulation and offer the possibility to describe and resolve phase transformation localizations. The constitutive theory is thoroughly described by a single free energy function in conjunction with a path-dependent dissipation function. Balance laws in the form of differential equations are obtained and contain both bulk and surface terms, the latter in terms of microstreses. A natural constraint on the tensor field for martensite reorientation gives rise to reactive fields in these balance laws. Conditions ensuring objectivity as well as the relation of this framework to that provided by currently used models for shape memory alloy behaviour are discussed.

  19. Models of recognition, repetition priming, and fluency: exploring a new framework.

    PubMed

    Berry, Christopher J; Shanks, David R; Speekenbrink, Maarten; Henson, Richard N A

    2012-01-01

    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely independent memory signals (such as explicit and implicit memory) drive recognition and priming; (c) a multiple-systems-2 (MS2) model, in which there are also 2 memory signals, but some degree of dependence is allowed between these 2 signals (and this model subsumes the SS and MS1 models as special cases); and (d) a dual-process signal detection (DPSD1) model, 1 possible extension of a dual-process theory of recognition (Yonelinas, 1994) to priming, in which a signal detection model is augmented by an independent recollection process. The predictions of the models are tested in a continuous-identification-with-recognition paradigm in both normal adults (Experiments 1-3) and amnesic individuals (using data from Conroy, Hopkins, & Squire, 2005). The SS model predicted numerous results in advance. These were not predicted by the MS1 model, though could be accommodated by the more flexible MS2 model. Importantly, measures of overall model fit favored the SS model over the others. These results illustrate a new, formal approach to testing theories of explicit and implicit memory.

  20. Framework for non-coherent interface models at finite displacement jumps and finite strains

    NASA Astrophysics Data System (ADS)

    Ottosen, Niels Saabye; Ristinmaa, Matti; Mosler, Jörn

    2016-05-01

    This paper deals with a novel constitutive framework suitable for non-coherent interfaces, such as cracks, undergoing large deformations in a geometrically exact setting. For this type of interface, the displacement field shows a jump across the interface. Within the engineering community, so-called cohesive zone models are frequently applied in order to describe non-coherent interfaces. However, for existing models to comply with the restrictions imposed by (a) thermodynamical consistency (e.g., the second law of thermodynamics), (b) balance equations (in particular, balance of angular momentum) and (c) material frame indifference, these models are essentially fiber models, i.e. models where the traction vector is collinear with the displacement jump. This constraints the ability to model shear and, in addition, anisotropic effects are excluded. A novel, extended constitutive framework which is consistent with the above mentioned fundamental physical principles is elaborated in this paper. In addition to the classical tractions associated with a cohesive zone model, the main idea is to consider additional tractions related to membrane-like forces and out-of-plane shear forces acting within the interface. For zero displacement jump, i.e. coherent interfaces, this framework degenerates to existing formulations presented in the literature. For hyperelasticity, the Helmholtz energy of the proposed novel framework depends on the displacement jump as well as on the tangent vectors of the interface with respect to the current configuration - or equivalently - the Helmholtz energy depends on the displacement jump and the surface deformation gradient. It turns out that by defining the Helmholtz energy in terms of the invariants of these variables, all above-mentioned fundamental physical principles are automatically fulfilled. Extensions of the novel framework necessary for material degradation (damage) and plasticity are also covered.

  1. Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

    NASA Astrophysics Data System (ADS)

    Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

    2016-11-01

    A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

  2. a Framework for Voxel-Based Global Scale Modeling of Urban Environments

    NASA Astrophysics Data System (ADS)

    Gehrung, Joachim; Hebel, Marcus; Arens, Michael; Stilla, Uwe

    2016-10-01

    The generation of 3D city models is a very active field of research. Modeling environments as point clouds may be fast, but has disadvantages. These are easily solvable by using volumetric representations, especially when considering selective data acquisition, change detection and fast changing environments. Therefore, this paper proposes a framework for the volumetric modeling and visualization of large scale urban environments. Beside an architecture and the right mix of algorithms for the task, two compression strategies for volumetric models as well as a data quality based approach for the import of range measurements are proposed. The capabilities of the framework are shown on a mobile laser scanning dataset of the Technical University of Munich. Furthermore the loss of the compression techniques is evaluated and their memory consumption is compared to that of raw point clouds. The presented results show that generation, storage and real-time rendering of even large urban models are feasible, even with off-the-shelf hardware.

  3. Integrated Modeling, Mapping, and Simulation (IMMS) Framework for Exercise and Response Planning

    NASA Technical Reports Server (NTRS)

    Mapar, Jalal; Hoette, Trisha; Mahrous, Karim; Pancerella, Carmen M.; Plantenga, Todd; Yang, Christine; Yang, Lynn; Hopmeier, Michael

    2011-01-01

    EmergenCy management personnel at federal, stale, and local levels can benefit from the increased situational awareness and operational efficiency afforded by simulation and modeling for emergency preparedness, including planning, training and exercises. To support this goal, the Department of Homeland Security's Science & Technology Directorate is funding the Integrated Modeling, Mapping, and Simulation (IMMS) program to create an integrating framework that brings together diverse models for use by the emergency response community. SUMMIT, one piece of the IMMS program, is the initial software framework that connects users such as emergency planners and exercise developers with modeling resources, bridging the gap in expertise and technical skills between these two communities. SUMMIT was recently deployed to support exercise planning for National Level Exercise 2010. Threat, casualty. infrastructure, and medical surge models were combined within SUMMIT to estimate health care resource requirements for the exercise ground truth.

  4. Water-quality screening-model framework for estuaries: Preliminary application to Long Island Sound

    SciTech Connect

    Not Available

    1986-06-01

    The screening model framework has been developed as part of NOAA's evolving National Estuaries Program (NEP) to provide 'first cut' order of magnitude assessments of resource-use problems and issues affecting marine resource development and conservation throughout the entire Nation. It uses readily available information and is generally designed for easy application to any system. The model is diagnostic in nature and does not replace the need for more sophisticated predictive modeling. It serves as a yardstick against which to assess relatively quickly and inexpensively alternative estuarine management strategies on a basinwide basis, and provides guidance in the development of more advanced modeling approaches that may be needed. The report describes briefly the Phase I application of NOAA's Water Quality Model Framework to Long Island Sound in support of EPA's Region 1 Bays Program. It addresses the pollutant transport behavior of the system as it is reflected in the distribution of salinity within the sound under varying hydrodynamic assumptions.

  5. A multidimensional discontinuous Galerkin modeling framework for overland flow and channel routing

    NASA Astrophysics Data System (ADS)

    West, Dustin W.; Kubatko, Ethan J.; Conroy, Colton J.; Yaufman, Mariah; Wood, Dylan

    2017-04-01

    In this paper, we present the development and application of a new multidimensional, unstructured-mesh model for simulating coupled overland/open-channel flows in the kinematic wave approximation regime. The modeling approach makes use of discontinuous Galerkin (DG) finite element spatial discretizations of variable polynomial degree p, paired with explicit Runge-Kutta time steppers, and is supported by advancements made to an automatic mesh generation tool, ADMESH +, that is used to construct constrained triangulations for channel routing. The developed modeling framework is applied to a set of four test cases, where numerical results are found to compare well with known analytic solutions, experimental data and results from another well-established (structured, finite difference) model within the area of application. The numerical results obtained demonstrate the accuracy and robustness of the developed modeling framework and highlight the potential benefits of using p (polynomial) refinement for hydrological simulations.

  6. Developing a financial framework for academic service partnerships: models of the United States and Europe.

    PubMed

    De Geest, Sabina; Sullivan Marx, Eileen M; Rich, Victoria; Spichiger, Elisabeth; Schwendimann, Rene; Spirig, Rebecca; Van Malderen, Greet

    2010-09-01

    Academic service partnerships (ASPs) are structured linkages between academe and service which have demonstrated higher levels of innovation. In the absence of descriptions in the literature on financial frameworks to support ASPs, the purpose of this paper is to present the supporting financial frameworks of a Swiss and a U.S. ASP. This paper used a case study approach. Two frameworks are presented. The U.S. model presented consists of a variety of ASPs, all linked to the School of Nursing of the University of Pennsylvania. The structural integration and governance system is elucidated. Each ASP has its own source of revenue or grant support with the goal to be fiscally in the black. Joint appointments are used as an instrument to realize these ASPs. The Swiss ASP entails a detailed description of the financial framework of one ASP between the Institute of Nursing Science at the University of Basel and the Inselspital Bern University Hospital. Balance in the partnership, in terms of both benefit and cost between both partners, was a main principle that guided the development of the financial framework and the translation of the ASP in budgetary terms. The model builds on a number of assumptions and provides the partnership management within a simple framework for monitoring and evaluation of the progress of the partnership. In operationalizing an ASP, careful budgetary planning should be an integral part of the preparation and evaluation of the collaboration. The proposed Swiss and U.S. financial frameworks allow doing so. Outcomes of care can be improved with strong nursing service and academic partnerships. Sustaining such partnerships requires attention to financial and contractual arrangements.

  7. Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories

    USGS Publications Warehouse

    Hipsey, Matthew R.; Hamilton, David P.; Hanson, Paul C.; Carey, Cayelan C.; Coletti, Janaine Z; Read, Jordan S.; Ibelings, Bas W; Valensini, Fiona J; Brookes, Justin D

    2015-01-01

    Maintaining the health of aquatic systems is an essential component of sustainable catchmentmanagement, however, degradation of water quality and aquatic habitat continues to challenge scientistsand policy-makers. To support management and restoration efforts aquatic system models are requiredthat are able to capture the often complex trajectories that these systems display in response to multiplestressors. This paper explores the abilities and limitations of current model approaches in meeting this chal-lenge, and outlines a strategy based on integration of flexible model libraries and data from observationnetworks, within a learning framework, as a means to improve the accuracy and scope of model predictions.The framework is comprised of a data assimilation component that utilizes diverse data streams from sensornetworks, and a second component whereby model structural evolution can occur once the model isassessed against theoretically relevant metrics of system function. Given the scale and transdisciplinarynature of the prediction challenge, network science initiatives are identified as a means to develop and inte-grate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to modelassessment that can guide model adaptation. We outline how such a framework can help us explore thetheory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry,and, in doing so, also advance the role of prediction in aquatic ecosystem management.

  8. Hybrid modelling framework by using mathematics-based and information-based methods

    NASA Astrophysics Data System (ADS)

    Ghaboussi, J.; Kim, J.; Elnashai, A.

    2010-06-01

    Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

  9. Theories, models, and frameworks related to sleep-wake disturbances in the context of cancer.

    PubMed

    Otte, Julie L; Carpenter, Janet S

    2009-01-01

    The purpose of this article was to review theories, models, and frameworks of sleep disturbances referenced in the cancer literature. Sleep-wake disturbances in cancer are a significant problem that negatively affects quality of life. There is no previously published review of the theories, models, or frameworks used to study sleep-wake disturbances in the context of cancer. Describing existing theories or models and their application in cancer is important to advance knowledge in this area. Two theories and 9 models were identified for review. These have been used to further understand the problem of sleep-wake disturbances as a primary or secondary symptom within the cancer literature. Searches were conducted from January 1, 1970, to July 31, 2008, to find relevant articles using 4 electronic databases: MEDLINE, CINAHL, PubMed, and PsychINFO. On the basis of the search, 73 descriptive or intervention studies were identified and reviewed. Most research was atheoretical, with no identified theory, model, or framework. In studies that did use theory or models, few were applied in more than one study. Although several commonalities across models did emerge, a more comprehensive and widely used model could help guide nursing research to facilitate effective symptom management for this prominent problem in cancer.

  10. Smart Frameworks and Self-Describing Models: Model Metadata for Automated Coupling of Hydrologic Process Components (Invited)

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.

    2013-12-01

    Model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that allow heterogeneous sets of process models to be assembled in a plug-and-play manner to create composite "system models". These mechanisms facilitate code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers, e.g. by requiring them to provide their output in specific forms that meet the input requirements of other models. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can compare the answers to these queries with similar answers from other process models in a collection and then automatically call framework

  11. A Novel, Physics-Based Data Analytics Framework for Reducing Systematic Model Errors

    NASA Astrophysics Data System (ADS)

    Wu, W.; Liu, Y.; Vandenberghe, F. C.; Knievel, J. C.; Hacker, J.

    2015-12-01

    Most climate and weather models exhibit systematic biases, such as under predicted diurnal temperatures in the WRF (Weather Research and Forecasting) model. General approaches to alleviate the systematic biases include improving model physics and numerics, improving data assimilation, and bias correction through post-processing. In this study, we developed a novel, physics-based data analytics framework in post processing by taking advantage of ever-growing high-resolution (spatial and temporal) observational and modeling data. In the framework, a spatiotemporal PCA (Principal Component Analysis) is first applied on the observational data to filter out noise and information on scales that a model may not be able to resolve. The filtered observations are then used to establish regression relationships with archived model forecasts in the same spatiotemporal domain. The regressions along with the model forecasts predict the projected observations in the forecasting period. The pre-regression PCA procedure strengthens regressions, and enhances predictive skills. We then combine the projected observations with the past observations to apply PCA iteratively to derive the final forecasts. This post-regression PCA reconstructs variances and scales of information that are lost in the regression. The framework was examined and validated with 24 days of 5-minute observational data and archives from the WRF model at 27 stations near Dugway Proving Ground, Utah. The validation shows significant bias reduction in the diurnal cycle of predicted surface air temperature compared to the direct output from the WRF model. Additionally, unlike other post-processing bias correction schemes, the data analytics framework does not require long-term historic data and model archives. A week or two of the data is enough to take into account changes in weather regimes. The program, written in python, is also computationally efficient.

  12. Coupled model of INM-IO global ocean model, CICE sea ice model and SCM OIAS framework

    NASA Astrophysics Data System (ADS)

    Bayburin, Ruslan; Rashit, Ibrayev; Konstantin, Ushakov; Vladimir, Kalmykov; Gleb, Dyakonov

    2015-04-01

    Status of coupled Arctic model of ocean and sea ice is presented. Model consists of INM IO global ocean component of high resolution, Los Alamos National Laboratory CICE sea ice model and a framework SCM OIAS for the ocean-ice-atmosphere-land coupled modeling on massively-parallel architectures. Model is currently under development at the Institute of Numerical Mathematics (INM), Hydrometeorological Center (HMC) and P.P. Shirshov Institute of Oceanology (IO). Model is aimed at modeling of intra-annual variability of hydrodynamics in Arctic and. The computational characteristics of the world ocean-sea ice coupled model governed by SCM OIAS are presented. The model is parallelized using MPI technologies and currently can use efficiently up to 5000 cores. Details of programming implementation, computational configuration and physical phenomena parametrization are analyzed in terms of intercoupling complex. Results of five year computational experiment of sea ice, snow and ocean state evolution in Arctic region on tripole grid with horizontal resolution of 3-5 kilometers, closed by atmospheric forcing field from repeating "normal" annual course taken from CORE1 experiment data base are presented and analyzed in terms of the state of vorticity and warm Atlantic water expansion.

  13. An interdisciplinary framework for participatory modeling design and evaluation—What makes models effective participatory decision tools?

    NASA Astrophysics Data System (ADS)

    Falconi, Stefanie M.; Palmer, Richard N.

    2017-02-01

    Increased requirements for public involvement in water resources management (WRM) over the past century have stimulated the development of more collaborative decision-making methods. Participatory modeling (PM) uses computer models to inform and engage stakeholders in the planning process in order to influence collaborative decisions in WRM. Past evaluations of participatory models focused on process and final outcomes, yet, were hindered by diversity of purpose and inconsistent documentation. This paper presents a two-stage framework for evaluating PM based on mechanisms for improving model effectiveness as participatory tools. The five dimensions characterize the "who, when, how, and why" of each participatory effort (stage 1). Models are evaluated as "boundary objects," a concept used to describe tools that bridge understanding and translate different bodies of knowledge to improve credibility, salience, and legitimacy (stage 2). This evaluation framework is applied to five existing case studies from the literature. Though the goals of participation can be diverse, the novel contribution of the two-stage proposed framework is the flexibility it has to evaluate a wide range of cases that differ in scope, modeling approach, and participatory context. Also, the evaluation criteria provide a structured vocabulary based on clear mechanisms that extend beyond previous process-based and outcome-based evaluations. Effective models are those that take advantage of mechanisms that facilitate dialogue and resolution and improve the accessibility and applicability of technical knowledge. Furthermore, the framework can help build more complete records and systematic documentation of evidence to help standardize the field of PM.

  14. Toward a Model Framework of Generalized Parallel Componential Processing of Multi-Symbol Numbers

    ERIC Educational Resources Information Center

    Huber, Stefan; Cornelsen, Sonja; Moeller, Korbinian; Nuerk, Hans-Christoph

    2015-01-01

    In this article, we propose and evaluate a new model framework of parallel componential multi-symbol number processing, generalizing the idea of parallel componential processing of multi-digit numbers to the case of negative numbers by considering the polarity signs similar to single digits. In a first step, we evaluated this account by defining…

  15. MODELING FRAMEWORK FOR EVALUATING SEDIMENTATION IN STREAM NETWORKS: FOR USE IN SEDIMENT TMDL ANALYSIS

    EPA Science Inventory

    A modeling framework that can be used to evaluate sedimentation in stream networks is described. This methodology can be used to determine sediment Total Maximum Daily Loads (TMDLs) in sediment impaired waters, and provide the necessary hydrodynamic and sediment-related data t...

  16. Instructional Dissent in the College Classroom: Using the Instructional Beliefs Model as a Framework

    ERIC Educational Resources Information Center

    LaBelle, Sara; Martin, Matthew M.; Weber, Keith

    2013-01-01

    We examined the impact of instructor characteristics and student beliefs on students' decisions to enact instructional dissent using the Instructional Beliefs Model (IBM) as a framework. Students (N = 244) completed survey questionnaires assessing their perceptions of instructors' clarity, nonverbal immediacy, and affirming style, as well as their…

  17. A framework for evaluating forest landscape model predictions using empirical data and knowledge

    Treesearch

    Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia. Wang

    2014-01-01

    Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

  18. An Analytical Framework for Evaluating E-Commerce Business Models and Strategies.

    ERIC Educational Resources Information Center

    Lee, Chung-Shing

    2001-01-01

    Considers electronic commerce as a paradigm shift, or a disruptive innovation, and presents an analytical framework based on the theories of transaction costs and switching costs. Topics include business transformation process; scale effect; scope effect; new sources of revenue; and e-commerce value creation model and strategy. (LRW)

  19. PIRPOSAL Model of Integrative STEM Education: Conceptual and Pedagogical Framework for Classroom Implementation

    ERIC Educational Resources Information Center

    Wells, John G.

    2016-01-01

    The PIRPOSAL model is both a conceptual and pedagogical framework intended for use as a pragmatic guide to classroom implementation of Integrative STEM Education. Designerly questioning prompted by a "need to know" serves as the basis for transitioning student designers within and among multiple phases while they progress toward an…

  20. A Quality Framework for Continuous Improvement of e-Learning: The e-Learning Maturity Model

    ERIC Educational Resources Information Center

    Marshall, Stephen

    2010-01-01

    The E-Learning Maturity Model (eMM) is a quality improvement framework designed to help institutional leaders assess their institution's e-learning maturity. This paper reviews the eMM, drawing on examples of assessments conducted in New Zealand, Australia, the UK and the USA to show how it helps institutional leaders assess and compare their…

  1. An Analytical Framework for Evaluating E-Commerce Business Models and Strategies.

    ERIC Educational Resources Information Center

    Lee, Chung-Shing

    2001-01-01

    Considers electronic commerce as a paradigm shift, or a disruptive innovation, and presents an analytical framework based on the theories of transaction costs and switching costs. Topics include business transformation process; scale effect; scope effect; new sources of revenue; and e-commerce value creation model and strategy. (LRW)

  2. Toward a Model Framework of Generalized Parallel Componential Processing of Multi-Symbol Numbers

    ERIC Educational Resources Information Center

    Huber, Stefan; Cornelsen, Sonja; Moeller, Korbinian; Nuerk, Hans-Christoph

    2015-01-01

    In this article, we propose and evaluate a new model framework of parallel componential multi-symbol number processing, generalizing the idea of parallel componential processing of multi-digit numbers to the case of negative numbers by considering the polarity signs similar to single digits. In a first step, we evaluated this account by defining…

  3. A Supervisory Issue When Utilizing the ASCA National Model Framework in School Counseling

    ERIC Educational Resources Information Center

    Bryant-Young, Necole; Bell, Catherine A.; Davis, Kalena M.

    2014-01-01

    The authors discuss a supervisory issue, in that, the ASCA National Model: A Framework for School Counseling Programs does not emphasize on-going supervision where ethical expectations of supervisors and supervisees in a school setting are clearly defined. Subsequently, the authors highlight supervisor expectations stated with the ASCA National…

  4. Beyond a Definition: Toward a Framework for Designing and Specifying Mentoring Models

    ERIC Educational Resources Information Center

    Dawson, Phillip

    2014-01-01

    More than three decades of mentoring research has yet to converge on a unifying definition of mentoring; this is unsurprising given the diversity of relationships classified as mentoring. This article advances beyond a definition toward a common framework for specifying mentoring models. Sixteen design elements were identified from the literature…

  5. Argumentation, Dialogue Theory, and Probability Modeling: Alternative Frameworks for Argumentation Research in Education

    ERIC Educational Resources Information Center

    Nussbaum, E. Michael

    2011-01-01

    Toulmin's model of argumentation, developed in 1958, has guided much argumentation research in education. However, argumentation theory in philosophy and cognitive science has advanced considerably since 1958. There are currently several alternative frameworks of argumentation that can be useful for both research and practice in education. These…

  6. PIRPOSAL Model of Integrative STEM Education: Conceptual and Pedagogical Framework for Classroom Implementation

    ERIC Educational Resources Information Center

    Wells, John G.

    2016-01-01

    The PIRPOSAL model is both a conceptual and pedagogical framework intended for use as a pragmatic guide to classroom implementation of Integrative STEM Education. Designerly questioning prompted by a "need to know" serves as the basis for transitioning student designers within and among multiple phases while they progress toward an…

  7. A Model Driven Framework to Address Challenges in a Mobile Learning Environment

    ERIC Educational Resources Information Center

    Khaddage, Ferial; Christensen, Rhonda; Lai, Wing; Knezek, Gerald; Norris, Cathie; Soloway, Elliot

    2015-01-01

    In this paper a review of the pedagogical, technological, policy and research challenges and concepts underlying mobile learning is presented, followed by a brief description of categories of implementations. A model Mobile learning framework and dynamic criteria for mobile learning implementations are proposed, along with a case study of one site…

  8. Map Resource Packet: Course Models for the History-Social Science Framework, Grade Seven.

    ERIC Educational Resources Information Center

    California State Dept. of Education, Sacramento.

    This packet of maps is an auxiliary resource to the "World History and Geography: Medieval and Early Modern Times. Course Models for the History-Social Science Framework, Grade Seven." The set includes: outline, precipitation, and elevation maps; maps for locating key places; landform maps; and historical maps. The list of maps are…

  9. A Model Driven Framework to Address Challenges in a Mobile Learning Environment

    ERIC Educational Resources Information Center

    Khaddage, Ferial; Christensen, Rhonda; Lai, Wing; Knezek, Gerald; Norris, Cathie; Soloway, Elliot

    2015-01-01

    In this paper a review of the pedagogical, technological, policy and research challenges and concepts underlying mobile learning is presented, followed by a brief description of categories of implementations. A model Mobile learning framework and dynamic criteria for mobile learning implementations are proposed, along with a case study of one site…

  10. Graph Unification and Tangram Hypothesis Explanation Representation (GATHER) and System and Component Modeling Framework (SCMF)

    DTIC Science & Technology

    2008-08-01

    AFRL-RI-RS-TR-2008-228 Final Technical Report August 2008 GRAPH UNIFICATION AND TANGRAM HYPOTHESIS EXPLANATION REPRESENTATION...AND SUBTITLE GRAPH UNIFICATION AND TANGRAM HYPOTHESIS EXPLANATION REPRESENTATION (GATHER) AND SYSTEM AND COMPONENT MODELING FRAMEWORK (SCMF) 5a...31  ii LIST OF FIGURES Figure 1: Tangram High Level Architecture

  11. A Study of the Model of Mastery as a Theoretical Framework for Coaching Teachers Writing Workshop

    ERIC Educational Resources Information Center

    Kimbrell, Jennifer L.

    2010-01-01

    The study investigated a coach's use of a theoretical framework called the Model of Mastery to assist three teachers in becoming self-regulated in the teaching of writing workshop by moving them through three settings: acquisition, consolidation, and consultation. The goal of the coach was to assist teachers in developing expertise in procedural,…

  12. Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

    EPA Science Inventory

    Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...

  13. Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

    EPA Science Inventory

    Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...

  14. Leading a New Pedagogical Approach to Australian Curriculum Mathematics: Using the Dual Mathematical Modelling Cycle Framework

    ERIC Educational Resources Information Center

    Lamb, Janeen; Kawakami, Takashi; Saeki, Akihiko; Matsuzaki, Akio

    2014-01-01

    The aim of this study was to investigate the use of the "dual mathematical modelling cycle framework" as one way to meet the espoused goals of the Australian Curriculum Mathematics. This study involved 23 Year 6 students from one Australian primary school who engaged in an "Oil Tank Task" that required them to develop two…

  15. Map Resource Packet: Course Models for the History-Social Science Framework, Grade Seven.

    ERIC Educational Resources Information Center

    California State Dept. of Education, Sacramento.

    This packet of maps is an auxiliary resource to the "World History and Geography: Medieval and Early Modern Times. Course Models for the History-Social Science Framework, Grade Seven." The set includes: outline, precipitation, and elevation maps; maps for locating key places; landform maps; and historical maps. The list of maps are…

  16. Beyond a Definition: Toward a Framework for Designing and Specifying Mentoring Models

    ERIC Educational Resources Information Center

    Dawson, Phillip

    2014-01-01

    More than three decades of mentoring research has yet to converge on a unifying definition of mentoring; this is unsurprising given the diversity of relationships classified as mentoring. This article advances beyond a definition toward a common framework for specifying mentoring models. Sixteen design elements were identified from the literature…

  17. MODELING FRAMEWORK FOR EVALUATING SEDIMENTATION IN STREAM NETWORKS: FOR USE IN SEDIMENT TMDL ANALYSIS

    EPA Science Inventory

    A modeling framework that can be used to evaluate sedimentation in stream networks is described. This methodology can be used to determine sediment Total Maximum Daily Loads (TMDLs) in sediment impaired waters, and provide the necessary hydrodynamic and sediment-related data t...

  18. A common framework for the development and analysis of process-based hydrological models

    NASA Astrophysics Data System (ADS)

    Clark, Martyn; Kavetski, Dmitri; Fenicia, Fabrizio; Gupta, Hoshin

    2013-04-01

    provide a common framework for model development and analysis. We recognize that the majority of process-based hydrological models use the same set of physics - most models use Darcy's Law to represent the flow of water through the soil matrix and Fourier's Law for thermodynamics. Our numerical model uses robust solutions of the hydrology and thermodynamic governing equations as the structural core, and incorporates multiple options to represent the impact of different modeling decisions, including different methods to represent spatial variability and different parameterizations of surface fluxes and shallow groundwater. Our analysis isolates individual modeling decisions and uses orthogonal diagnostic signatures to evaluate model behavior. Application of this framework in research basins demonstrates that the combination of (1) flexibility in the numerical model and (2) comprehensive scrutiny of orthogonal signatures provides a powerful approach to identify the suitability of different modeling options and different model parameter values. We contend that this common framework has general utility, and its widespread application in both research basins and at larger spatial scales will help accelerate the development of process-based hydrologic models.

  19. Groundwater modelling in decision support: reflections on a unified conceptual framework

    NASA Astrophysics Data System (ADS)

    Doherty, John; Simmons, Craig T.

    2013-11-01

    Groundwater models are commonly used as basis for environmental decision-making. There has been discussion and debate in recent times regarding the issue of model simplicity and complexity. This paper contributes to this ongoing discourse. The selection of an appropriate level of model structural and parameterization complexity is not a simple matter. Although the metrics on which such selection should be based are simple, there are many competing, and often unquantifiable, considerations which must be taken into account as these metrics are applied. A unified conceptual framework is introduced and described which is intended to underpin groundwater modelling in decision support with a direct focus on matters regarding model simplicity and complexity.

  20. Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

    SciTech Connect

    Ackerman, Thomas P.

    2015-03-01

    The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained